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diff --git a/reports/first_pages.html b/reports/first_pages.html index 9280eca9..1fa50094 100644 --- a/reports/first_pages.html +++ b/reports/first_pages.html @@ -38,19 +38,73 @@ <br/><b>University of California at Berkeley</b><br/>Technical Report No. UCB/EECS-2016-147 <br/>http://www.eecs.berkeley.edu/Pubs/TechRpts/2016/EECS-2016-147.html <br/>August 14, 2016 -</td><td>('3173667', 'Mert Pilanci', 'mert pilanci')</td><td></td></tr><tr><td>612075999e82596f3b42a80e6996712cc52880a3</td><td>CNNs with Cross-Correlation Matching for Face Recognition in Video +</td><td>('3173667', 'Mert Pilanci', 'mert pilanci')</td><td></td></tr><tr><td>61f04606528ecf4a42b49e8ac2add2e9f92c0def</td><td>Deep Deformation Network for Object Landmark +<br/>Localization +<br/>NEC Laboratories America, Department of Media Analytics +</td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('46468682', 'Feng Zhou', 'feng zhou')</td><td>{xiangyu,manu}@nec-labs.com, zhfe99@gmail.com +</td></tr><tr><td>612075999e82596f3b42a80e6996712cc52880a3</td><td>CNNs with Cross-Correlation Matching for Face Recognition in Video <br/>Surveillance Using a Single Training Sample Per Person <br/><b>University of Texas at Arlington, TX, USA</b><br/>2École de technologie supérieure, Université du Québec, Montreal, Canada </td><td>('3046171', 'Mostafa Parchami', 'mostafa parchami')<br/>('2805645', 'Saman Bashbaghi', 'saman bashbaghi')<br/>('1697195', 'Eric Granger', 'eric granger')</td><td>mostafa.parchami@mavs.uta.edu, bashbaghi@livia.etsmtl.ca and eric.granger@etsmtl.ca +</td></tr><tr><td>61efeb64e8431cfbafa4b02eb76bf0c58e61a0fa</td><td>Merging Datasets Through Deep learning +<br/>IBM Research +<br/><b>Yeshiva University</b><br/>IBM Research +</td><td>('35970154', 'Kavitha Srinivas', 'kavitha srinivas')<br/>('51428397', 'Abraham Gale', 'abraham gale')<br/>('2828094', 'Julian Dolby', 'julian dolby')</td><td></td></tr><tr><td>61e9e180d3d1d8b09f1cc59bdd9f98c497707eff</td><td>Semi-supervised learning of +<br/>facial attributes in video +<br/>1INRIA, WILLOW, Laboratoire d’Informatique de l’Ecole Normale Sup´erieure, +<br/>ENS/INRIA/CNRS UMR 8548 +<br/><b>University of Oxford</b></td><td>('1877079', 'Neva Cherniavsky', 'neva cherniavsky')<br/>('1785596', 'Ivan Laptev', 'ivan laptev')<br/>('1782755', 'Josef Sivic', 'josef sivic')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td></td></tr><tr><td>6193c833ad25ac27abbde1a31c1cabe56ce1515b</td><td>Trojaning Attack on Neural Networks +<br/><b>Purdue University, 2Nanjing University</b></td><td>('3347155', 'Yingqi Liu', 'yingqi liu')<br/>('2026855', 'Shiqing Ma', 'shiqing ma')<br/>('3216258', 'Yousra Aafer', 'yousra aafer')<br/>('2547748', 'Wen-Chuan Lee', 'wen-chuan lee')<br/>('3293342', 'Juan Zhai', 'juan zhai')<br/>('3155328', 'Weihang Wang', 'weihang wang')<br/>('1771551', 'Xiangyu Zhang', 'xiangyu zhang')</td><td>liu1751@purdue.edu, ma229@purdue.edu, yaafer@purdue.edu, lee1938@purdue.edu, zhaijuan@nju.edu.cn, +<br/>wang1315@cs.purdue.edu, xyzhang@cs.purdue.edu </td></tr><tr><td>614a7c42aae8946c7ad4c36b53290860f6256441</td><td>1 <br/>Joint Face Detection and Alignment using <br/>Multi-task Cascaded Convolutional Networks -</td><td>('3393556', 'Kaipeng Zhang', 'kaipeng zhang')<br/>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('32787758', 'Zhifeng Li', 'zhifeng li')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>0d746111135c2e7f91443869003d05cde3044beb</td><td>PARTIAL FACE DETECTION FOR CONTINUOUS AUTHENTICATION +</td><td>('3393556', 'Kaipeng Zhang', 'kaipeng zhang')<br/>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('32787758', 'Zhifeng Li', 'zhifeng li')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>614079f1a0d0938f9c30a1585f617fa278816d53</td><td>Automatic Detection of ADHD and ASD from Expressive Behaviour in +<br/>RGBD Data +<br/><b>School of Computer Science, The University of Nottingham</b><br/>2Nottingham City Asperger Service & ADHD Clinic +<br/><b>Institute of Mental Health, The University of Nottingham</b></td><td>('2736086', 'Shashank Jaiswal', 'shashank jaiswal')<br/>('1795528', 'Michel F. Valstar', 'michel f. valstar')<br/>('38690723', 'Alinda Gillott', 'alinda gillott')<br/>('2491166', 'David Daley', 'david daley')</td><td></td></tr><tr><td>0d746111135c2e7f91443869003d05cde3044beb</td><td>PARTIAL FACE DETECTION FOR CONTINUOUS AUTHENTICATION <br/>(cid:63)Department of Electrical and Computer Engineering and the Center for Automation Research, <br/><b>Rutgers, The State University of New Jersey, 723 CoRE, 94 Brett Rd, Piscataway, NJ</b><br/><b>UMIACS, University of Maryland, College Park, MD</b><br/>§Google Inc., 1600 Amphitheatre Parkway, Mountain View, CA 94043 </td><td>('3152615', 'Upal Mahbub', 'upal mahbub')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('2406413', 'Brandon Barbello', 'brandon barbello')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>umahbub@umiacs.umd.edu, vishal.m.patel@rutgers.edu, <br/>dchandra@google.com, bbarbello@google.com, rama@umiacs.umd.edu -</td></tr><tr><td>0d88ab0250748410a1bc990b67ab2efb370ade5d</td><td>Author(s) : +</td></tr><tr><td>0da75b0d341c8f945fae1da6c77b6ec345f47f2a</td><td>121 +<br/>The Effect of Computer-Generated Descriptions on Photo- +<br/>Sharing Experiences of People With Visual Impairments +<br/><b>YUHANG ZHAO, Information Science, Cornell Tech, Cornell University</b><br/>SHAOMEI WU, Facebook Inc. +<br/>LINDSAY REYNOLDS, Facebook Inc. +<br/><b>SHIRI AZENKOT, Information Science, Cornell Tech, Cornell University</b><br/>Like sighted people, visually impaired people want to share photographs on social networking services, but +<br/>find it difficult to identify and select photos from their albums. We aimed to address this problem by +<br/>incorporating state-of-the-art computer-generated descriptions into Facebook’s photo-sharing feature. We +<br/>interviewed 12 visually impaired participants to understand their photo-sharing experiences and designed +<br/>a photo description feature for the Facebook mobile application. We evaluated this feature with six +<br/>participants in a seven-day diary study. We found that participants used the descriptions to recall and +<br/>organize their photos, but they hesitated to upload photos without a sighted person’s input. In addition to +<br/>basic information about photo content, participants wanted to know more details about salient objects and +<br/>people, and whether the photos reflected their personal aesthetic. We discuss these findings from the lens +<br/>of self-disclosure and self-presentation theories and propose new computer vision research directions that +<br/>will better support visual content sharing by visually impaired people. +<br/>CCS Concepts: • Information interfaces and presentations → Multimedia and information systems; • +<br/>Computer and society → Social issues +<br/>impairments; computer-generated descriptions; SNSs; photo sharing; self-disclosure; self- +<br/>KEYWORDS +<br/>Visual +<br/>presentation +<br/>ACM Reference format: +<br/>2017. The Effect of Computer-Generated Descriptions On Photo-Sharing Experiences of People With Visual +<br/>Impairments. Proc. ACM Hum.-Comput. Interact. 1, 1. 121 (January 2017), 24 pages. +<br/>DOI: 10.1145/3134756 +<br/>1 INTRODUCTION +<br/>Sharing memories and experiences via photos is a common way to engage with others on social +<br/>networking services (SNSs) [39,46,51]. For instance, Facebook users uploaded more than 350 +<br/>million photos a day [24] and Twitter, which initially supported only text in tweets, now has +<br/>more than 28.4% of tweets containing images [39]. Visually impaired people (both blind and low +<br/>vision) have a strong presence on SNS and are interested in sharing photos [50]. They take +<br/>photos for the same reasons that sighted people do: sharing daily moments with their sighted +<br/> +<br/>Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee +<br/>provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and +<br/>the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. +</td><td></td><td></td></tr><tr><td>0d88ab0250748410a1bc990b67ab2efb370ade5d</td><td>Author(s) : <br/>ERROR HANDLING IN MULTIMODAL BIOMETRIC SYSTEMS USING <br/>RELIABILITY MEASURES (ThuPmOR6) <br/>(EPFL, Switzerland) @@ -200,7 +254,13 @@ <br/>jyoti.joshi@uwaterloo.ca <br/>jhoey@cs.uwaterloo.ca <br/>tom.gedeon@anu.edu.au -</td></tr><tr><td>0d735e7552af0d1dcd856a8740401916e54b7eee</td><td></td><td></td><td></td></tr><tr><td>0d06b3a4132d8a2effed115a89617e0a702c957a</td><td></td><td></td><td></td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td></td><td></td><td></td></tr><tr><td>0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2</td><td><b>University of Nebraska - Lincoln</b><br/>US Army Research +</td></tr><tr><td>0d735e7552af0d1dcd856a8740401916e54b7eee</td><td></td><td></td><td></td></tr><tr><td>0d06b3a4132d8a2effed115a89617e0a702c957a</td><td></td><td></td><td></td></tr><tr><td>0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e</td><td></td><td></td><td></td></tr><tr><td>0d33b6c8b4d1a3cb6d669b4b8c11c2a54c203d1a</td><td>Detection and Tracking of Faces in Videos: A Review +<br/>© 2016 IJEDR | Volume 4, Issue 2 | ISSN: 2321-9939 +<br/>of Related Work +<br/>1Student, 2Assistant Professor +<br/>1, 2Dept. of Electronics & Comm., S S I E T, Punjab, India +<br/>________________________________________________________________________________________________________ +</td><td>('48816689', 'Seema Saini', 'seema saini')</td><td></td></tr><tr><td>0d1d9a603b08649264f6e3b6d5a66bf1e1ac39d2</td><td><b>University of Nebraska - Lincoln</b><br/>US Army Research <br/>2015 <br/>U.S. Department of Defense <br/>Effects of emotional expressions on persuasion @@ -212,6 +272,27 @@ <br/>University of Southern California, wangyuqiong@ymail.com <br/>This Article is brought to you for free and open access by the U.S. Department of Defense at DigitalCommons@University of Nebraska - Lincoln. It has <br/>been accepted for inclusion in US Army Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. +</td></tr><tr><td>0da4c3d898ca2fff9e549d18f513f4898e960aca</td><td>Wang, Y., Thomas, J., Weissgerber, S. C., Kazemini, S., Ul-Haq, I., & +<br/>Quadflieg, S. (2015). The Headscarf Effect Revisited: Further Evidence for a +<br/>336. 10.1068/p7940 +<br/>Peer reviewed version +<br/>Link to published version (if available): +<br/>10.1068/p7940 +<br/>Link to publication record in Explore Bristol Research +<br/>PDF-document +<br/><b>University of Bristol - Explore Bristol Research</b><br/>General rights +<br/>This document is made available in accordance with publisher policies. Please cite only the published +<br/>version using the reference above. Full terms of use are available: +<br/>http://www.bristol.ac.uk/pure/about/ebr-terms.html +<br/>Take down policy +<br/>Explore Bristol Research is a digital archive and the intention is that deposited content should not be +<br/>removed. However, if you believe that this version of the work breaches copyright law please contact +<br/>• Your contact details +<br/><b>Bibliographic details for the item, including a URL</b><br/>• An outline of the nature of the complaint +<br/>On receipt of your message the Open Access Team will immediately investigate your claim, make an +<br/>initial judgement of the validity of the claim and, where appropriate, withdraw the item in question +<br/>from public view. +<br/> </td><td></td><td>open-access@bristol.ac.uk and include the following information in your message: </td></tr><tr><td>951368a1a8b3c5cd286726050b8bdf75a80f7c37</td><td>A Family of Online Boosting Algorithms <br/><b>University of California, San Diego</b><br/><b>University of California, Merced</b><br/><b>University of California, San Diego</b></td><td>('2490700', 'Boris Babenko', 'boris babenko')<br/>('37144787', 'Ming-Hsuan Yang', 'ming-hsuan yang')<br/>('1769406', 'Serge Belongie', 'serge belongie')</td><td>bbabenko@cs.ucsd.edu <br/>mhyang@ucmerced.edu @@ -238,7 +319,13 @@ <br/>http://www.ieee.org/ <br/>Griffith Research Online <br/>https://research-repository.griffith.edu.au -</td><td></td><td></td></tr><tr><td>951f21a5671a4cd14b1ef1728dfe305bda72366f</td><td>International Journal of Science and Research (IJSR) +</td><td></td><td></td></tr><tr><td>959bcb16afdf303c34a8bfc11e9fcc9d40d76b1c</td><td>Temporal Coherency based Criteria for Predicting +<br/>Video Frames using Deep Multi-stage Generative +<br/>Adversarial Networks +<br/>Visualization and Perception Laboratory +<br/>Department of Computer Science and Engineering +<br/><b>Indian Institute of Technology Madras, Chennai, India</b></td><td>('29901316', 'Prateep Bhattacharjee', 'prateep bhattacharjee')<br/>('1680398', 'Sukhendu Das', 'sukhendu das')</td><td>1prateepb@cse.iitm.ac.in, 2sdas@iitm.ac.in +</td></tr><tr><td>951f21a5671a4cd14b1ef1728dfe305bda72366f</td><td>International Journal of Science and Research (IJSR) <br/>ISSN (Online): 2319-7064 <br/>Impact Factor (2012): 3.358 <br/>Use of ℓ2/3-norm Sparse Representation for Facial @@ -278,19 +365,31 @@ <br/>873 <br/>A Novel Incremental Principal Component Analysis <br/>and Its Application for Face Recognition -</td><td>('1776124', 'Haitao Zhao', 'haitao zhao')<br/>('1768574', 'Pong Chi Yuen', 'pong chi yuen')</td><td></td></tr><tr><td>958c599a6f01678513849637bec5dc5dba592394</td><td>Noname manuscript No. +</td><td>('1776124', 'Haitao Zhao', 'haitao zhao')<br/>('1768574', 'Pong Chi Yuen', 'pong chi yuen')</td><td></td></tr><tr><td>95ea564bd983129ddb5535a6741e72bb1162c779</td><td>Multi-Task Learning by Deep Collaboration and +<br/>Application in Facial Landmark Detection +<br/><b>Laval University, Qu bec, Canada</b></td><td>('2758280', 'Ludovic Trottier', 'ludovic trottier')<br/>('2310695', 'Philippe Giguère', 'philippe giguère')<br/>('1700926', 'Brahim Chaib-draa', 'brahim chaib-draa')</td><td>ludovic.trottier.1@ulaval.ca +<br/>{philippe.giguere,brahim.chaib-draa}@ift.ulaval.ca +</td></tr><tr><td>958c599a6f01678513849637bec5dc5dba592394</td><td>Noname manuscript No. <br/>(will be inserted by the editor) <br/>Generalized Zero-Shot Learning for Action <br/>Recognition with Web-Scale Video Data <br/>Received: date / Accepted: date -</td><td>('2473509', 'Kun Liu', 'kun liu')<br/>('8984539', 'Wenbing Huang', 'wenbing huang')</td><td></td></tr><tr><td>59be98f54bb4ed7a2984dc6a3c84b52d1caf44eb</td><td>A Deep-Learning Approach to Facial Expression Recognition +</td><td>('2473509', 'Kun Liu', 'kun liu')<br/>('8984539', 'Wenbing Huang', 'wenbing huang')</td><td></td></tr><tr><td>950171acb24bb24a871ba0d02d580c09829de372</td><td>Speeding up 2D-Warping for Pose-Invariant Face Recognition +<br/><b>Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Germany</b></td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('1685956', 'Hermann Ney', 'hermann ney')</td><td>surname@cs.rwth-aachen.de +</td></tr><tr><td>59be98f54bb4ed7a2984dc6a3c84b52d1caf44eb</td><td>A Deep-Learning Approach to Facial Expression Recognition <br/>with Candid Images <br/><b>CUNY City College</b><br/>Alibaba. Inc <br/><b>IBM China Research Lab</b><br/><b>CUNY Graduate Center and City College</b></td><td>('40617554', 'Wei Li', 'wei li')<br/>('1713016', 'Min Li', 'min li')<br/>('1703625', 'Zhong Su', 'zhong su')<br/>('4697712', 'Zhigang Zhu', 'zhigang zhu')</td><td>lwei000@citymail.cuny.edu <br/>mushi.lm@alibaba.inc <br/>suzhong@cn.ibm.com <br/>zhu@cs.ccny.cuny.edu -</td></tr><tr><td>591a737c158be7b131121d87d9d81b471c400dba</td><td>Affect Valence Inference From Facial Action Unit Spectrograms +</td></tr><tr><td>59fc69b3bc4759eef1347161e1248e886702f8f7</td><td>Final Report of Final Year Project +<br/>HKU-Face: A Large Scale Dataset for +<br/>Deep Face Recognition +<br/>3035141841 +<br/>COMP4801 Final Year Project +<br/>Project Code: 17007 +</td><td>('40456402', 'Haoyu Li', 'haoyu li')</td><td></td></tr><tr><td>591a737c158be7b131121d87d9d81b471c400dba</td><td>Affect Valence Inference From Facial Action Unit Spectrograms <br/>MIT Media Lab <br/>MA 02139, USA <br/>MIT Media Lab @@ -305,7 +404,11 @@ <br/>picard@mit.edu </td></tr><tr><td>59bfeac0635d3f1f4891106ae0262b81841b06e4</td><td>Face Verification Using the LARK Face <br/>Representation -</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>590628a9584e500f3e7f349ba7e2046c8c273fcf</td><td></td><td></td><td></td></tr><tr><td>593234ba1d2e16a887207bf65d6b55bbc7ea2247</td><td>Combining Language Sources and Robust +</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>59efb1ac77c59abc8613830787d767100387c680</td><td>DIF : Dataset of Intoxicated Faces for Drunk Person +<br/>Identification +<br/><b>Indian Institute of Technology Ropar</b><br/><b>Indian Institute of Technology Ropar</b></td><td>('46241736', 'Devendra Pratap Yadav', 'devendra pratap yadav')<br/>('1735697', 'Abhinav Dhall', 'abhinav dhall')</td><td>2014csb1010@iitrpr.ac.in +<br/>abhinav@iitrpr.ac.in +</td></tr><tr><td>590628a9584e500f3e7f349ba7e2046c8c273fcf</td><td></td><td></td><td></td></tr><tr><td>593234ba1d2e16a887207bf65d6b55bbc7ea2247</td><td>Combining Language Sources and Robust <br/>Semantic Relatedness for Attribute-Based <br/>Knowledge Transfer <br/>1 Department of Computer Science, TU Darmstadt @@ -315,7 +418,29 @@ <br/>Cross-Pose Recognition </td><td>('24020847', 'Hung-Cheng Shie', 'hung-cheng shie')<br/>('9640380', 'Cheng-Hua Hsieh', 'cheng-hua hsieh')</td><td></td></tr><tr><td>59e2037f5079794cb9128c7f0900a568ced14c2a</td><td>Clothing and People - A Social Signal Processing Perspective <br/><b>Faculty of Mathematics and Computer Science, University of Barcelona, Barcelona, Spain</b><br/>2 Computer Vision Center, Barcelona, Spain -<br/><b>University of Verona, Verona, Italy</b></td><td>('2084534', 'Maedeh Aghaei', 'maedeh aghaei')<br/>('10724083', 'Federico Parezzan', 'federico parezzan')<br/>('2837527', 'Mariella Dimiccoli', 'mariella dimiccoli')<br/>('1724155', 'Petia Radeva', 'petia radeva')<br/>('1723008', 'Marco Cristani', 'marco cristani')</td><td></td></tr><tr><td>59c9d416f7b3d33141cc94567925a447d0662d80</td><td>Universität des Saarlandes +<br/><b>University of Verona, Verona, Italy</b></td><td>('2084534', 'Maedeh Aghaei', 'maedeh aghaei')<br/>('10724083', 'Federico Parezzan', 'federico parezzan')<br/>('2837527', 'Mariella Dimiccoli', 'mariella dimiccoli')<br/>('1724155', 'Petia Radeva', 'petia radeva')<br/>('1723008', 'Marco Cristani', 'marco cristani')</td><td></td></tr><tr><td>59dac8b460a89e03fa616749a08e6149708dcc3a</td><td>A Convergent Solution to Matrix Bidirectional Projection Based Feature +<br/>Extraction with Application to Face Recognition ∗ +<br/><b>School of Computer, National University of Defense Technology</b><br/>No 137, Yanwachi Street, Kaifu District, +<br/>Changsha, Hunan Province, 410073, P.R. China +</td><td>('3144121', 'Yubin Zhan', 'yubin zhan')<br/>('1969736', 'Jianping Yin', 'jianping yin')<br/>('33793976', 'Xinwang Liu', 'xinwang liu')</td><td>E-mail: {YubinZhan,JPYin,XWLiu}@nudt.edu.cn +</td></tr><tr><td>59e9934720baf3c5df3a0e1e988202856e1f83ce</td><td>UA-DETRAC: A New Benchmark and Protocol for +<br/>Multi-Object Detection and Tracking +<br/><b>University at Albany, SUNY</b><br/>2 School of Computer and Control Engineering, UCAS +<br/>3 Department of Electrical and Computer Engineering, UCSD +<br/>4 National Laboratory of Pattern Recognition, CASIA +<br/><b>University at Albany, SUNY</b><br/><b>Division of Computer Science and Engineering, Hanyang University</b><br/>7 Electrical Engineering and Computer Science, UCM +</td><td>('39774417', 'Longyin Wen', 'longyin wen')<br/>('1910738', 'Dawei Du', 'dawei du')<br/>('1773408', 'Zhaowei Cai', 'zhaowei cai')<br/>('39643145', 'Ming-Ching Chang', 'ming-ching chang')<br/>('3245785', 'Honggang Qi', 'honggang qi')<br/>('33047058', 'Jongwoo Lim', 'jongwoo lim')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>59d225486161b43b7bf6919b4a4b4113eb50f039</td><td>Complex Event Recognition from Images with Few Training Examples +<br/>Irfan Essa∗ +<br/><b>Georgia Institute of Technology</b><br/><b>University of Southern California</b></td><td>('2308598', 'Unaiza Ahsan', 'unaiza ahsan')<br/>('1726241', 'Chen Sun', 'chen sun')<br/>('1945508', 'James Hays', 'james hays')</td><td>uahsan3@gatech.edu +<br/>chensun@google.com +<br/>hays@gatech.edu +<br/>irfan@cc.gatech.edu +</td></tr><tr><td>5945464d47549e8dcaec37ad41471aa70001907f</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Every Moment Counts: Dense Detailed Labeling of Actions in Complex +<br/>Videos +<br/>Received: date / Accepted: date +</td><td>('34149749', 'Serena Yeung', 'serena yeung')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>59c9d416f7b3d33141cc94567925a447d0662d80</td><td>Universität des Saarlandes <br/>Max-Planck-Institut für Informatik <br/>AG5 <br/>Matrix factorization over max-times @@ -339,7 +464,11 @@ <br/>FOR FACE RECOGNITION <br/>1. INTRODUCTION </td><td></td><td></td></tr><tr><td>59420fd595ae745ad62c26ae55a754b97170b01f</td><td>Objects as Attributes for Scene Classification -<br/><b>Stanford University</b></td><td>('33642044', 'Li-Jia Li', 'li-jia li')<br/>('2888806', 'Hao Su', 'hao su')<br/>('7892285', 'Yongwhan Lim', 'yongwhan lim')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>5922e26c9eaaee92d1d70eae36275bb226ecdb2e</td><td>Boosting Classification Based Similarity +<br/><b>Stanford University</b></td><td>('33642044', 'Li-Jia Li', 'li-jia li')<br/>('2888806', 'Hao Su', 'hao su')<br/>('7892285', 'Yongwhan Lim', 'yongwhan lim')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>599adc0dcd4ebcc2a868feedd243b5c3c1bd1d0a</td><td>How Robust is 3D Human Pose Estimation to Occlusion? +<br/><b>Visual Computing Institute, RWTH Aachen University</b><br/>2Robert Bosch GmbH, Corporate Research +</td><td>('2699877', 'Timm Linder', 'timm linder')<br/>('1789756', 'Bastian Leibe', 'bastian leibe')</td><td>{sarandi,leibe}@vision.rwth-aachen.de +<br/>{timm.linder,kaioliver.arras}@de.bosch.com +</td></tr><tr><td>5922e26c9eaaee92d1d70eae36275bb226ecdb2e</td><td>Boosting Classification Based Similarity <br/>Learning by using Standard Distances <br/>Departament d’Informàtica, Universitat de València <br/>Av. de la Universitat s/n. 46100-Burjassot (Spain) @@ -362,6 +491,8 @@ <br/>Information and Communication Management School <br/><b>The University of the Humanities</b><br/>Ulaanbaatar, Mongolia </td><td></td><td>e-mail: basubaer@gmail.com +</td></tr><tr><td>59a6c9333c941faf2540979dcfcb5d503a49b91e</td><td>Sampling Clustering +<br/><b>School of Computer Science and Technology, Shandong University, China</b></td><td>('51016741', 'Ching Tarn', 'ching tarn')<br/>('2413471', 'Yinan Zhang', 'yinan zhang')<br/>('48260402', 'Ye Feng', 'ye feng')</td><td>∗i@ctarn.io </td></tr><tr><td>59031a35b0727925f8c47c3b2194224323489d68</td><td>Sparse Variation Dictionary Learning for Face Recognition with A Single <br/>Training Sample Per Person <br/>ETH Zurich @@ -373,15 +504,25 @@ </td><td>('38188040', 'Dong Xu', 'dong xu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('1686911', 'Stephen Lin', 'stephen lin')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td></td></tr><tr><td>923ede53b0842619831e94c7150e0fc4104e62f7</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE <br/>1293 <br/>ICASSP 2016 -</td><td></td><td></td></tr><tr><td>9264b390aa00521f9bd01095ba0ba4b42bf84d7e</td><td>Displacement Template with Divide-&-Conquer +</td><td></td><td></td></tr><tr><td>92b61b09d2eed4937058d0f9494d9efeddc39002</td><td>Under review in IJCV manuscript No. +<br/>(will be inserted by the editor) +<br/>BoxCars: Improving Vehicle Fine-Grained Recognition using +<br/>3D Bounding Boxes in Traffic Surveillance +<br/>Received: date / Accepted: date +</td><td>('34891870', 'Jakub Sochor', 'jakub sochor')</td><td></td></tr><tr><td>9264b390aa00521f9bd01095ba0ba4b42bf84d7e</td><td>Displacement Template with Divide-&-Conquer <br/>Algorithm for Significantly Improving <br/>Descriptor based Face Recognition Approaches -<br/><b>Wenzhou University, China</b><br/><b>University of Northern British Columbia, Canada</b><br/><b>Aberystwyth University, UK</b></td><td>('1692551', 'Liang Chen', 'liang chen')<br/>('33500699', 'Ling Yan', 'ling yan')<br/>('1990125', 'Yonghuai Liu', 'yonghuai liu')<br/>('39388942', 'Lixin Gao', 'lixin gao')<br/>('3779849', 'Xiaoqin Zhang', 'xiaoqin zhang')</td><td></td></tr><tr><td>920a92900fbff22fdaaef4b128ca3ca8e8d54c3e</td><td>LEARNING PATTERN TRANSFORMATION MANIFOLDS WITH PARAMETRIC ATOM +<br/><b>Wenzhou University, China</b><br/><b>University of Northern British Columbia, Canada</b><br/><b>Aberystwyth University, UK</b></td><td>('1692551', 'Liang Chen', 'liang chen')<br/>('33500699', 'Ling Yan', 'ling yan')<br/>('1990125', 'Yonghuai Liu', 'yonghuai liu')<br/>('39388942', 'Lixin Gao', 'lixin gao')<br/>('3779849', 'Xiaoqin Zhang', 'xiaoqin zhang')</td><td></td></tr><tr><td>92be73dffd3320fe7734258961fe5a5f2a43390e</td><td>TRANSFERRING FACE VERIFICATION NETS TO PAIN AND EXPRESSION REGRESSION +<br/>Dept. of {Computer Science1, Electrical & Computer Engineering2, Radiation Oncology3, Cognitive Science4} +<br/><b>Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b><br/>5Dept. of EE, UESTC, 2006 Xiyuan Ave, Chengdu, Sichuan 611731, China +<br/><b>Tsinghua University, Beijing 100084, China</b></td><td>('39369840', 'Feng Wang', 'feng wang')<br/>('40031188', 'Xiang Xiang', 'xiang xiang')<br/>('1692867', 'Chang Liu', 'chang liu')<br/>('1709073', 'Trac D. Tran', 'trac d. tran')<br/>('3207112', 'Austin Reiter', 'austin reiter')<br/>('1678633', 'Gregory D. Hager', 'gregory d. hager')<br/>('2095823', 'Harry Quon', 'harry quon')<br/>('1709439', 'Jian Cheng', 'jian cheng')<br/>('1746141', 'Alan L. Yuille', 'alan l. yuille')</td><td></td></tr><tr><td>920a92900fbff22fdaaef4b128ca3ca8e8d54c3e</td><td>LEARNING PATTERN TRANSFORMATION MANIFOLDS WITH PARAMETRIC ATOM <br/>SELECTION <br/>Ecole Polytechnique F´ed´erale de Lausanne (EPFL) <br/>Signal Processing Laboratory (LTS4) <br/>Switzerland-1015 Lausanne -</td><td>('12636684', 'Elif Vural', 'elif vural')<br/>('1703189', 'Pascal Frossard', 'pascal frossard')</td><td></td></tr><tr><td>924b14a9e36d0523a267293c6d149bca83e73f3b</td><td>Volume 5, Number 2, pp. 133 -164 +</td><td>('12636684', 'Elif Vural', 'elif vural')<br/>('1703189', 'Pascal Frossard', 'pascal frossard')</td><td></td></tr><tr><td>9207671d9e2b668c065e06d9f58f597601039e5e</td><td>Face Detection Using a 3D Model on +<br/>Face Keypoints +</td><td>('2455529', 'Adrian Barbu', 'adrian barbu')<br/>('3019469', 'Gary Gramajo', 'gary gramajo')</td><td></td></tr><tr><td>924b14a9e36d0523a267293c6d149bca83e73f3b</td><td>Volume 5, Number 2, pp. 133 -164 <br/>Development and Evaluation of a Method <br/>Employed to Identify Internal State <br/>Utilizing Eye Movement Data @@ -400,6 +541,14 @@ <br/>Department of Computer Science, <br/>Centre of Biological Signalling Studies (BIOSS), <br/><b>University of Freiburg, Germany</b></td><td>('2127987', 'Benjamin Drayer', 'benjamin drayer')<br/>('1710872', 'Thomas Brox', 'thomas brox')</td><td>{drayer,brox}@cs.uni-freiburg.de +</td></tr><tr><td>928b8eb47288a05611c140d02441660277a7ed54</td><td>Exploiting Images for Video Recognition with Hierarchical Generative +<br/>Adversarial Networks +<br/>1 Beijing Laboratory of Intelligent Information Technology, School of Computer Science, +<br/><b>Big Data Research Center, University of Electronic Science and Technology of China</b><br/><b>Beijing Institute of Technology</b></td><td>('3450614', 'Feiwu Yu', 'feiwu yu')<br/>('2125709', 'Xinxiao Wu', 'xinxiao wu')<br/>('9177510', 'Yuchao Sun', 'yuchao sun')<br/>('2055900', 'Lixin Duan', 'lixin duan')</td><td>{yufeiwu,wuxinxiao,sunyuchao}@bit.edu.cn, lxduan@uestc.edu.cn +</td></tr><tr><td>926e97d5ce2a6e070f8ec07c5aa7f91d3df90ba0</td><td>Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural +<br/>Networks +<br/>Department of Electrical and Computer Engineering +<br/><b>University of Denver, Denver, CO</b></td><td>('3093835', 'Mohammad H. Mahoor', 'mohammad h. mahoor')</td><td>behzad.hasani@du.edu and mmahoor@du.edu </td></tr><tr><td>92c2dd6b3ac9227fce0a960093ca30678bceb364</td><td>Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published <br/>version when available. <br/>Title @@ -424,7 +573,29 @@ <br/>http://hdl.handle.net/10379/1350 <br/>Some rights reserved. For more information, please see the item record link above. <br/>Downloaded 2018-11-06T00:40:53Z -</td><td></td><td></td></tr><tr><td>922838dd98d599d1d229cc73896d55e7a769aa7c</td><td>Learning Hierarchical Representations for Face Verification +</td><td></td><td></td></tr><tr><td>92e464a5a67582d5209fa75e3b29de05d82c7c86</td><td>Reconstruction for Feature Disentanglement in Pose-invariant Face Recognition +<br/><b>Rutgers University, NJ, USA</b><br/>2NEC Labs America, CA, USA +</td><td>('4340744', 'Xi Peng', 'xi peng')<br/>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')</td><td>{xpeng.cs, dnm}@rutgers.edu, {xiangyu, ksohn, manu}@nec-labs.com +</td></tr><tr><td>927ba64123bd4a8a31163956b3d1765eb61e4426</td><td>Customer satisfaction measuring based on the most +<br/>significant facial emotion +<br/>To cite this version: +<br/>most significant facial emotion. 15th IEEE International Multi-Conference on Systems, Signals +<br/>Devices (SSD 2018), Mar 2018, Hammamet, Tunisia. <hal-01790317> +<br/>HAL Id: hal-01790317 +<br/>https://hal-upec-upem.archives-ouvertes.fr/hal-01790317 +<br/>Submitted on 11 May 2018 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('50101862', 'Rostom Kachouri', 'rostom kachouri')<br/>('50101862', 'Rostom Kachouri', 'rostom kachouri')</td><td></td></tr><tr><td>922838dd98d599d1d229cc73896d55e7a769aa7c</td><td>Learning Hierarchical Representations for Face Verification <br/>with Convolutional Deep Belief Networks <br/>Erik Learned-Miller <br/><b>University of Massachusetts</b><br/><b>University of Michigan</b><br/><b>University of Massachusetts</b><br/>Amherst, MA @@ -489,7 +660,9 @@ <br/>copy-editing and formatting may not be reflected in this document. For a <br/>definitive version of this work, please refer to the published source: <br/>http://dx.doi.org/10.1007/978-3-642-17534-3_72 -</td><td></td><td></td></tr><tr><td>0c741fa0966ba3ee4fc326e919bf2f9456d0cd74</td><td>Facial Age Estimation by Learning from Label Distributions +</td><td></td><td></td></tr><tr><td>923ec0da8327847910e8dd71e9d801abcbc93b08</td><td>Hide-and-Seek: Forcing a Network to be Meticulous for +<br/>Weakly-supervised Object and Action Localization +<br/><b>University of California, Davis</b></td><td>('19553871', 'Krishna Kumar Singh', 'krishna kumar singh')<br/>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td></td></tr><tr><td>0c741fa0966ba3ee4fc326e919bf2f9456d0cd74</td><td>Facial Age Estimation by Learning from Label Distributions <br/><b>School of Mathematical Sciences, Monash University, VIC 3800, Australia</b><br/><b>School of Computer Science and Engineering, Southeast University, Nanjing 210096, China</b><br/><b>National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China</b></td><td>('1735299', 'Xin Geng', 'xin geng')<br/>('2848275', 'Kate Smith-Miles', 'kate smith-miles')<br/>('1692625', 'Zhi-Hua Zhou', 'zhi-hua zhou')</td><td></td></tr><tr><td>0c435e7f49f3e1534af0829b7461deb891cf540a</td><td>Capturing Global Semantic Relationships for Facial Action Unit Recognition <br/><b>Rensselaer Polytechnic Institute</b><br/><b>School of Electrical Engineering and Automation, Harbin Institute of Technology</b><br/><b>School of Computer Science and Technology, University of Science and Technology of China</b></td><td>('2860279', 'Ziheng Wang', 'ziheng wang')<br/>('1830523', 'Yongqiang Li', 'yongqiang li')<br/>('1791319', 'Shangfei Wang', 'shangfei wang')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>{wangz10,liy23,jiq}@rpi.edu <br/>sfwang@ustc.edu.cn @@ -521,7 +694,15 @@ </td><td></td><td></td></tr><tr><td>0c75c7c54eec85e962b1720755381cdca3f57dfb</td><td>2212 <br/>Face Landmark Fitting via Optimized Part <br/>Mixtures and Cascaded Deformable Model -</td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1753384', 'Shaoting Zhang', 'shaoting zhang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>0c1d85a197a1f5b7376652a485523e616a406273</td><td>Joint Registration and Representation Learning for Unconstrained Face +</td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1753384', 'Shaoting Zhang', 'shaoting zhang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>0cf2eecf20cfbcb7f153713479e3206670ea0e9c</td><td>Privacy-Protective-GAN for Face De-identification +<br/><b>Temple University</b></td><td>('50117915', 'Yifan Wu', 'yifan wu')<br/>('46319628', 'Fan Yang', 'fan yang')<br/>('1805398', 'Haibin Ling', 'haibin ling')</td><td>{yifan.wu, fyang, hbling} @temple.edu +</td></tr><tr><td>0ca36ecaf4015ca4095e07f0302d28a5d9424254</td><td>Improving Bag-of-Visual-Words Towards Effective Facial Expressive +<br/>Image Classification +<br/>1Univ. Grenoble Alpes, CNRS, Grenoble INP∗ , GIPSA-lab, 38000 Grenoble, France +<br/>Keywords: +<br/>BoVW, k-means++, Relative Conjunction Matrix, SIFT, Spatial Pyramids, TF.IDF. +</td><td>('10762131', 'Dawood Al Chanti', 'dawood al chanti')<br/>('1788869', 'Alice Caplier', 'alice caplier')</td><td>dawood.alchanti@gmail.com +</td></tr><tr><td>0c1d85a197a1f5b7376652a485523e616a406273</td><td>Joint Registration and Representation Learning for Unconstrained Face <br/>Identification <br/><b>University of Canberra, Australia, Data61 - CSIRO and ANU, Australia</b><br/><b>Khalifa University, Abu Dhabi, United Arab Emirates</b></td><td>('2008898', 'Munawar Hayat', 'munawar hayat')<br/>('1802072', 'Naoufel Werghi', 'naoufel werghi')</td><td>{munawar.hayat,roland.goecke}@canberra.edu.au, salman.khan@csiro.au, naoufel.werghi@kustar.ac.ae </td></tr><tr><td>0ca66283f4fb7dbc682f789fcf6d6732006befd5</td><td>Active Dictionary Learning for Image Representation @@ -533,7 +714,15 @@ <br/>of Doctor of Philosophy <br/>in the Graduate School of Arts and Sciences <br/><b>COLUMBIA UNIVERSITY</b><br/>2003 -</td><td>('1779052', 'Srinivasa G. Narasimhan', 'srinivasa g. narasimhan')</td><td></td></tr><tr><td>0c20fd90d867fe1be2459223a3cb1a69fa3d44bf</td><td>A Monte Carlo Strategy to Integrate Detection +</td><td>('1779052', 'Srinivasa G. Narasimhan', 'srinivasa g. narasimhan')</td><td></td></tr><tr><td>0cfca73806f443188632266513bac6aaf6923fa8</td><td>Predictive Uncertainty in Large Scale Classification +<br/>using Dropout - Stochastic Gradient Hamiltonian +<br/>Monte Carlo. +<br/>Vergara, Diego∗1, Hern´andez, Sergio∗2, Valdenegro-Toro, Mat´ıas∗∗3 and Jorquera, Felipe∗4. +<br/>∗Laboratorio de Procesamiento de Informaci´on Geoespacial, Universidad Cat´olica del Maule, Chile. +<br/>∗∗German Research Centre for Artificial Intelligence, Bremen, Germany. +</td><td></td><td>Email: 1diego.vergara@alu.ucm.cl, 2shernandez@ucm.cl,3matias.valdenegro@dfki.de, +<br/>4f.jorquera.uribe@gmail.com +</td></tr><tr><td>0c20fd90d867fe1be2459223a3cb1a69fa3d44bf</td><td>A Monte Carlo Strategy to Integrate Detection <br/>and Model-Based Face Analysis <br/>Department for Mathematics and Computer Science <br/><b>University of Basel, Switzerland</b></td><td>('2591294', 'Andreas Forster', 'andreas forster')<br/>('34460642', 'Bernhard Egger', 'bernhard egger')<br/>('1687079', 'Thomas Vetter', 'thomas vetter')</td><td>sandro.schoenborn,andreas.forster,bernhard.egger,thomas.vetter@unibas.ch @@ -663,7 +852,12 @@ <br/>Aggregating Local Patches for Scene Recognition </td><td>('40184588', 'Zhe Wang', 'zhe wang')<br/>('39709927', 'Limin Wang', 'limin wang')<br/>('40457196', 'Yali Wang', 'yali wang')<br/>('3047890', 'Bowen Zhang', 'bowen zhang')<br/>('40285012', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>0c60eebe10b56dbffe66bb3812793dd514865935</td><td></td><td></td><td></td></tr><tr><td>0c05f60998628884a9ac60116453f1a91bcd9dda</td><td>Optimizing Open-Ended Crowdsourcing: The Next Frontier in <br/>Crowdsourced Data Management -<br/><b>University of Illinois</b><br/><b>cid:63)Stanford University</b></td><td>('32953042', 'Akash Das Sarma', 'akash das sarma')<br/>('8336538', 'Vipul Venkataraman', 'vipul venkataraman')</td><td></td></tr><tr><td>660b73b0f39d4e644bf13a1745d6ee74424d4a16</td><td></td><td></td><td>3,250+OPEN ACCESS BOOKS106,000+INTERNATIONALAUTHORS AND EDITORS113+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Reviews, Refinements and New Ideas in Face RecognitionDownloaded from: http://www.intechopen.com/books/reviews-refinements-and-new-ideas-in-face-recognitionPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at book.department@intechopen.com </td></tr><tr><td>66d512342355fb77a4450decc89977efe7e55fa2</td><td>Under review as a conference paper at ICLR 2018 +<br/><b>University of Illinois</b><br/><b>cid:63)Stanford University</b></td><td>('32953042', 'Akash Das Sarma', 'akash das sarma')<br/>('8336538', 'Vipul Venkataraman', 'vipul venkataraman')</td><td></td></tr><tr><td>6601a0906e503a6221d2e0f2ca8c3f544a4adab7</td><td>SRTM-2 2/9/06 3:27 PM Page 321 +<br/>Detection of Ancient Settlement Mounds: +<br/>Archaeological Survey Based on the +<br/>SRTM Terrain Model +<br/>B.H. Menze, J.A. Ur, and A.G. Sherratt +</td><td></td><td></td></tr><tr><td>660b73b0f39d4e644bf13a1745d6ee74424d4a16</td><td></td><td></td><td>3,250+OPEN ACCESS BOOKS106,000+INTERNATIONALAUTHORS AND EDITORS113+ MILLIONDOWNLOADSBOOKSDELIVERED TO151 COUNTRIESAUTHORS AMONGTOP 1%MOST CITED SCIENTIST12.2%AUTHORS AND EDITORSFROM TOP 500 UNIVERSITIESSelection of our books indexed in theBook Citation Index in Web of Science™Core Collection (BKCI)Chapter from the book Reviews, Refinements and New Ideas in Face RecognitionDownloaded from: http://www.intechopen.com/books/reviews-refinements-and-new-ideas-in-face-recognitionPUBLISHED BYWorld's largest Science,Technology & Medicine Open Access book publisherInterested in publishing with InTechOpen?Contact us at book.department@intechopen.com </td></tr><tr><td>66d512342355fb77a4450decc89977efe7e55fa2</td><td>Under review as a conference paper at ICLR 2018 <br/>LEARNING NON-LINEAR TRANSFORM WITH DISCRIM- <br/>INATIVE AND MINIMUM INFORMATION LOSS PRIORS <br/>Anonymous authors @@ -686,7 +880,8 @@ <br/>jeffcohn@pitt.edu </td></tr><tr><td>6643a7feebd0479916d94fb9186e403a4e5f7cbf</td><td>Chapter 8 <br/>3D Face Recognition -</td><td>('1737428', 'Nick Pears', 'nick pears')</td><td></td></tr><tr><td>66dcd855a6772d2731b45cfdd75f084327b055c2</td><td>Quality Classified Image Analysis with Application +</td><td>('1737428', 'Nick Pears', 'nick pears')</td><td></td></tr><tr><td>661ca4bbb49bb496f56311e9d4263dfac8eb96e9</td><td>Datasheets for Datasets +</td><td>('2076288', 'Timnit Gebru', 'timnit gebru')<br/>('1722360', 'Hal Daumé', 'hal daumé')</td><td></td></tr><tr><td>66dcd855a6772d2731b45cfdd75f084327b055c2</td><td>Quality Classified Image Analysis with Application <br/>to Face Detection and Recognition <br/>International Doctoral Innovation Centre <br/><b>University of Nottingham Ningbo China</b><br/>School of Computer Science @@ -696,6 +891,12 @@ </td><td>('3247966', 'Jianlong Fu', 'jianlong fu')<br/>('1783122', 'Jinqiao Wang', 'jinqiao wang')<br/>('3349534', 'Xin-Jing Wang', 'xin-jing wang')<br/>('3663422', 'Yong Rui', 'yong rui')<br/>('1694235', 'Hanqing Lu', 'hanqing lu')</td><td>1fjlfu, jqwang, luhqg@nlpr.ia.ac.cn, 2fxjwang, yongruig@microsoft.com </td></tr><tr><td>66330846a03dcc10f36b6db9adf3b4d32e7a3127</td><td>Polylingual Multimodal Learning <br/><b>Institute AIFB, Karlsruhe Institute of Technology, Germany</b></td><td>('3219864', 'Aditya Mogadala', 'aditya mogadala')</td><td>{aditya.mogadala}@kit.edu +</td></tr><tr><td>66d087f3dd2e19ffe340c26ef17efe0062a59290</td><td>Dog Breed Identification +<br/>Brian Mittl +<br/>Vijay Singh +</td><td></td><td>wlarow@stanford.edu +<br/>bmittl@stanford.edu +<br/>vpsingh@stanford.edu </td></tr><tr><td>6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c</td><td>Ordinal Regression with Multiple Output CNN for Age Estimation <br/><b>Xidian University 2Xi an Jiaotong University 3Microsoft Research Asia</b></td><td>('1786361', 'Zhenxing Niu', 'zhenxing niu')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('10699750', 'Xinbo Gao', 'xinbo gao')<br/>('36497527', 'Mo Zhou', 'mo zhou')<br/>('40367806', 'Le Wang', 'le wang')</td><td>{zhenxingniu,cdluminate}@gmail.com, lewang@mail.xjtu.edu.cn, xinbogao@mail.xidian.edu.cn <br/>ganghua@gmail.com @@ -720,7 +921,7 @@ <br/>for Exploring the Face Space <br/>Escuela Superior Politecnica del Litoral (ESPOL) <br/>Guayaquil-Ecuador -</td><td>('3123974', 'Andres G. Abad', 'andres g. abad')<br/>('3044670', 'Luis I. Reyes Castro', 'luis i. reyes castro')</td><td></td></tr><tr><td>66886997988358847615375ba7d6e9eb0f1bb27f</td><td></td><td></td><td></td></tr><tr><td>66a9935e958a779a3a2267c85ecb69fbbb75b8dc</td><td>FAST AND ROBUST FIXED-RANK MATRIX RECOVERY +</td><td>('3123974', 'Andres G. Abad', 'andres g. abad')<br/>('3044670', 'Luis I. Reyes Castro', 'luis i. reyes castro')</td><td></td></tr><tr><td>66886997988358847615375ba7d6e9eb0f1bb27f</td><td></td><td></td><td></td></tr><tr><td>66837add89caffd9c91430820f49adb5d3f40930</td><td></td><td></td><td></td></tr><tr><td>66a9935e958a779a3a2267c85ecb69fbbb75b8dc</td><td>FAST AND ROBUST FIXED-RANK MATRIX RECOVERY <br/>Fast and Robust Fixed-Rank Matrix <br/>Recovery <br/>Antonio Lopez @@ -911,6 +1112,11 @@ <br/>Recognition Systems by Segmenting Face Region <br/><b>St. Xavier s Catholic College of Engineering, Nagercoil, India</b><br/><b>Manonmaniam Sundaranar University, Tirunelveli, India</b></td><td>('9375880', 'R. Reena Rose', 'r. reena rose')<br/>('3311251', 'A. Suruliandi', 'a. suruliandi')</td><td>mailtoreenarose@yahoo.in <br/>suruliandi@yahoo.com +</td></tr><tr><td>3e0a1884448bfd7f416c6a45dfcdfc9f2e617268</td><td>Understanding and Controlling User Linkability in +<br/>Decentralized Learning +<br/><b>Max Planck Institute for Informatics</b><br/>Saarland Informatics Campus +<br/>Saarbrücken, Germany +</td><td>('9517443', 'Tribhuvanesh Orekondy', 'tribhuvanesh orekondy')<br/>('2390510', 'Seong Joon Oh', 'seong joon oh')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td>{orekondy,joon,schiele,mfritz}@mpi-inf.mpg.de </td></tr><tr><td>3e4b38b0574e740dcbd8f8c5dfe05dbfb2a92c07</td><td>FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS <br/>AND LINEAR PROGRAMMING <br/>Xiaoyi Feng1, 2, Matti Pietikäinen1, Abdenour Hadid1 @@ -999,7 +1205,9 @@ </td></tr><tr><td>3ee7a8107a805370b296a53e355d111118e96b7c</td><td></td><td></td><td></td></tr><tr><td>3ebce6710135d1f9b652815e59323858a7c60025</td><td>Component-based Face Detection <br/>(cid:1)Center for Biological and Computational Learning, M.I.T., Cambridge, MA, USA <br/><b>cid:2)Honda RandD Americas, Inc., Boston, MA, USA</b><br/><b>University of Siena, Siena, Italy</b></td><td>('1684626', 'Bernd Heisele', 'bernd heisele')</td><td>(cid:1)heisele, serre, tp(cid:2) @ai.mit.edu pontil@dii.unisi.it -</td></tr><tr><td>3e3f305dac4fbb813e60ac778d6929012b4b745a</td><td>Feature sampling and partitioning for visual vocabulary +</td></tr><tr><td>3e4acf3f2d112fc6516abcdddbe9e17d839f5d9b</td><td>Deep Value Networks Learn to +<br/>Evaluate and Iteratively Refine Structured Outputs +</td><td>('3037160', 'Michael Gygli', 'michael gygli')</td><td></td></tr><tr><td>3e3f305dac4fbb813e60ac778d6929012b4b745a</td><td>Feature sampling and partitioning for visual vocabulary <br/>generation on large action classification datasets. <br/><b>Oxford Brookes University</b><br/><b>University of Oxford</b></td><td>('3019396', 'Michael Sapienza', 'michael sapienza')<br/>('1754181', 'Fabio Cuzzolin', 'fabio cuzzolin')</td><td></td></tr><tr><td>3ea8a6dc79d79319f7ad90d663558c664cf298d4</td><td></td><td>('40253814', 'IRA COHEN', 'ira cohen')</td><td></td></tr><tr><td>3e4f84ce00027723bdfdb21156c9003168bc1c80</td><td>1979 <br/>© EURASIP, 2011 - ISSN 2076-1465 @@ -1046,7 +1254,12 @@ <br/>FOR FACE RECOGNITION BASED ON SPARSE REPRESENTATION <br/><b>Tokyo Metropolitan University</b><br/>6–6 Asahigaoka, Hino-shi, Tokyo 191–0065, Japan <br/>† NTT Network Innovation Laboratories, Japan -</td><td>('32403098', 'Yuichi Muraki', 'yuichi muraki')<br/>('11129971', 'Masakazu Furukawa', 'masakazu furukawa')<br/>('1728060', 'Masaaki Fujiyoshi', 'masaaki fujiyoshi')<br/>('34638424', 'Yoshihide Tonomura', 'yoshihide tonomura')<br/>('1737217', 'Hitoshi Kiya', 'hitoshi kiya')</td><td></td></tr><tr><td>3e687d5ace90c407186602de1a7727167461194a</td><td>Photo Tagging by Collection-Aware People Recognition +</td><td>('32403098', 'Yuichi Muraki', 'yuichi muraki')<br/>('11129971', 'Masakazu Furukawa', 'masakazu furukawa')<br/>('1728060', 'Masaaki Fujiyoshi', 'masaaki fujiyoshi')<br/>('34638424', 'Yoshihide Tonomura', 'yoshihide tonomura')<br/>('1737217', 'Hitoshi Kiya', 'hitoshi kiya')</td><td></td></tr><tr><td>3e40991ab1daa2a4906eb85a5d6a01a958b6e674</td><td>LIPNET: END-TO-END SENTENCE-LEVEL LIPREADING +<br/><b>University of Oxford, Oxford, UK</b><br/>Google DeepMind, London, UK 2 +<br/>CIFAR, Canada 3 +<br/>{yannis.assael,brendan.shillingford, +</td><td>('3365565', 'Yannis M. Assael', 'yannis m. assael')<br/>('3144580', 'Brendan Shillingford', 'brendan shillingford')<br/>('1766767', 'Shimon Whiteson', 'shimon whiteson')</td><td>shimon.whiteson,nando.de.freitas}@cs.ox.ac.uk +</td></tr><tr><td>3e687d5ace90c407186602de1a7727167461194a</td><td>Photo Tagging by Collection-Aware People Recognition <br/>UFF <br/>UFF <br/>Asla S´a @@ -1115,7 +1328,17 @@ <br/>Email: guyon@chalearn.org </td></tr><tr><td>501eda2d04b1db717b7834800d74dacb7df58f91</td><td></td><td>('3846862', 'Pedro Miguel Neves Marques', 'pedro miguel neves marques')</td><td></td></tr><tr><td>5083c6be0f8c85815ead5368882b584e4dfab4d1</td><td> Please do not quote. In press, Handbook of affective computing. New York, NY: Oxford <br/>Automated Face Analysis for Affective Computing -</td><td>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>500b92578e4deff98ce20e6017124e6d2053b451</td><td></td><td></td><td></td></tr><tr><td>5058a7ec68c32984c33f357ebaee96c59e269425</td><td>A Comparative Evaluation of Regression Learning +</td><td>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>506c2fbfa9d16037d50d650547ad3366bb1e1cde</td><td>Convolutional Channel Features: Tailoring CNN to Diverse Tasks +<br/>Junjie Yan +<br/>Zhen Lei +<br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition +<br/><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>('1716231', 'Bin Yang', 'bin yang')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{zlei, szli}@nlpr.ia.ac.cn +<br/>{yb.derek, yanjjie}@gmail.com +</td></tr><tr><td>500b92578e4deff98ce20e6017124e6d2053b451</td><td></td><td></td><td></td></tr><tr><td>504028218290d68859f45ec686f435f473aa326c</td><td>Multi-Fiber Networks for Video Recognition +<br/><b>National University of Singapore</b><br/>2 Facebook Research +<br/><b>Qihoo 360 AI Institute</b></td><td>('1713312', 'Yunpeng Chen', 'yunpeng chen')<br/>('1944225', 'Yannis Kalantidis', 'yannis kalantidis')<br/>('2757639', 'Jianshu Li', 'jianshu li')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')</td><td>{chenyunpeng, jianshu}@u.nus.edu, yannisk@fb.com, +<br/>{eleyans, elefjia}@nus.edu.sg +</td></tr><tr><td>5058a7ec68c32984c33f357ebaee96c59e269425</td><td>A Comparative Evaluation of Regression Learning <br/>Algorithms for Facial Age Estimation <br/>1 Herta Security <br/>Pau Claris 165 4-B, 08037 Barcelona, Spain @@ -1150,7 +1373,18 @@ </td></tr><tr><td>5050807e90a925120cbc3a9cd13431b98965f4b9</td><td>To appear in the ECCV Workshop on Parts and Attributes, Oct. 2012. <br/>Unsupervised Learning of Discriminative <br/>Relative Visual Attributes -<br/><b>Boston University</b><br/><b>Hacettepe University</b></td><td>('2863531', 'Shugao Ma', 'shugao ma')<br/>('2011587', 'Nazli Ikizler-Cinbis', 'nazli ikizler-cinbis')</td><td></td></tr><tr><td>50eb2ee977f0f53ab4b39edc4be6b760a2b05f96</td><td>Australian Journal of Basic and Applied Sciences, 11(5) April 2017, Pages: 1-11 +<br/><b>Boston University</b><br/><b>Hacettepe University</b></td><td>('2863531', 'Shugao Ma', 'shugao ma')<br/>('2011587', 'Nazli Ikizler-Cinbis', 'nazli ikizler-cinbis')</td><td></td></tr><tr><td>50a0930cb8cc353e15a5cb4d2f41b365675b5ebf</td><td></td><td></td><td></td></tr><tr><td>508702ed2bf7d1b0655ea7857dd8e52d6537e765</td><td>ZUO, ORGANISCIAK, SHUM, YANG: SST-VLAD AND SST-FV FOR VAR +<br/>Saliency-Informed Spatio-Temporal Vector +<br/>of Locally Aggregated Descriptors and +<br/>Fisher Vectors for Visual Action Recognition +<br/>Department of Computer and +<br/>Information Sciences +<br/><b>Northumbria University</b><br/>Newcastle upon Tyne, NE1 8ST, UK +</td><td>('40760781', 'Zheming Zuo', 'zheming zuo')<br/>('34975328', 'Daniel Organisciak', 'daniel organisciak')<br/>('2840036', 'Hubert P. H. Shum', 'hubert p. h. shum')<br/>('1706028', 'Longzhi Yang', 'longzhi yang')</td><td>zheming.zuo@northumbria.ac.uk +<br/>daniel.organisciak@northumbria.ac.uk +<br/>hubert.shum@northumbria.ac.uk +<br/>longzhi.yang@northumbria.ac.uk +</td></tr><tr><td>50eb2ee977f0f53ab4b39edc4be6b760a2b05f96</td><td>Australian Journal of Basic and Applied Sciences, 11(5) April 2017, Pages: 1-11 <br/>AUSTRALIAN JOURNAL OF BASIC AND <br/>APPLIED SCIENCES <br/>ISSN:1991-8178 EISSN: 2309-8414 @@ -1392,12 +1626,14 @@ </td><td>('34964075', 'Satyanarayana Murty', 'satyanarayana murty')</td><td>India, 1gsn_73@yahoo.co.in <br/>2drvvk144@gmail.com <br/>3obulesh.a@gmail.com -</td></tr><tr><td>68a3f12382003bc714c51c85fb6d0557dcb15467</td><td></td><td></td><td></td></tr><tr><td>6859b891a079a30ef16f01ba8b85dc45bd22c352</td><td>International Journal of Emerging Technology and Advanced Engineering +</td></tr><tr><td>68d2afd8c5c1c3a9bbda3dd209184e368e4376b9</td><td>Representation Learning by Rotating Your Faces +</td><td>('1849929', 'Luan Tran', 'luan tran')<br/>('2399004', 'Xi Yin', 'xi yin')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td></td></tr><tr><td>68a3f12382003bc714c51c85fb6d0557dcb15467</td><td></td><td></td><td></td></tr><tr><td>6859b891a079a30ef16f01ba8b85dc45bd22c352</td><td>International Journal of Emerging Technology and Advanced Engineering <br/>Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 10, October 2014) <br/>2D Face Recognition Based on PCA & Comparison of <br/>Manhattan Distance, Euclidean Distance & Chebychev <br/>Distance -<br/><b>RCC Institute of Information Technology, Kolkata, India</b></td><td>('2467416', 'Rajib Saha', 'rajib saha')<br/>('2144187', 'Sayan Barman', 'sayan barman')</td><td></td></tr><tr><td>68003e92a41d12647806d477dd7d20e4dcde1354</td><td>ISSN: 0976-9102 (ONLINE) +<br/><b>RCC Institute of Information Technology, Kolkata, India</b></td><td>('2467416', 'Rajib Saha', 'rajib saha')<br/>('2144187', 'Sayan Barman', 'sayan barman')</td><td></td></tr><tr><td>68d08ed9470d973a54ef7806318d8894d87ba610</td><td>Drive Video Analysis for the Detection of Traffic Near-Miss Incidents +</td><td>('1730200', 'Hirokatsu Kataoka', 'hirokatsu kataoka')<br/>('5014206', 'Teppei Suzuki', 'teppei suzuki')<br/>('6881850', 'Shoko Oikawa', 'shoko oikawa')<br/>('1720770', 'Yasuhiro Matsui', 'yasuhiro matsui')<br/>('1732705', 'Yutaka Satoh', 'yutaka satoh')</td><td></td></tr><tr><td>68caf5d8ef325d7ea669f3fb76eac58e0170fff0</td><td></td><td></td><td></td></tr><tr><td>68003e92a41d12647806d477dd7d20e4dcde1354</td><td>ISSN: 0976-9102 (ONLINE) <br/>DOI: 10.21917/ijivp.2013.0101 <br/> ICTACT JOURNAL ON IMAGE AND VIDEO PROCESSING, NOVEMBER 2013, VOLUME: 04, ISSUE: 02 <br/>FUZZY BASED IMAGE DIMENSIONALITY REDUCTION USING SHAPE @@ -1416,7 +1652,10 @@ <br/>3 ITESM, Campus Saltillo, Saltillo 25270, Coahuila, M´exico <br/>Veracruz, M´exico </td><td></td><td>mario.castelan@cinvestav.edu.mx -</td></tr><tr><td>68c5238994e3f654adea0ccd8bca29f2a24087fc</td><td>PLSA-BASED ZERO-SHOT LEARNING +</td></tr><tr><td>684f5166d8147b59d9e0938d627beff8c9d208dd</td><td>IEEE TRANS. NNLS, JUNE 2017 +<br/>Discriminative Block-Diagonal Representation +<br/>Learning for Image Recognition +</td><td>('38448016', 'Zheng Zhang', 'zheng zhang')<br/>('40065614', 'Yong Xu', 'yong xu')<br/>('40799321', 'Ling Shao', 'ling shao')<br/>('49500178', 'Jian Yang', 'jian yang')</td><td></td></tr><tr><td>68c5238994e3f654adea0ccd8bca29f2a24087fc</td><td>PLSA-BASED ZERO-SHOT LEARNING <br/>Centre of Image and Signal Processing <br/>Faculty of Computer Science & Information Technology <br/><b>University of Malaya, 50603 Kuala Lumpur, Malaysia</b></td><td>('2800072', 'Wai Lam Hoo', 'wai lam hoo')<br/>('2863960', 'Chee Seng Chan', 'chee seng chan')</td><td>{wailam88@siswa.um.edu.my; cs.chan@um.edu.my} @@ -1428,7 +1667,10 @@ <br/><b>Link ping University</b><br/>Face Recognition with <br/>Preprocessing and Neural <br/>Networks -</td><td></td><td></td></tr><tr><td>687e17db5043661f8921fb86f215e9ca2264d4d2</td><td>A Robust Elastic and Partial Matching Metric for Face Recognition +</td><td></td><td></td></tr><tr><td>68484ae8a042904a95a8d284a7f85a4e28e37513</td><td>Spoofing Deep Face Recognition with Custom Silicone Masks +<br/>S´ebastien Marcel +<br/><b>Idiap Research Institute. Centre du Parc, Rue Marconi 19, Martigny (VS), Switzerland</b></td><td>('1952348', 'Sushil Bhattacharjee', 'sushil bhattacharjee')</td><td>{sushil.bhattacharjee; amir.mohammadi; sebastien.marcel}@idiap.ch +</td></tr><tr><td>687e17db5043661f8921fb86f215e9ca2264d4d2</td><td>A Robust Elastic and Partial Matching Metric for Face Recognition <br/>Microsoft Corporate <br/>One Microsoft Way, Redmond, WA 98052 </td><td>('1745420', 'Gang Hua', 'gang hua')<br/>('33474090', 'Amir Akbarzadeh', 'amir akbarzadeh')</td><td>{ganghua, amir}@microsoft.com @@ -1553,7 +1795,38 @@ <br/><b>Florida International University</b><br/>Miami, FL 33199, USA </td><td>('1685202', 'Lin Lin', 'lin lin')<br/>('1693826', 'Mei-Ling Shyu', 'mei-ling shyu')<br/>('1705664', 'Shu-Ching Chen', 'shu-ching chen')</td><td>Email: l.lin2@umiami.edu, shyu@miami.edu <br/>Email: chens@cs.fiu.edu -</td></tr><tr><td>683ec608442617d11200cfbcd816e86ce9ec0899</td><td>Dual Linear Regression Based Classification for Face Cluster Recognition +</td></tr><tr><td>682760f2f767fb47e1e2ca35db3becbb6153756f</td><td>The Effect of Pets on Happiness: A Large-scale Multi-Factor +<br/>Analysis using Social Multimedia +<br/>From reducing stress and loneliness, to boosting productivity and overall well-being, pets are believed to play +<br/>a significant role in people’s daily lives. Many traditional studies have identified that frequent interactions +<br/>with pets could make individuals become healthier and more optimistic, and ultimately enjoy a happier life. +<br/>However, most of those studies are not only restricted in scale, but also may carry biases by using subjective +<br/>self-reports, interviews, and questionnaires as the major approaches. In this paper, we leverage large-scale +<br/>data collected from social media and the state-of-the-art deep learning technologies to study this phenomenon +<br/>in depth and breadth. Our study includes four major steps: 1) collecting timeline posts from around 20,000 +<br/>Instagram users; 2) using face detection and recognition on 2-million photos to infer users’ demographics, +<br/>relationship status, and whether having children, 3) analyzing a user’s degree of happiness based on images +<br/>and captions via smiling classification and textual sentiment analysis; 3) applying transfer learning techniques +<br/>to retrain the final layer of the Inception v3 model for pet classification; and 4) analyzing the effects of pets +<br/>on happiness in terms of multiple factors of user demographics. Our main results have demonstrated the +<br/>efficacy of our proposed method with many new insights. We believe this method is also applicable to other +<br/>domains as a scalable, efficient, and effective methodology for modeling and analyzing social behaviors and +<br/>psychological well-being. In addition, to facilitate the research involving human faces, we also release our +<br/>dataset of 700K analyzed faces. +<br/>CCS Concepts: • Human-centered computing → Social media; +<br/>Additional Key Words and Phrases: Happiness analysis, happiness, user demographics, pet and happiness, +<br/>social multimedia, social media. +<br/>ACM Reference format: +<br/>Analysis using Social Multimedia. ACM Trans. Intell. Syst. Technol. 9, 4, Article 39 (June 2017), 15 pages. +<br/>https://doi.org/0000001.0000001 +<br/>1 INTRODUCTION +<br/>Happiness has always been a subjective and multidimensional matter; its definition varies individu- +<br/>ally, and the factors impacting our feeling of happiness are diverse. A study in [21] has constructed +<br/><b>We thank the support of New York State through the Goergen Institute for Data Science, our corporate research sponsors</b><br/>Xerox and VisualDX, and NSF Award #1704309. +<br/><b>Author s addresses: X. Peng, University of Rochester; L. Chi</b><br/><b>University of Rochester and J. Luo, University of Rochester</b><br/>Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee +<br/>provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the +<br/>full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. +</td><td>('1901094', 'Xuefeng Peng', 'xuefeng peng')<br/>('35678395', 'Li-Kai Chi', 'li-kai chi')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')<br/>('1901094', 'Xuefeng Peng', 'xuefeng peng')<br/>('35678395', 'Li-Kai Chi', 'li-kai chi')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')</td><td></td></tr><tr><td>683ec608442617d11200cfbcd816e86ce9ec0899</td><td>Dual Linear Regression Based Classification for Face Cluster Recognition <br/><b>University of Northern British Columbia</b><br/>Prince George, BC, Canada V2N 4Z9 </td><td>('1692551', 'Liang Chen', 'liang chen')</td><td>chen.liang.97@gmail.com </td></tr><tr><td>68c17aa1ecbff0787709be74d1d98d9efd78f410</td><td>International Journal of Optomechatronics, 6: 92–119, 2012 @@ -1595,6 +1868,74 @@ <br/>ing.uchile.cl <br/>92 </td><td>('32271973', 'Claudio Perez', 'claudio perez')<br/>('40333310', 'Juan Tapia', 'juan tapia')<br/>('32723983', 'Claudio Held', 'claudio held')<br/>('32271973', 'Claudio Perez', 'claudio perez')<br/>('32271973', 'Claudio Perez', 'claudio perez')</td><td>Engineering, Universidad de Chile Casilla 412-3, Av. Tupper 2007, Santiago, Chile. E-mail: clperez@ +</td></tr><tr><td>68f61154a0080c4aae9322110c8827978f01ac2e</td><td>Research Article +<br/>Journal of the Optical Society of America A +<br/>Recognizing blurred, non-frontal, illumination and +<br/>expression variant partially occluded faces +<br/><b>Indian Institute of Technology Madras, Chennai 600036, India</b><br/>Compiled June 26, 2016 +<br/>The focus of this paper is on the problem of recognizing faces across space-varying motion blur, changes +<br/>in pose, illumination, and expression, as well as partial occlusion, when only a single image per subject +<br/>is available in the gallery. We show how the blur incurred due to relative motion between the camera and +<br/>the subject during exposure can be estimated from the alpha matte of pixels that straddle the boundary +<br/>between the face and the background. We also devise a strategy to automatically generate the trimap re- +<br/>quired for matte estimation. Having computed the motion via the matte of the probe, we account for pose +<br/>variations by synthesizing from the intensity image of the frontal gallery, a face image that matches the +<br/>pose of the probe. To handle illumination and expression variations, and partial occlusion, we model the +<br/>probe as a linear combination of nine blurred illumination basis images in the synthesized non-frontal +<br/>pose, plus a sparse occlusion. We also advocate a recognition metric that capitalizes on the sparsity of the +<br/>occluded pixels. The performance of our method is extensively validated on synthetic as well as real face +<br/>data. © 2016 Optical Society of America +<br/>OCIS codes: +<br/>(150.0150) Machine vision. +<br/>http://dx.doi.org/10.1364/ao.XX.XXXXXX +<br/>(100.0100) Image processing; (100.5010) Pattern recognition; (100.3008) Image recognition, algorithms and filters; +<br/>1. INTRODUCTION +<br/>State-of-the-art face recognition (FR) systems can outperform +<br/>even humans when presented with images captured under con- +<br/>trolled environments. However, their performance drops quite +<br/>rapidly in unconstrained settings due to image degradations +<br/>arising from blur, variations in pose, illumination, and expres- +<br/>sion, partial occlusion etc. Motion blur is commonplace today +<br/>owing to the exponential rise in the use and popularity of light- +<br/>weight and cheap hand-held imaging devices, and the ubiquity +<br/>of mobile phones equipped with cameras. Photographs cap- +<br/>tured using a hand-held device usually contain blur when the +<br/>illumination is poor because larger exposure times are needed +<br/>to compensate for the lack of light, and this increases the possi- +<br/>bility of camera shake. On the other hand, reducing the shutter +<br/>speed results in noisy images while tripods inevitably restrict +<br/>mobility. Even for a well-lit scene, the face might be blurred if +<br/>the subject is in motion. The problem is further compounded +<br/>in the case of poorly-lit dynamic scenes since the blur observed +<br/>on the face is due to the combined effects of the blur induced +<br/>by the motion of the camera and the independent motion of +<br/>the subject. In addition to blur and illumination, practical face +<br/>recognition algorithms must also possess the ability to recognize +<br/>faces across reasonable variations in pose. Partial occlusion and +<br/>facial expression changes, common in real-world applications, +<br/>escalate the challenges further. Yet another factor that governs +<br/>the performance of face recognition algorithms is the number +<br/>of images per subject available for training. In many practical +<br/>application scenarios such as law enforcement, driver license or +<br/>passport identification, where there is usually only one training +<br/>sample per subject in the database, techniques that rely on the +<br/>size and representation of the training set suffer a serious perfor- +<br/>mance drop or even fail to work. Face recognition algorithms +<br/>can broadly be classified into either discriminative or genera- +<br/>tive approaches. While the availability of large labeled datasets +<br/>and greater computing power has boosted the performance of +<br/>discriminative methods [1, 2] recently, generative approaches +<br/>continue to remain very popular [3, 4], and there is concurrent +<br/>research in both directions. The model we present in this paper +<br/>falls into the latter category. In fact, generative models are even +<br/>useful for producing training samples for learning algorithms. +<br/>Literature on face recognition from blurred images can be +<br/>broadly classified into four categories. It is important to note +<br/>that all of them (except our own earlier work in [4]) are restricted +<br/>to the convolution model for uniform blur. In the first approach +<br/>[5, 6], the blurred probe image is first deblurred using standard +<br/>deconvolution algorithms before performing recognition. How- +</td><td></td><td>*Corresponding author: jithuthatswho@gmail.com </td></tr><tr><td>6821113166b030d2123c3cd793dd63d2c909a110</td><td>STUDIA INFORMATICA <br/>Volume 36 <br/>2015 @@ -2018,7 +2359,17 @@ <br/>[15 of 21] N. Pinto, J. J. DiCarlo, and D. D. Cox. How far can you get with a modern face recognition test set using only simple features? In IEEE CVPR, 2009. <br/>[18 of 21] T. Sim, S. Baker, and M. Bsat. The CMU Pose, Illumination and Expression (PIE) Database. In Proceedings of the IEEE F&G, May 2002. </td><td>('31552290', 'Brian C. Parks', 'brian c. parks')<br/>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')</td><td>{viyer,skirkbride,bparks,wscheirer,tboult}@vast.uccs.edu -</td></tr><tr><td>5721216f2163d026e90d7cd9942aeb4bebc92334</td><td></td><td></td><td></td></tr><tr><td>575141e42740564f64d9be8ab88d495192f5b3bc</td><td>Age Estimation based on Multi-Region +</td></tr><tr><td>574b62c845809fd54cc168492424c5fac145bc83</td><td>Learning Warped Guidance for Blind Face +<br/>Restoration +<br/><b>School of Computer Science and Technology, Harbin Institute of Technology, China</b><br/><b>School of Data and Computer Science, Sun Yat-sen University, China</b><br/><b>University of Kentucky, USA</b></td><td>('21515518', 'Xiaoming Li', 'xiaoming li')<br/>('40508248', 'Yuting Ye', 'yuting ye')<br/>('1724520', 'Wangmeng Zuo', 'wangmeng zuo')<br/>('1737218', 'Liang Lin', 'liang lin')<br/>('38958903', 'Ruigang Yang', 'ruigang yang')</td><td>csxmli@hit.edu.cn, csmliu@outlook.com, yeyuting.jlu@gmail.com, +<br/>wmzuo@hit.edu.cn +<br/>linliang@ieee.org +<br/>ryang@cs.uky.edu +</td></tr><tr><td>57246142814d7010d3592e3a39a1ed819dd01f3b</td><td><b>MITSUBISHI ELECTRIC RESEARCH LABORATORIES</b><br/>http://www.merl.com +<br/>Verification of Very Low-Resolution Faces Using An +<br/>Identity-Preserving Deep Face Super-resolution Network +<br/>TR2018-116 August 24, 2018 +</td><td></td><td></td></tr><tr><td>5721216f2163d026e90d7cd9942aeb4bebc92334</td><td></td><td></td><td></td></tr><tr><td>575141e42740564f64d9be8ab88d495192f5b3bc</td><td>Age Estimation based on Multi-Region <br/>Convolutional Neural Network <br/>1Center for Biometrics and Security Research & National Laboratory of Pattern <br/><b>Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b><br/><b>University of Chinese Academy of Sciences</b></td><td>('40282288', 'Ting Liu', 'ting liu')<br/>('1756538', 'Jun Wan', 'jun wan')<br/>('39974958', 'Tingzhao Yu', 'tingzhao yu')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{ting.liu,jun.wan,zlei,szli}@nlpr.ia.ac.cn,yutingzhao2013@ia.ac.cn @@ -2033,7 +2384,35 @@ <br/>A Novel Approach for Face Recognition <br/>Using PCA and Artificial Neural Network <br/><b>Dayananda Sagar College of Engg., India</b><br/><b>Dayananda Sagar College of Engg., India</b></td><td>('9856026', 'Karthik G', 'karthik g')<br/>('9856026', 'Karthik G', 'karthik g')</td><td>1 email : karthik.knocks@gmail.com; 2 email : hcsateesh@gmail.com -</td></tr><tr><td>5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725</td><td></td><td></td><td></td></tr><tr><td>57b052cf826b24739cd7749b632f85f4b7bcf90b</td><td>Fast Fashion Guided Clothing Image Retrieval: +</td></tr><tr><td>5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725</td><td></td><td></td><td></td></tr><tr><td>571b83f7fc01163383e6ca6a9791aea79cafa7dd</td><td>SeqFace: Make full use of sequence information for face recognition +<br/><b>College of Information Science and Technology</b><br/><b>Beijing University of Chemical Technology, China</b><br/>YUNSHITU Corp., China +</td><td>('48594708', 'Wei Hu', 'wei hu')<br/>('7524887', 'Yangyu Huang', 'yangyu huang')<br/>('8451319', 'Guodong Yuan', 'guodong yuan')<br/>('47191084', 'Fan Zhang', 'fan zhang')<br/>('50391855', 'Ruirui Li', 'ruirui li')<br/>('47113208', 'Wei Li', 'wei li')</td><td></td></tr><tr><td>574ad7ef015995efb7338829a021776bf9daaa08</td><td>AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks +<br/>for Human Action Recognition in Videos +<br/>1IIT Kanpur‡ +<br/>2SRI International +<br/>3UCSD +</td><td>('24899770', 'Amlan Kar', 'amlan kar')<br/>('12692625', 'Nishant Rai', 'nishant rai')<br/>('39707211', 'Karan Sikka', 'karan sikka')<br/>('39396475', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>57a14a65e8ae15176c9afae874854e8b0f23dca7</td><td>UvA-DARE (Digital Academic Repository) +<br/>Seeing mixed emotions: The specificity of emotion perception from static and dynamic +<br/>facial expressions across cultures +<br/>Fang, X.; Sauter, D.A.; van Kleef, G.A. +<br/>Published in: +<br/>Journal of Cross-Cultural Psychology +<br/>DOI: +<br/>10.1177/0022022117736270 +<br/>Link to publication +<br/>Citation for published version (APA): +<br/>Fang, X., Sauter, D. A., & van Kleef, G. A. (2018). Seeing mixed emotions: The specificity of emotion perception +<br/>from static and dynamic facial expressions across cultures. Journal of Cross-Cultural Psychology, 49(1), 130- +<br/>148. DOI: 10.1177/0022022117736270 +<br/>General rights +<br/>It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +<br/>other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +<br/>Disclaimer/Complaints regulations +<br/>If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +<br/>your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +<br/><b>the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam</b><br/>The Netherlands. You will be contacted as soon as possible. +<br/>Download date: 08 Aug 2018 +<br/><b>UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl</b></td><td></td><td></td></tr><tr><td>57b052cf826b24739cd7749b632f85f4b7bcf90b</td><td>Fast Fashion Guided Clothing Image Retrieval: <br/>Delving Deeper into What Feature Makes <br/>Fashion <br/><b>School of Data and Computer Science, Sun Yat-sen University</b><br/>Guangzhou, P.R China @@ -2060,6 +2439,11 @@ <br/>Center for Automation Research, UMIACS* <br/>Department of Electrical and Computer Engineering† <br/><b>University of Maryland, College Park</b></td><td>('2747758', 'Maya Kabkab', 'maya kabkab')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>Email: {mayak, emhand, rama}@umiacs.umd.edu +</td></tr><tr><td>3b73f8a2b39751efb7d7b396bf825af2aaadee24</td><td>Connecting Pixels to Privacy and Utility: +<br/>Automatic Redaction of Private Information in Images +<br/><b>Max Planck Institute for Informatics</b><br/>Saarland Informatics Campus +<br/>Saabr¨ucken, Germany +</td><td>('9517443', 'Tribhuvanesh Orekondy', 'tribhuvanesh orekondy')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td>{orekondy,mfritz,schiele}@mpi-inf.mpg.de </td></tr><tr><td>3b2d5585af59480531616fe970cb265bbdf63f5b</td><td>Robust Face Recognition under Varying Light <br/>Based on 3D Recovery <br/>Center of Computer Vision, School of @@ -2293,7 +2677,9 @@ <br/><b>Queen Mary University of London</b></td><td>('1735328', 'Xun Xu', 'xun xu')<br/>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')</td><td>{xun.xu,t.hospedales,s.gong}@qmul.ac.uk </td></tr><tr><td>3b9c08381282e65649cd87dfae6a01fe6abea79b</td><td>CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016 <br/><b>Multimedia Laboratory, The Chinese University of Hong Kong, Hong Kong</b><br/>2Computer Vision Lab, ETH Zurich, Switzerland -<br/><b>Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('1915826', 'Zhe Wang', 'zhe wang')<br/>('3047890', 'Bowen Zhang', 'bowen zhang')<br/>('2313919', 'Hang Song', 'hang song')<br/>('1688012', 'Wei Li', 'wei li')<br/>('1807606', 'Dahua Lin', 'dahua lin')<br/>('1681236', 'Luc Van Gool', 'luc van gool')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>3b4fd2aec3e721742f11d1ed4fa3f0a86d988a10</td><td>Glimpse: Continuous, Real-Time Object Recognition on +<br/><b>Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('1915826', 'Zhe Wang', 'zhe wang')<br/>('3047890', 'Bowen Zhang', 'bowen zhang')<br/>('2313919', 'Hang Song', 'hang song')<br/>('1688012', 'Wei Li', 'wei li')<br/>('1807606', 'Dahua Lin', 'dahua lin')<br/>('1681236', 'Luc Van Gool', 'luc van gool')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>3b84d074b8622fac125f85ab55b63e876fed4628</td><td>End-to-End Localization and Ranking for +<br/>Relative Attributes +<br/><b>University of California, Davis</b></td><td>('19553871', 'Krishna Kumar Singh', 'krishna kumar singh')<br/>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td></td></tr><tr><td>3b4fd2aec3e721742f11d1ed4fa3f0a86d988a10</td><td>Glimpse: Continuous, Real-Time Object Recognition on <br/>Mobile Devices <br/>MIT CSAIL <br/>Microsoft Research @@ -2305,7 +2691,11 @@ <br/>shuodeng@csail.mit.edu <br/>bahl@microsoft.com <br/>hari@csail.mit.edu -</td></tr><tr><td>3bc376f29bc169279105d33f59642568de36f17f</td><td>Active Shape Models with SIFT Descriptors and MARS +</td></tr><tr><td>3be8f1f7501978287af8d7ebfac5963216698249</td><td>Deep Cascaded Regression for Face Alignment +<br/><b>School of Data and Computer Science, Sun Yat-Sen University, China</b><br/><b>National University of Singapore, Singapore</b><br/>algorithm refines the shape by estimating a shape increment +<br/>∆S. In particular, a shape increment at stage k is calculated +<br/>as: +</td><td>('3124720', 'Shengtao Xiao', 'shengtao xiao')<br/>('10338111', 'Zhen Cui', 'zhen cui')<br/>('48815683', 'Yan Pan', 'yan pan')<br/>('48258938', 'Chunyan Xu', 'chunyan xu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>3bc376f29bc169279105d33f59642568de36f17f</td><td>Active Shape Models with SIFT Descriptors and MARS <br/><b>University of Cape Town, South Africa</b><br/>Keywords: <br/>Facial Landmark, Active Shape Model, Multivariate Adaptive Regression Splines </td><td>('2822258', 'Stephen Milborrow', 'stephen milborrow')<br/>('2537623', 'Fred Nicolls', 'fred nicolls')</td><td>milbo@sonic.net @@ -2332,7 +2722,10 @@ <br/>Date of Defense: 23rd of September, 2010 <br/>Darmstadt, 2010 <br/>D17 -</td><td>('37718254', 'Michael Stark', 'michael stark')</td><td></td></tr><tr><td>3b9b200e76a35178da940279d566bbb7dfebb787</td><td>Learning Channel Inter-dependencies at Multiple Scales on Dense +</td><td>('37718254', 'Michael Stark', 'michael stark')</td><td></td></tr><tr><td>3baa3d5325f00c7edc1f1427fcd5bdc6a420a63f</td><td>Enhancing Convolutional Neural Networks for Face Recognition with +<br/>Occlusion Maps and Batch Triplet Loss +<br/><b>aSchool of Engineering and Technology, University of Hertfordshire, Hat eld AL10 9AB, UK</b><br/>bIDscan Biometrics (a GBG company), London E14 9QD, UK +</td><td>('2133352', 'Li Meng', 'li meng')<br/>('46301106', 'Margaret Hartnett', 'margaret hartnett')</td><td></td></tr><tr><td>3b9b200e76a35178da940279d566bbb7dfebb787</td><td>Learning Channel Inter-dependencies at Multiple Scales on Dense <br/>Networks for Face Recognition <br/>109 Research Way — PO Box 6109 Morgantown, West Virginia <br/><b>West Virginia University</b><br/>November 29, 2017 @@ -2408,7 +2801,10 @@ <br/>Face Recognition in Personal Photo Collections <br/>Anonymous CVPR submission <br/>Paper ID 2052 -</td><td></td><td></td></tr><tr><td>3b557c4fd6775afc80c2cf7c8b16edde125b270e</td><td>Face Recognition: Perspectives from the +</td><td></td><td></td></tr><tr><td>3bb6570d81685b769dc9e74b6e4958894087f3f1</td><td>Hu-Fu: Hardware and Software Collaborative +<br/>Attack Framework against Neural Networks +<br/><b>Beijing National Research Center for Information Science and Technology</b><br/><b>Tsinghua University</b></td><td>('3493074', 'Wenshuo Li', 'wenshuo li')<br/>('1909938', 'Jincheng Yu', 'jincheng yu')<br/>('6636914', 'Xuefei Ning', 'xuefei ning')<br/>('2892980', 'Pengjun Wang', 'pengjun wang')<br/>('49988678', 'Qi Wei', 'qi wei')<br/>('47904166', 'Yu Wang', 'yu wang')<br/>('39150998', 'Huazhong Yang', 'huazhong yang')</td><td>{lws17@mails.tsinghua.edu.cn, yu-wang@tsinghua.edu.cn} +</td></tr><tr><td>3b557c4fd6775afc80c2cf7c8b16edde125b270e</td><td>Face Recognition: Perspectives from the <br/>Real-World <br/><b>Institute for Infocomm Research, A*STAR</b><br/>1 Fusionopolis Way, #21-01 Connexis (South Tower), Singapore 138632. <br/>Phone: +65 6408 2071; Fax: +65 6776 1378; @@ -2435,7 +2831,10 @@ </td></tr><tr><td>3b470b76045745c0ef5321e0f1e0e6a4b1821339</td><td>Consensus of Regression for Occlusion-Robust <br/>Facial Feature Localization <br/><b>Rutgers University, Piscataway, NJ 08854, USA</b><br/>2 Adobe Research, San Jose, CA 95110, USA -</td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>6f288a12033fa895fb0e9ec3219f3115904f24de</td><td>Learning Expressionlets via Universal Manifold +</td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>6f5ce5570dc2960b8b0e4a0a50eab84b7f6af5cb</td><td>Low Resolution Face Recognition Using a +<br/>Two-Branch Deep Convolutional Neural Network +<br/>Architecture +</td><td>('19189138', 'Erfan Zangeneh', 'erfan zangeneh')<br/>('1772623', 'Mohammad Rahmati', 'mohammad rahmati')<br/>('3071758', 'Yalda Mohsenzadeh', 'yalda mohsenzadeh')</td><td></td></tr><tr><td>6f288a12033fa895fb0e9ec3219f3115904f24de</td><td>Learning Expressionlets via Universal Manifold <br/>Model for Dynamic Facial Expression Recognition </td><td>('1730228', 'Mengyi Liu', 'mengyi liu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('3373117', 'Ruiping Wang', 'ruiping wang')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td></td></tr><tr><td>6fa0c206873dcc5812f7ea74a48bb4bf4b273494</td><td>Real-time Mobile Facial Expression Recognition System – A Case Study <br/>Department of Computer Engineering @@ -2471,7 +2870,14 @@ <br/>Blood Reveal Novel Biomarkers for Early Detection Of <br/>Clinical Alzheimer’s Disease <br/><b>Centre for Bioinformatics, Biomarker Discovery and Information-Based Medicine, The University of Newcastle, Callaghan, Australia, 2 Departamento de Engenharia de</b><br/>Produc¸a˜o, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil -</td><td>('8423987', 'Mateus Rocha de Paula', 'mateus rocha de paula')<br/>('34861417', 'Regina Berretta', 'regina berretta')<br/>('1738680', 'Pablo Moscato', 'pablo moscato')</td><td></td></tr><tr><td>6f75697a86d23d12a14be5466a41e5a7ffb79fad</td><td></td><td></td><td></td></tr><tr><td>6f6b4e2885ea1d9bea1bb2ed388b099a5a6d9b81</td><td>Structured Output SVM Prediction of Apparent Age, +</td><td>('8423987', 'Mateus Rocha de Paula', 'mateus rocha de paula')<br/>('34861417', 'Regina Berretta', 'regina berretta')<br/>('1738680', 'Pablo Moscato', 'pablo moscato')</td><td></td></tr><tr><td>6f75697a86d23d12a14be5466a41e5a7ffb79fad</td><td></td><td></td><td></td></tr><tr><td>6f7d06ced04ead3b9a5da86b37e7c27bfcedbbdd</td><td>Pages 51.1-51.12 +<br/>DOI: https://dx.doi.org/10.5244/C.30.51 +</td><td></td><td></td></tr><tr><td>6f7a8b3e8f212d80f0fb18860b2495be4c363eac</td><td>Creating Capsule Wardrobes from Fashion Images +<br/>UT-Austin +<br/>UT-Austin +</td><td>('22211024', 'Wei-Lin Hsiao', 'wei-lin hsiao')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>kimhsiao@cs.utexas.edu +<br/>grauman@cs.utexas.edu +</td></tr><tr><td>6f6b4e2885ea1d9bea1bb2ed388b099a5a6d9b81</td><td>Structured Output SVM Prediction of Apparent Age, <br/>Gender and Smile From Deep Features <br/>Michal Uˇriˇc´aˇr <br/>CMP, Dept. of Cybernetics @@ -2510,6 +2916,17 @@ <br/>*AICTE Emeritus Fellow </td><td>('1694317', 'Mrinal Kanti Bhowmik', 'mrinal kanti bhowmik')<br/>('1721942', 'Debotosh Bhattacharjee', 'debotosh bhattacharjee')<br/>('1729425', 'Mita Nasipuri', 'mita nasipuri')<br/>('1679476', 'Dipak Kumar Basu', 'dipak kumar basu')<br/>('1727663', 'Mahantapas Kundu', 'mahantapas kundu')</td><td>mkb_cse@yahoo.co.in <br/>debotosh@indiatimes.com, mitanasipuri@gmail.com, dipakkbasu@gmail.com, mkundu@cse.jdvu.ac.in +</td></tr><tr><td>6fea198a41d2f6f73e47f056692f365c8e6b04ce</td><td>Video Captioning with Boundary-aware Hierarchical Language +<br/>Decoding and Joint Video Prediction +<br/><b>Nanyang Technological University</b><br/><b>Nanyang Technological University</b><br/>Singapore, Singapore +<br/>Singapore, Singapore +<br/><b>Nanyang Technological University</b><br/>Singapore, Singapore +<br/>Shafiq Joty +<br/><b>Nanyang Technological University</b><br/>Singapore, Singapore +</td><td>('8668622', 'Xiangxi Shi', 'xiangxi shi')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')<br/>('2174964', 'Jiuxiang Gu', 'jiuxiang gu')</td><td>xxshi@ntu.edu.sg +<br/>JGU004@e.ntu.edu.sg +<br/>asjfcai@ntu.edu.sg +<br/>srjoty@ntu.edu.sg </td></tr><tr><td>6fbb179a4ad39790f4558dd32316b9f2818cd106</td><td>Input Aggregated Network for Face Video Representation <br/><b>Beijing Laboratory of IIT, School of Computer Science, Beijing Institute of Technology, Beijing, China</b><br/><b>Stony Brook University, Stony Brook, USA</b></td><td>('40061483', 'Zhen Dong', 'zhen dong')<br/>('3306427', 'Su Jia', 'su jia')<br/>('1690083', 'Chi Zhang', 'chi zhang')<br/>('35371203', 'Mingtao Pei', 'mingtao pei')</td><td></td></tr><tr><td>6f84e61f33564e5188136474f9570b1652a0606f</td><td>Dual Motion GAN for Future-Flow Embedded Video Prediction <br/><b>Carnegie Mellon University</b></td><td>('40250403', 'Xiaodan Liang', 'xiaodan liang')<br/>('3682478', 'Lisa Lee', 'lisa lee')</td><td>{xiaodan1,lslee}@cs.cmu.edu @@ -2521,7 +2938,14 @@ <br/>c(cid:1) Springer-Verlag 2005 <br/>intelligent <br/>interaction, -</td><td>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td></td></tr><tr><td>6fa3857faba887ed048a9e355b3b8642c6aab1d8</td><td>Face Recognition in Challenging Environments: +</td><td>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td></td></tr><tr><td>6f3054f182c34ace890a32fdf1656b583fbc7445</td><td>Article +<br/>Age Estimation Robust to Optical and Motion +<br/>Blurring by Deep Residual CNN +<br/><b>Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu</b><br/>Received: 9 March 2018; Accepted: 10 April 2018; Published: 13 April 2018 +</td><td>('31515471', 'Jeon Seong Kang', 'jeon seong kang')<br/>('31864414', 'Chan Sik Kim', 'chan sik kim')<br/>('29944844', 'Se Woon Cho', 'se woon cho')<br/>('4634733', 'Kang Ryoung Park', 'kang ryoung park')</td><td>Seoul 100-715, Korea; kjs2605@dgu.edu (J.S.K.); kimchsi9004@naver.com (C.S.K.); +<br/>lyw941021@dongguk.edu (Y.W.L.); jsu319@naver.com (S.W.C.) +<br/>* Correspondence: parkgr@dongguk.edu; Tel.: +82-10-3111-7022; Fax: +82-2-2277-8735 +</td></tr><tr><td>6fa3857faba887ed048a9e355b3b8642c6aab1d8</td><td>Face Recognition in Challenging Environments: <br/>An Experimental and Reproducible Research <br/>Survey </td><td>('2121764', 'Laurent El Shafey', 'laurent el shafey')</td><td></td></tr><tr><td>6fda12c43b53c679629473806c2510d84358478f</td><td>Journal of Academic and Applied Studies @@ -2532,13 +2956,23 @@ <br/><b>Islamic Azad University</b><br/>Iran </td><td></td><td>Available online @ www.academians.org <br/>Email:a.jamshidnejad@yahoo.com +</td></tr><tr><td>6fef65bd7287b57f0c3b36bf8e6bc987fd161b7d</td><td>Deep Discriminative Model for Video +<br/>Classification +<br/>Center for Machine Vision and Signal Analysis (CMVS) +<br/><b>University of Oulu, Finland</b></td><td>('2014145', 'Mohammad Tavakolian', 'mohammad tavakolian')<br/>('1751372', 'Abdenour Hadid', 'abdenour hadid')</td><td>firstname.lastname@oulu.fi </td></tr><tr><td>6f7ce89aa3e01045fcd7f1c1635af7a09811a1fe</td><td>978-1-4673-0046-9/12/$26.00 ©2012 IEEE <br/>937 <br/>ICASSP 2012 </td><td></td><td></td></tr><tr><td>6fe2efbcb860767f6bb271edbb48640adbd806c3</td><td>SOFT BIOMETRICS: HUMAN IDENTIFICATION USING COMPARATIVE DESCRIPTIONS <br/>Soft Biometrics; Human Identification using <br/>Comparative Descriptions -</td><td>('34386180', 'Daniel A. Reid', 'daniel a. reid')<br/>('1727698', 'Mark S. Nixon', 'mark s. nixon')<br/>('2093843', 'Sarah V. Stevenage', 'sarah v. stevenage')</td><td></td></tr><tr><td>6f5151c7446552fd6a611bf6263f14e729805ec7</td><td>5KHHAO /7 %:0 7 +</td><td>('34386180', 'Daniel A. Reid', 'daniel a. reid')<br/>('1727698', 'Mark S. Nixon', 'mark s. nixon')<br/>('2093843', 'Sarah V. Stevenage', 'sarah v. stevenage')</td><td></td></tr><tr><td>6fdc0bc13f2517061eaa1364dcf853f36e1ea5ae</td><td>DAISEE: Dataset for Affective States in +<br/>E-Learning Environments +<br/>1 Microsoft India R&D Pvt. Ltd. +<br/>2 Department of Computer Science, IIT Hyderabad +</td><td>('50178849', 'Abhay Gupta', 'abhay gupta')<br/>('3468123', 'Richik Jaiswal', 'richik jaiswal')<br/>('3468212', 'Sagar Adhikari', 'sagar adhikari')<br/>('1973980', 'Vineeth Balasubramanian', 'vineeth balasubramanian')</td><td>abhgup@microsoft.com +<br/>{cs12b1032, cs12b1034, vineethnb}@iith.ac.in +</td></tr><tr><td>6f5151c7446552fd6a611bf6263f14e729805ec7</td><td>5KHHAO /7 %:0 7 <br/>)>IJH=?J 9EJDE JDA ?JANJ B=?A ANFHAIIE ?=IIE?=JE KIEC JDA <br/>FH>=>EEJEAI JD=J A=?D A B IALAH= ?O ??KHHEC )7 CHKFI EI <br/>?=IIIAF=H=>EEJO MAECDJEC @@ -2575,7 +3009,11 @@ <br/>D=I >AA BK@ DMALAH JD=J ?F=H=>A H >AJJAH HAIKJI ?= >A >J=EA@ >O <br/>J=EC = HA DEIJE? =FFH=?D J BA=JKHA ANJH=?JE KIEC AJD@I IK?D =I <br/>?F=HA JM IK?D AJD@I =AO 2+) " =@ ?= >E=HO F=JJAH *2 -</td></tr><tr><td>03d9ccce3e1b4d42d234dba1856a9e1b28977640</td><td></td><td></td><td></td></tr><tr><td>036c41d67b49e5b0a578a401eb31e5f46b3624e0</td><td>The Tower Game Dataset: A Multimodal Dataset +</td></tr><tr><td>03c56c176ec6377dddb6a96c7b2e95408db65a7a</td><td>A Novel Geometric Framework on Gram Matrix +<br/>Trajectories for Human Behavior Understanding +</td><td>('46243486', 'Anis Kacem', 'anis kacem')<br/>('2909056', 'Mohamed Daoudi', 'mohamed daoudi')<br/>('2125606', 'Boulbaba Ben Amor', 'boulbaba ben amor')<br/>('2507859', 'Stefano Berretti', 'stefano berretti')</td><td></td></tr><tr><td>03d9ccce3e1b4d42d234dba1856a9e1b28977640</td><td></td><td></td><td></td></tr><tr><td>0322e69172f54b95ae6a90eb3af91d3daa5e36ea</td><td>Face Classification using Adjusted Histogram in +<br/>Grayscale +</td><td></td><td></td></tr><tr><td>036c41d67b49e5b0a578a401eb31e5f46b3624e0</td><td>The Tower Game Dataset: A Multimodal Dataset <br/>for Analyzing Social Interaction Predicates <br/>∗ SRI International <br/><b>University of California, Santa Cruz</b><br/><b>University of California, Berkeley</b></td><td>('1955011', 'David A. Salter', 'david a. salter')<br/>('1860011', 'Amir Tamrakar', 'amir tamrakar')<br/>('1832513', 'Behjat Siddiquie', 'behjat siddiquie')<br/>('4599641', 'Mohamed R. Amer', 'mohamed r. amer')<br/>('1696401', 'Ajay Divakaran', 'ajay divakaran')<br/>('40530418', 'Brian Lande', 'brian lande')<br/>('2108704', 'Darius Mehri', 'darius mehri')</td><td>Email: {david.salter, amir.tamrakar, behjat.siddiquie, mohamed.amer, ajay.divakaran}@sri.com @@ -2586,7 +3024,9 @@ <br/>Cortexica Vision Systems Limited </td><td>('39599054', 'Biswa Sengupta', 'biswa sengupta')<br/>('29742002', 'Yu Qian', 'yu qian')</td><td>b.sengupta@imperial.ac.uk </td></tr><tr><td>03f7041515d8a6dcb9170763d4f6debd50202c2b</td><td>Clustering Millions of Faces by Identity -</td><td>('40653304', 'Charles Otto', 'charles otto')<br/>('7496032', 'Dayong Wang', 'dayong wang')<br/>('40217643', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>03b99f5abe0e977ff4c902412c5cb832977cf18e</td><td>CROWLEY AND ZISSERMAN: OF GODS AND GOATS +</td><td>('40653304', 'Charles Otto', 'charles otto')<br/>('7496032', 'Dayong Wang', 'dayong wang')<br/>('40217643', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>03ce2ff688f9b588b6f264ca79c6857f0d80ceae</td><td>Attention Clusters: Purely Attention Based +<br/>Local Feature Integration for Video Classification +<br/><b>Tsinghua University, 2Rutgers University, 3Massachusetts Institute of Technology, 4Baidu IDL</b></td><td>('1716690', 'Xiang Long', 'xiang long')<br/>('2551285', 'Chuang Gan', 'chuang gan')<br/>('1732213', 'Gerard de Melo', 'gerard de melo')<br/>('3045089', 'Jiajun Wu', 'jiajun wu')<br/>('48033101', 'Xiao Liu', 'xiao liu')<br/>('35247507', 'Shilei Wen', 'shilei wen')</td><td></td></tr><tr><td>03b99f5abe0e977ff4c902412c5cb832977cf18e</td><td>CROWLEY AND ZISSERMAN: OF GODS AND GOATS <br/>Of Gods and Goats: Weakly Supervised <br/>Learning of Figurative Art <br/>Elliot J. Crowley @@ -2697,7 +3137,17 @@ </td></tr><tr><td>03f98c175b4230960ac347b1100fbfc10c100d0c</td><td>Supervised Descent Method and its Applications to Face Alignment <br/><b>The Robotics Institute, Carnegie Mellon University, Pittsburgh PA</b></td><td>('3182065', 'Xuehan Xiong', 'xuehan xiong')<br/>('1707876', 'Fernando De la Torre', 'fernando de la torre')</td><td>xxiong@andrew.cmu.edu <br/>ftorre@cs.cmu.edu -</td></tr><tr><td>03264e2e2709d06059dd79582a5cc791cbef94b1</td><td>Convolutional Neural Networks for Facial Attribute-based Active Authentication +</td></tr><tr><td>032825000c03b8ab4c207e1af4daeb1f225eb025</td><td>J. Appl. Environ. Biol. Sci., 7(10)159-164, 2017 +<br/>ISSN: 2090-4274 +<br/>© 2017, TextRoad Publication +<br/>Journal of Applied Environmental +<br/>and Biological Sciences +<br/>www.textroad.com +<br/>A Novel Approach for Human Face Detection in Color Images Using Skin +<br/>Color and Golden Ratio +<br/><b>Bacha Khan University, Charsadda, KPK, Pakistan</b><br/><b>Abdul WaliKhan University, Mardan, KPK, Pakistan</b><br/>Received: May 9, 2017 +<br/>Accepted: August 2, 2017 +</td><td>('12144785', 'Faizan Ullah', 'faizan ullah')<br/>('49669073', 'Dilawar Shah', 'dilawar shah')<br/>('46463663', 'Sabir Shah', 'sabir shah')<br/>('47160013', 'Abdus Salam', 'abdus salam')<br/>('12579194', 'Shujaat Ali', 'shujaat ali')</td><td></td></tr><tr><td>03264e2e2709d06059dd79582a5cc791cbef94b1</td><td>Convolutional Neural Networks for Facial Attribute-based Active Authentication <br/>On Mobile Devices <br/><b>University of Maryland, College Park</b><br/><b>University of Maryland, College Park</b><br/>MD, USA <br/>MD, USA @@ -2837,7 +3287,38 @@ <br/>Ben Amar1 <br/><b>Research Groups on Intelligent Machines, University of Sfax, Sfax 3038, Tunisia</b><br/><b>University of Houston, Houston, TX 77204, USA</b></td><td>('2791150', 'Mohamed Anouar Borgi', 'mohamed anouar borgi')<br/>('8847309', 'Demetrio Labate', 'demetrio labate')</td><td>{anoir.borgi@ieee.org ; dlabate@math.uh.edu ; <br/>maher.elarbi@gmail.com; chokri.benamar@ieee.org} -</td></tr><tr><td>03baf00a3d00887dd7c828c333d4a29f3aacd5f5</td><td>Entropy Based Feature Selection for 3D Facial +</td></tr><tr><td>03ac1c694bc84a27621da6bfe73ea9f7210c6d45</td><td>Chapter 1 +<br/>Introduction to information security +<br/>foundations and applications +<br/>1.1 Background +<br/>Information security has extended to include several research directions like user +<br/>authentication and authorization, network security, hardware security, software secu- +<br/>rity, and data cryptography. Information security has become a crucial need for +<br/>protecting almost all information transaction applications. Security is considered as +<br/>an important science discipline whose many multifaceted complexities deserve the +<br/>synergy of the computer science and engineering communities. +<br/>Recently, due to the proliferation of Information and Communication Tech- +<br/>nologies, information security has started to cover emerging topics such as cloud +<br/>computing security, smart cities’ security and privacy, healthcare and telemedicine, +<br/>the Internet-of-Things (IoT) security [1], the Internet-of-Vehicles security, and sev- +<br/>eral types of wireless sensor networks security [2,3]. In addition, information security +<br/>has extended further to cover not only technical security problems but also social and +<br/>organizational security challenges [4,5]. +<br/>Traditional systems’ development approaches were focusing on the system’s +<br/>usability where security was left to the last stage with less priority. However, the +<br/>new design approaches consider security-in-design process where security is consid- +<br/>ered at the early phase of the design process. The new designed systems should be +<br/>well protected against the available security attacks. Having new systems such as IoT +<br/>or healthcare without enough security may lead to a leakage of sensitive data and, in +<br/>some cases, life threatening situations. +<br/>Taking the social aspect into account, security education is a vital need for both +<br/>practitioners and system users [6]. Users’ misbehaviour due to a lack of security +<br/>knowledge is the weakest point in the system security chain. The users’ misbehaviour +<br/>is considered as a security vulnerability that may be exploited for launching security +<br/>attacks. A successful security attack such as distributed denial-of-service attack will +<br/>impose incident recovery cost in addition to the downtime cost. +<br/><b>Electrical and Space Engineering, Lule University of Technology</b><br/>Sweden +<br/><b>Faculty of Engineering, Al Azhar University, Qena, Egypt</b></td><td>('4073409', 'Ali Ismail Awad', 'ali ismail awad')</td><td></td></tr><tr><td>03baf00a3d00887dd7c828c333d4a29f3aacd5f5</td><td>Entropy Based Feature Selection for 3D Facial <br/>Expression Recognition <br/>Submitted to the <br/><b>Institute of Graduate Studies and Research</b><br/>in partial fulfillment of the requirements for the Degree of @@ -3020,7 +3501,128 @@ </td></tr><tr><td>03701e66eda54d5ab1dc36a3a6d165389be0ce79</td><td>179 <br/>Improved Principal Component Regression for Face <br/>Recognition Under Illumination Variations -</td><td>('1776127', 'Shih-Ming Huang', 'shih-ming huang')<br/>('1749263', 'Jar-Ferr Yang', 'jar-ferr yang')</td><td></td></tr><tr><td>9b318098f3660b453fbdb7a579778ab5e9118c4c</td><td>3931 +</td><td>('1776127', 'Shih-Ming Huang', 'shih-ming huang')<br/>('1749263', 'Jar-Ferr Yang', 'jar-ferr yang')</td><td></td></tr><tr><td>03fe3d031afdcddf38e5cc0d908b734884542eeb</td><td>DOI: http://dx.doi.org/10.14236/ewic/EVA2017.60 +<br/>Engagement with Artificial Intelligence +<br/>through Natural Interaction Models +<br/>Sara (Salevati) Feldman +<br/><b>Simon Fraser University</b><br/>Vancouver, Canada +<br/><b>Simon Fraser University</b><br/>Vancouver, Canada +<br/><b>Simon Fraser University</b><br/>Vancouver, Canada +<br/>As Artificial Intelligence (AI) systems become more ubiquitous, what user experience design +<br/>paradigms will be used by humans to impart their needs and intents to an AI system, in order to +<br/>engage in a more social interaction? In our work, we look mainly at expression and creativity +<br/>based systems, where the AI both attempts to model or understand/assist in processes of human +<br/>expression and creativity. We therefore have designed and implemented a prototype system with +<br/>more natural interaction modes for engagement with AI as well as other human computer +<br/>interaction (HCI) where a more open natural communication stream is beneficial. Our proposed +<br/>conversational agent system makes use of the affective signals from the gestural behaviour of the +<br/>user and the semantic information from the speech input in order to generate a personalised, +<br/>human-like conversation that is expressed in the visual and conversational output of the 3D virtual +<br/>avatar system. We describe our system and two application spaces we are using it in – a care +<br/>advisor / assistant for the elderly and an interactive creative assistant for uses to produce art +<br/>forms. +<br/>Artificial Intelligence. Natural user interfaces. Voice systems. Expression systems. ChatBots. +<br/>1. INTRODUCTION +<br/>is +<br/>for +<br/>way +<br/>there +<br/>sensor +<br/>natural +<br/>devices, +<br/>understand +<br/>requirement +<br/>to +<br/>the human +<br/>Due to the increase of natural user interfaces and +<br/>untethered +<br/>a +<br/>corresponding +<br/>for computational +<br/>models that can utilise interactive and affective +<br/>user data in order to understand and emulate a +<br/>more +<br/>conversational +<br/>communication. From an emulation standpoint, it is +<br/>the mechanisms +<br/>important +<br/>underlying +<br/>to human multilayered +<br/>semantic communication to achieve a more natural +<br/>user experience. Humans tend to make use of +<br/>gestures and expressions +<br/>in a conversational +<br/>setting in addition to the linguistic components that +<br/>allow them to express more than the semantics of +<br/>is usually +<br/>the utterances. This phenomenon +<br/>automated +<br/>current +<br/>disregarded +<br/>to +<br/>conversational +<br/>due +<br/>being +<br/>computationally demanding and +<br/>requiring a +<br/>cognitive component to be able to model the +<br/>complexity of the additional signals. With the +<br/>advances in the current technology we are now +<br/>closer to achieve more natural-like conversational +<br/>systems. Gesture capture and recognition systems +<br/>for video and sound input can be combined with +<br/>output systems such as Artificial Intelligence (AI) +<br/>based conversational +<br/>tools and 3D modelling +<br/>systems +<br/>the +<br/>in +<br/>© Feldman et al. Published by +<br/>BCS Learning and Development Ltd. +<br/>Proceedings of Proceedings of EVA London 2017, UK +<br/>296 +<br/>to +<br/>include +<br/>in order +<br/>systems +<br/>to achieve human-level +<br/>meaningful communication. This may allow the +<br/>interaction to be more intuitive, open and fluent that +<br/>can be more helpful in certain situations. In this +<br/>work, we attempt +<br/>the affective +<br/>components from these input signals in order to +<br/>generate a compatible and personalised character +<br/>that can reflect some human-like qualities. +<br/>Given +<br/>these goals, we overview our 3D +<br/>conversational avatar system and describe its use +<br/>in our two application spaces, stressing its use +<br/>where AI systems are involved. Our first application +<br/>space is CareAdvisor, for maintaining active and +<br/>healthy aging in older adults through a multi- +<br/>modular Personalised Virtual Coaching system. +<br/>Here the natural communication system is better +<br/>suited for the elderly, who are technologically less +<br/>experienced, +<br/>non- +<br/>confrontationally and as an assistant conduit to +<br/>health data from other less conversational devices. +<br/>Our second application space is in the interactive +<br/>art exhibition area, where our avatar system is able +<br/>to converse with users in a more open way, +<br/>compared to say forms and input systems, on +<br/>issues of art and creativity. This allows for more +<br/>open, +<br/>to an +<br/>intuitive conversation +<br/>especially when +<br/>leading +<br/>used +</td><td>('22588208', 'Ozge Nilay Yalcin', 'ozge nilay yalcin')<br/>('1700040', 'Steve DiPaola', 'steve dipaola')</td><td>sara_salevati@sfu.ca +<br/>oyalcin@sfu.ca +<br/>sdipaola@sfu.ca +</td></tr><tr><td>9b318098f3660b453fbdb7a579778ab5e9118c4c</td><td>3931 <br/>Joint Patch and Multi-label Learning for Facial <br/>Action Unit and Holistic Expression Recognition <br/>classifiers without @@ -3034,6 +3636,13 @@ <br/>doi: 10.1049/iet-bmt.2015.0008 <br/>www.ietdl.org <br/><b>North Dakota State University, Fargo, ND 58108-6050, USA</b><br/><b>Faculty of Computer Science, Mathematics, and Engineering, University of Twente, Enschede, Netherlands</b></td><td>('3001880', 'Zahid Mahmood', 'zahid mahmood')<br/>('1798087', 'Tauseef Ali', 'tauseef ali')</td><td>✉ E-mail: zahid.mahmood@ndsu.edu +</td></tr><tr><td>9bd35145c48ce172b80da80130ba310811a44051</td><td>Face Detection with End-to-End Integration of a +<br/>ConvNet and a 3D Model +<br/>1Nat’l Engineering Laboratory for Video Technology, +<br/>Key Laboratory of Machine Perception (MoE), +<br/>Cooperative Medianet Innovation Center, Shanghai +<br/><b>Sch l of EECS, Peking University, Beijing, 100871, China</b><br/>2Department of ECE and the Visual Narrative Cluster, +<br/><b>North Carolina State University, Raleigh, USA</b></td><td>('3422021', 'Yunzhu Li', 'yunzhu li')<br/>('3423002', 'Benyuan Sun', 'benyuan sun')<br/>('47353858', 'Tianfu Wu', 'tianfu wu')<br/>('1717863', 'Yizhou Wang', 'yizhou wang')</td><td>{leo.liyunzhu, sunbenyuan, Yizhou.Wang}@pku.edu.cn, tianfu wu@ncsu.edu </td></tr><tr><td>9b000ccc04a2605f6aab867097ebf7001a52b459</td><td></td><td></td><td></td></tr><tr><td>9b0489f2d5739213ef8c3e2e18739c4353c3a3b7</td><td>Visual Data Augmentation through Learning <br/><b>Imperial College London, UK</b><br/><b>Middlesex University London, UK</b></td><td>('34586458', 'Grigorios G. Chrysos', 'grigorios g. chrysos')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td>{g.chrysos, i.panagakis, s.zafeiriou}@imperial.ac.uk </td></tr><tr><td>9b474d6e81e3b94e0c7881210e249689139b3e04</td><td>VG-RAM Weightless Neural Networks for @@ -3076,9 +3685,22 @@ </td><td>('1699216', 'Alberto F. De Souza', 'alberto f. de souza')<br/>('3015563', 'Claudine Badue', 'claudine badue')<br/>('3158075', 'Felipe Pedroni', 'felipe pedroni')<br/>('3169286', 'Hallysson Oliveira', 'hallysson oliveira')</td><td></td></tr><tr><td>9b928c0c7f5e47b4480cb9bfdf3d5b7a29dfd493</td><td>Close the Loop: Joint Blind Image Restoration and Recognition <br/>with Sparse Representation Prior <br/><b>School of Computer Science, Northwestern Polytechnical University, Xi an China</b><br/><b>Beckman Institute, University of Illinois at Urbana-Champaign, IL USA</b><br/><b>U.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi, MD USA</b></td><td>('40479011', 'Haichao Zhang', 'haichao zhang')<br/>('1706007', 'Jianchao Yang', 'jianchao yang')<br/>('1801395', 'Yanning Zhang', 'yanning zhang')<br/>('8147588', 'Nasser M. Nasrabadi', 'nasser m. nasrabadi')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>‡{hczhang,jyang29,huang}@ifp.uiuc.edu †ynzhang@nwpu.edu.cn §nasser.m.nasrabadi.civ@mail.mil +</td></tr><tr><td>9bc01fa9400c231e41e6a72ec509d76ca797207c</td><td></td><td></td><td></td></tr><tr><td>9b2c359c36c38c289c5bacaeb5b1dd06b464f301</td><td>Dense Face Alignment +<br/><b>Michigan State University, MI</b><br/>2Monta Vista High School, Cupertino, CA +</td><td>('6797891', 'Yaojie Liu', 'yaojie liu')<br/>('2357264', 'Amin Jourabloo', 'amin jourabloo')<br/>('26365310', 'William Ren', 'william ren')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>1{liuyaoj1,jourablo,liuxm}@msu.edu, 2williamyren@gmail.com </td></tr><tr><td>9bcfadd22b2c84a717c56a2725971b6d49d3a804</td><td>How to Detect a Loss of Attention in a Tutoring System <br/>using Facial Expressions and Gaze Direction -</td><td>('2975858', 'Mark ter Maat', 'mark ter maat')</td><td></td></tr><tr><td>9b07084c074ba3710fee59ed749c001ae70aa408</td><td>698535 CDPXXX10.1177/0963721417698535MartinezComputational Models of Face Perception +</td><td>('2975858', 'Mark ter Maat', 'mark ter maat')</td><td></td></tr><tr><td>9b1bcef8bfef0fb5eb5ea9af0b699aa0534fceca</td><td>Position-Squeeze and Excitation Module +<br/>for Facial Attribute Analysis +<br/>Shanghai Key Laboratory of +<br/>Multidimensional Information +<br/>Processing, +<br/><b>East China Normal University</b><br/>200241 Shanghai, China +</td><td>('36124320', 'Yan Zhang', 'yan zhang')<br/>('7962836', 'Wanxia Shen', 'wanxia shen')<br/>('49755228', 'Li Sun', 'li sun')<br/>('12493943', 'Qingli Li', 'qingli li')<br/>('36124320', 'Yan Zhang', 'yan zhang')<br/>('7962836', 'Wanxia Shen', 'wanxia shen')<br/>('49755228', 'Li Sun', 'li sun')<br/>('12493943', 'Qingli Li', 'qingli li')</td><td>452642781@qq.com +<br/>51151214005@ecnu.cn +<br/>sunli@ee.ecnu.edu.cn +<br/>qlli@cs.ecnu.edu.cn +</td></tr><tr><td>9b07084c074ba3710fee59ed749c001ae70aa408</td><td>698535 CDPXXX10.1177/0963721417698535MartinezComputational Models of Face Perception <br/>research-article2017 <br/>Computational Models of Face Perception <br/>Aleix M. Martinez @@ -3092,7 +3714,10 @@ <br/>DOI: 10.1177/0963721417698535 <br/>https://doi.org/10.1177/0963721417698535 <br/>www.psychologicalscience.org/CDPS -</td><td></td><td></td></tr><tr><td>9b246c88a0435fd9f6d10dc88f47a1944dd8f89e</td><td>PICODES: Learning a Compact Code for +</td><td></td><td></td></tr><tr><td>9be653e1bc15ef487d7f93aad02f3c9552f3ee4a</td><td>Computer Vision for Head Pose Estimation: +<br/>Review of a Competition +<br/><b>Tampere University of Technology, Finland</b><br/><b>University of Paderborn, Germany</b><br/>3 Zorgon, The Netherlands +</td><td>('1847889', 'Heikki Huttunen', 'heikki huttunen')<br/>('40394658', 'Ke Chen', 'ke chen')<br/>('2364638', 'Abhishek Thakur', 'abhishek thakur')<br/>('2558923', 'Artus Krohn-Grimberghe', 'artus krohn-grimberghe')<br/>('2300445', 'Oguzhan Gencoglu', 'oguzhan gencoglu')<br/>('3328835', 'Xingyang Ni', 'xingyang ni')<br/>('2067035', 'Mohammed Al-Musawi', 'mohammed al-musawi')<br/>('40448210', 'Lei Xu', 'lei xu')<br/>('3152947', 'Hendrik Jacob van Veen', 'hendrik jacob van veen')</td><td></td></tr><tr><td>9b246c88a0435fd9f6d10dc88f47a1944dd8f89e</td><td>PICODES: Learning a Compact Code for <br/>Novel-Category Recognition <br/><b>Dartmouth College</b><br/>Hanover, NH, U.S.A. <br/>Andrew Fitzgibbon @@ -3107,7 +3732,9 @@ <br/>Contour Detection <br/><b>School of Computer Engineering, Shahrood University of Technology, Shahrood, IRAN</b><br/>Received 26th September 2012, revised 27th October 2012, accepted 6th November 2012 <br/>Available online at: www.isca.in -</td><td></td><td></td></tr><tr><td>9b93406f3678cf0f16451140ea18be04784faeee</td><td>A Bayesian Approach to Alignment-Based +</td><td></td><td></td></tr><tr><td>9bac481dc4171aa2d847feac546c9f7299cc5aa0</td><td>Matrix Product State for Higher-Order Tensor +<br/>Compression and Classification +</td><td>('2852180', 'Johann A. Bengua', 'johann a. bengua')<br/>('2839912', 'Ho N. Phien', 'ho n. phien')<br/>('1834451', 'Minh N. Do', 'minh n. do')</td><td></td></tr><tr><td>9b93406f3678cf0f16451140ea18be04784faeee</td><td>A Bayesian Approach to Alignment-Based <br/>Image Hallucination <br/><b>University of Central Florida</b><br/>2 Microsoft Research New England </td><td>('1802944', 'Marshall F. Tappen', 'marshall f. tappen')<br/>('1681442', 'Ce Liu', 'ce liu')</td><td>mtappen@eecs.ucf.edu @@ -3117,6 +3744,17 @@ </td><td>('3057167', 'Renjie Liu', 'renjie liu')<br/>('36485086', 'Ruofei Du', 'ruofei du')<br/>('40371477', 'Bao-Liang Lu', 'bao-liang lu')</td><td></td></tr><tr><td>9b6d0b3fbf7d07a7bb0d86290f97058aa6153179</td><td>NII, Japan at the first THUMOS Workshop 2013 <br/><b>National Institute of Informatics</b><br/>2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo, Japan 101-8430 </td><td>('39814149', 'Sang Phan', 'sang phan')<br/>('1802416', 'Duy-Dinh Le', 'duy-dinh le')<br/>('40693818', 'Shin’ichi Satoh', 'shin’ichi satoh')</td><td>{plsang,ledduy,satoh}@nii.ac.jp +</td></tr><tr><td>9b684e2e2bb43862f69b12c6be94db0e7a756187</td><td>Differentiating Objects by Motion: +<br/>Joint Detection and Tracking of Small Flying Objects +<br/><b>The University of Tokyo</b><br/>CSIRO-Data61 +<br/><b>Australian National University</b><br/><b>The University of Tokyo</b><br/>Figure 1: Importance of multi-frame information for recognizing apparently small flying objects (birds in these examples). +<br/><b>While visual features in single frames are vague and limited, multi-frame information, including deformation and pose</b><br/>changes, provides better clues with which to recognize birds. To extract such useful motion patterns, tracking is necessary for +<br/>compensating translation of objects, but the tracking itself is a challenge due to the limited visual information. The blue boxes +<br/>are birds tracked by our method that utilizes multi-frame representation for detection, while the red boxes are the results of a +<br/>single-frame handcrafted-feature-based tracker [11] , which tends to fail when tracking small objects. +</td><td>('1890560', 'Ryota Yoshihashi', 'ryota yoshihashi')<br/>('38621343', 'Tu Tuan Trinh', 'tu tuan trinh')<br/>('48727803', 'Rei Kawakami', 'rei kawakami')<br/>('2941564', 'Shaodi You', 'shaodi you')<br/>('33313329', 'Makoto Iida', 'makoto iida')<br/>('48795689', 'Takeshi Naemura', 'takeshi naemura')</td><td>{yoshi, tu, rei, naemura}@hc.ic.i.u-tokyo.ac.jp +<br/>iida@ilab.eco.rcast.u-tokyo.ac.jp +<br/>shaodi.you@data61.csiro.au </td></tr><tr><td>9e8637a5419fec97f162153569ec4fc53579c21e</td><td>Segmentation and Normalization of Human Ears <br/>using Cascaded Pose Regression <br/><b>University of Applied Sciences Darmstadt - CASED</b><br/>Haardtring 100, @@ -3124,6 +3762,11 @@ <br/>http://www.h-da.de </td><td>('1742085', 'Christoph Busch', 'christoph busch')</td><td>anika.pflug@cased.de <br/>christoph.busch@hig.no +</td></tr><tr><td>9ea223c070ec9a00f4cb5ca0de35d098eb9a8e32</td><td>Exploring Temporal Preservation Networks for Precise Temporal Action +<br/>Localization +<br/>National Laboratory for Parallel and Distributed Processing, +<br/><b>National University of Defense Technology</b><br/>Changsha, China +</td><td>('2352864', 'Ke Yang', 'ke yang')<br/>('2292038', 'Peng Qiao', 'peng qiao')<br/>('1718853', 'Dongsheng Li', 'dongsheng li')<br/>('1893776', 'Shaohe Lv', 'shaohe lv')<br/>('1791001', 'Yong Dou', 'yong dou')</td><td>{yangke13,pengqiao,dongshengli,yongdou,shaohelv}@nudt.edu.cn </td></tr><tr><td>9e4b052844d154c3431120ec27e78813b637b4fc</td><td>Journal of AI and Data Mining <br/>Vol. 2, No .1, 2014, 33-38. <br/>Local gradient pattern - A novel feature representation for facial @@ -3184,7 +3827,9 @@ </td><td>('4241648', 'M. Saquib Sarfraz', 'm. saquib sarfraz')<br/>('6262445', 'Muhammad Adnan Siddique', 'muhammad adnan siddique')<br/>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')</td><td>saquib.sarfraz@kit.edu <br/>siddique@ifu.baug.ethz.ch <br/>rainer.stiefelhagen@kit.edu -</td></tr><tr><td>9e8d87dc5d8a6dd832716a3f358c1cdbfa97074c</td><td>What Makes an Image Popular? +</td></tr><tr><td>9e182e0cd9d70f876f1be7652c69373bcdf37fb4</td><td>Talking Face Generation by Adversarially +<br/>Disentangled Audio-Visual Representation +<br/><b>The Chinese University of Hong Kong</b></td><td>('40576774', 'Hang Zhou', 'hang zhou')<br/>('1715752', 'Yu Liu', 'yu liu')<br/>('3243969', 'Ziwei Liu', 'ziwei liu')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')</td><td></td></tr><tr><td>9e8d87dc5d8a6dd832716a3f358c1cdbfa97074c</td><td>What Makes an Image Popular? <br/><b>Massachusetts Institute</b><br/>of Technology <br/><b>eBay Research Labs</b><br/>DigitalGlobe </td><td>('2556428', 'Aditya Khosla', 'aditya khosla')<br/>('2541992', 'Atish Das Sarma', 'atish das sarma')<br/>('37164887', 'Raffay Hamid', 'raffay hamid')</td><td>khosla@csail.mit.edu @@ -3193,7 +3838,11 @@ </td></tr><tr><td>9e5c2d85a1caed701b68ddf6f239f3ff941bb707</td><td></td><td></td><td></td></tr><tr><td>044d9a8c61383312cdafbcc44b9d00d650b21c70</td><td>300 Faces in-the-Wild Challenge: The first facial landmark localization <br/>Challenge <br/><b>Imperial College London, UK</b><br/><b>School of Computer Science, University of Lincoln, U.K</b><br/><b>EEMCS, University of Twente, The Netherlands</b></td><td>('3320415', 'Christos Sagonas', 'christos sagonas')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td>{c.sagonas, gt204, s.zafeiriou, m.pantic}@imperial.ac.uk -</td></tr><tr><td>04bb3fa0824d255b01e9db4946ead9f856cc0b59</td><td></td><td></td><td></td></tr><tr><td>04f0292d9a062634623516edd01d92595f03bd3f</td><td>Distribution-based Iterative Pairwise Classification of +</td></tr><tr><td>04bb3fa0824d255b01e9db4946ead9f856cc0b59</td><td></td><td></td><td></td></tr><tr><td>040dc119d5ca9ea3d5fc39953a91ec507ed8cc5d</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Large-scale Bisample Learning on ID vs. Spot Face Recognition +<br/>Received: date / Accepted: date +</td><td>('8362374', 'Xiangyu Zhu', 'xiangyu zhu')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td></td></tr><tr><td>04f0292d9a062634623516edd01d92595f03bd3f</td><td>Distribution-based Iterative Pairwise Classification of <br/>Emotions in the Wild Using LGBP-TOP <br/><b>The University of Nottingham</b><br/>Mised Reality Lab <br/>Anıl Yüce @@ -3211,6 +3860,11 @@ <br/>Using DCT for Face Detection <br/><b>Technical University of Ostrava, FEECS</b><br/>17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic </td><td>('2467747', 'Radovan Fusek', 'radovan fusek')<br/>('2557877', 'Eduard Sojka', 'eduard sojka')</td><td>{radovan.fusek,eduard.sojka,karel.mozdren,milan.surkala}@vsb.cz +</td></tr><tr><td>04b851f25d6d49e61a528606953e11cfac7df2b2</td><td>Optical Flow Guided Feature: A Fast and Robust Motion Representation for +<br/>Video Action Recognition +<br/><b>The University of Sydney 2SenseTime Research 3The Chinese University of Hong Kong</b></td><td>('1837024', 'Shuyang Sun', 'shuyang sun')<br/>('1874900', 'Zhanghui Kuang', 'zhanghui kuang')<br/>('37145669', 'Lu Sheng', 'lu sheng')<br/>('3001348', 'Wanli Ouyang', 'wanli ouyang')<br/>('1726357', 'Wei Zhang', 'wei zhang')</td><td>{shuyang.sun wanli.ouyang}@sydney.edu.au +<br/>{wayne.zhang kuangzhanghui}@sensetime.com +<br/>lsheng@ee.cuhk.edu.hk </td></tr><tr><td>04522dc16114c88dfb0ebd3b95050fdbd4193b90</td><td>Appears in 2nd Canadian Conference on Computer and Robot Vision, Victoria, Canada, 2005. <br/>Minimum Bayes Error Features for Visual Recognition by Sequential Feature <br/>Selection and Extraction @@ -3268,6 +3922,19 @@ <br/>cropped face, we pass the cropped face on the Deep Multi- <br/>for </td><td>('27343041', 'Ayesha Gurnani', 'ayesha gurnani')<br/>('23922616', 'Vandit Gajjar', 'vandit gajjar')<br/>('22239413', 'Viraj Mavani', 'viraj mavani')<br/>('26425477', 'Yash Khandhediya', 'yash khandhediya')</td><td>{gurnani.ayesha.52, gajjar.vandit.381, mavani.viraj.604, khandhediya.yash.364}@ldce.ac.in +</td></tr><tr><td>043efe5f465704ced8d71a067d2b9d5aa5b59c29</td><td>EGGER ET AL.: OCCLUSION-AWARE 3D MORPHABLE FACE MODELS +<br/>Occlusion-aware 3D Morphable Face Models +<br/>Department of Mathematics and +<br/>Computer Science +<br/><b>University of Basel</b><br/>Basel Switzerland +<br/>http://gravis.cs.unibas.ch +<br/>Andreas Morel-Forster +</td><td>('34460642', 'Bernhard Egger', 'bernhard egger')<br/>('49462138', 'Andreas Schneider', 'andreas schneider')<br/>('39550224', 'Clemens Blumer', 'clemens blumer')<br/>('1987368', 'Sandro Schönborn', 'sandro schönborn')<br/>('1687079', 'Thomas Vetter', 'thomas vetter')</td><td>bernhard.egger@unibas.ch +<br/>andreas.schneider@unibas.ch +<br/>clemens.blumer@unibas.ch +<br/>andreas.forster@unibas.ch +<br/>sandro.schoenborn@unibas.ch +<br/>thomas.vetter@unibas.ch </td></tr><tr><td>044ba70e6744e80c6a09fa63ed6822ae241386f2</td><td>TO APPEAR IN AUTONOMOUS ROBOTS, SPECIAL ISSUE IN LEARNING FOR HUMAN-ROBOT COLLABORATION <br/>Early Prediction for Physical Human Robot <br/>Collaboration in the Operating Room @@ -3292,7 +3959,17 @@ </td><td>('1707922', 'Hongli Liu', 'hongli liu')</td><td></td></tr><tr><td>04250e037dce3a438d8f49a4400566457190f4e2</td><td></td><td></td><td></td></tr><tr><td>0431e8a01bae556c0d8b2b431e334f7395dd803a</td><td>Learning Localized Perceptual Similarity Metrics for Interactive Categorization <br/>Google Inc. <br/>google.com -</td><td>('2367820', 'Catherine Wah', 'catherine wah')</td><td></td></tr><tr><td>04616814f1aabe3799f8ab67101fbaf9fd115ae4</td><td><b>UNIVERSIT´EDECAENBASSENORMANDIEU.F.R.deSciences´ECOLEDOCTORALESIMEMTH`ESEPr´esent´eeparM.GauravSHARMAsoutenuele17D´ecembre2012envuedel’obtentionduDOCTORATdel’UNIVERSIT´EdeCAENSp´ecialit´e:InformatiqueetapplicationsArrˆet´edu07aoˆut2006Titre:DescriptionS´emantiquedesHumainsPr´esentsdansdesImagesVid´eo(SemanticDescriptionofHumansinImages)TheworkpresentedinthisthesiswascarriedoutatGREYC-UniversityofCaenandLEAR–INRIAGrenobleJuryM.PatrickPEREZDirecteurdeRechercheINRIA/Technicolor,RennesRapporteurM.FlorentPERRONNINPrincipalScientistXeroxRCE,GrenobleRapporteurM.JeanPONCEProfesseurdesUniversit´esENS,ParisExaminateurMme.CordeliaSCHMIDDirectricedeRechercheINRIA,GrenobleDirectricedeth`eseM.Fr´ed´ericJURIEProfesseurdesUniversit´esUniversit´edeCaenDirecteurdeth`ese</b></td><td></td><td></td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td>Hipster Wars: Discovering Elements +</td><td>('2367820', 'Catherine Wah', 'catherine wah')</td><td></td></tr><tr><td>04b4c779b43b830220bf938223f685d1057368e9</td><td>Video retrieval based on deep convolutional +<br/>neural network +<br/>Yajiao Dong +<br/>School of Information and Electronics, +<br/>Beijing Institution of Technology, Beijing, China +<br/>Jianguo Li +<br/>School of Information and Electronics, +<br/>Beijing Institution of Technology, Beijing, China +</td><td></td><td>yajiaodong@bit.edu.cn +<br/>jianguoli@bit.edu.cn +</td></tr><tr><td>04616814f1aabe3799f8ab67101fbaf9fd115ae4</td><td><b>UNIVERSIT´EDECAENBASSENORMANDIEU.F.R.deSciences´ECOLEDOCTORALESIMEMTH`ESEPr´esent´eeparM.GauravSHARMAsoutenuele17D´ecembre2012envuedel’obtentionduDOCTORATdel’UNIVERSIT´EdeCAENSp´ecialit´e:InformatiqueetapplicationsArrˆet´edu07aoˆut2006Titre:DescriptionS´emantiquedesHumainsPr´esentsdansdesImagesVid´eo(SemanticDescriptionofHumansinImages)TheworkpresentedinthisthesiswascarriedoutatGREYC-UniversityofCaenandLEAR–INRIAGrenobleJuryM.PatrickPEREZDirecteurdeRechercheINRIA/Technicolor,RennesRapporteurM.FlorentPERRONNINPrincipalScientistXeroxRCE,GrenobleRapporteurM.JeanPONCEProfesseurdesUniversit´esENS,ParisExaminateurMme.CordeliaSCHMIDDirectricedeRechercheINRIA,GrenobleDirectricedeth`eseM.Fr´ed´ericJURIEProfesseurdesUniversit´esUniversit´edeCaenDirecteurdeth`ese</b></td><td></td><td></td></tr><tr><td>04c2cda00e5536f4b1508cbd80041e9552880e67</td><td>Hipster Wars: Discovering Elements <br/>of Fashion Styles <br/><b>University of North Carolina at Chapel Hill, NC, USA</b><br/><b>Tohoku University, Japan</b></td><td>('1772294', 'M. Hadi Kiapour', 'm. hadi kiapour')<br/>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')<br/>('39668247', 'Alexander C. Berg', 'alexander c. berg')<br/>('1685538', 'Tamara L. Berg', 'tamara l. berg')</td><td>{hadi,aberg,tlberg}@cs.unc.edu <br/>kyamagu@vision.is.tohoku.ac.jp @@ -3325,11 +4002,34 @@ <br/>´emanant des ´etablissements d’enseignement et de <br/>recherche fran¸cais ou ´etrangers, des laboratoires <br/>publics ou priv´es. -</td><td>('3307172', 'Antoine Deleforge', 'antoine deleforge')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('2159538', 'Yoav Y. Schechner', 'yoav y. schechner')<br/>('1780746', 'Laurent Girin', 'laurent girin')<br/>('3307172', 'Antoine Deleforge', 'antoine deleforge')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('2159538', 'Yoav Y. Schechner', 'yoav y. schechner')<br/>('1780746', 'Laurent Girin', 'laurent girin')</td><td></td></tr><tr><td>046865a5f822346c77e2865668ec014ec3282033</td><td>Discovering Informative Social Subgraphs and Predicting +</td><td>('3307172', 'Antoine Deleforge', 'antoine deleforge')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('2159538', 'Yoav Y. Schechner', 'yoav y. schechner')<br/>('1780746', 'Laurent Girin', 'laurent girin')<br/>('3307172', 'Antoine Deleforge', 'antoine deleforge')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('2159538', 'Yoav Y. Schechner', 'yoav y. schechner')<br/>('1780746', 'Laurent Girin', 'laurent girin')</td><td></td></tr><tr><td>04317e63c08e7888cef480fe79f12d3c255c5b00</td><td>Face Recognition Using a Unified 3D Morphable Model +<br/>Hu, G., Yan, F., Chan, C-H., Deng, W., Christmas, W., Kittler, J., & Robertson, N. M. (2016). Face Recognition +<br/>Using a Unified 3D Morphable Model. In Computer Vision – ECCV 2016: 14th European Conference, +<br/>Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII (pp. 73-89). (Lecture Notes in +<br/>Computer Science; Vol. 9912). Springer Verlag. DOI: 10.1007/978-3-319-46484-8_5 +<br/>Published in: +<br/>Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, +<br/>2016, Proceedings, Part VIII +<br/>Document Version: +<br/>Peer reviewed version +<br/><b>Queen's University Belfast - Research Portal</b><br/><b>Link to publication record in Queen's University Belfast Research Portal</b><br/>Publisher rights +<br/>The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46484-8_5 +<br/>General rights +<br/><b>Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other</b><br/>copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated +<br/>with these rights. +<br/>Take down policy +<br/>The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to +<br/>ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the +<br/>Download date:12. Sep. 2018 +</td><td></td><td>Research Portal that you believe breaches copyright or violates any law, please contact openaccess@qub.ac.uk. +</td></tr><tr><td>046865a5f822346c77e2865668ec014ec3282033</td><td>Discovering Informative Social Subgraphs and Predicting <br/>Pairwise Relationships from Group Photos <br/><b>National Taiwan University, Taipei, Taiwan</b><br/>†Academia Sinica, Taipei, Taiwan </td><td>('35081710', 'Yan-Ying Chen', 'yan-ying chen')<br/>('1716836', 'Winston H. Hsu', 'winston h. hsu')<br/>('1704678', 'Hong-Yuan Mark Liao', 'hong-yuan mark liao')</td><td>yanying@cmlab.csie.ntu.edu.tw, winston@csie.ntu.edu.tw, liao@iis.sinica.edu.tw -</td></tr><tr><td>0470b0ab569fac5bbe385fa5565036739d4c37f8</td><td>Automatic Face Naming with Caption-based Supervision +</td></tr><tr><td>047bb1b1bd1f19b6c8d7ee7d0324d5ecd1a3efff</td><td>Unsupervised Training for 3D Morphable Model Regression +<br/><b>Princeton University</b><br/>2Google Research +<br/>3MIT CSAIL +</td><td>('32627314', 'Kyle Genova', 'kyle genova')<br/>('39578349', 'Forrester Cole', 'forrester cole')</td><td></td></tr><tr><td>0470b0ab569fac5bbe385fa5565036739d4c37f8</td><td>Automatic Face Naming with Caption-based Supervision <br/>To cite this version: <br/>with Caption-based Supervision. CVPR 2008 - IEEE Conference on Computer Vision <br/>Pattern Recognition, @@ -3370,7 +4070,7 @@ <br/><b>Max Planck Institute f ur biologische Kybernetik</b><br/>Spemannstr. 38, D-72076 T¨ubingen, Germany <br/>http://www.kyb.tuebingen.mpg.de/ </td><td>('1808255', 'Kwang In Kim', 'kwang in kim')<br/>('30541601', 'Matthias O. Franz', 'matthias o. franz')</td><td>{kimki, mof, bs}@tuebingen.mpg.de -</td></tr><tr><td>6a184f111d26787703f05ce1507eef5705fdda83</td><td></td><td></td><td></td></tr><tr><td>6a16b91b2db0a3164f62bfd956530a4206b23fea</td><td>A Method for Real-Time Eye Blink Detection and Its Application +</td></tr><tr><td>6ad107c08ac018bfc6ab31ec92c8a4b234f67d49</td><td></td><td></td><td></td></tr><tr><td>6a184f111d26787703f05ce1507eef5705fdda83</td><td></td><td></td><td></td></tr><tr><td>6a16b91b2db0a3164f62bfd956530a4206b23fea</td><td>A Method for Real-Time Eye Blink Detection and Its Application <br/>Mahidol Wittayanusorn School <br/>Puttamonton, Nakornpatom 73170, Thailand </td><td></td><td>Chinnawat.Deva@gmail.com @@ -3399,6 +4099,10 @@ <br/>rrji@xmu.edu.cn <br/>dmeyer@math.ucsd.edu <br/>jsmith@us.ibm.com +</td></tr><tr><td>6a52e6fce541126ff429f3c6d573bc774f5b8d89</td><td>Role of Facial Emotion in Social Correlation +<br/>Department of Computer Science and Engineering +<br/><b>Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, 466-8555 Japan</b></td><td>('2159044', 'Pankaj Mishra', 'pankaj mishra')<br/>('47865262', 'Takayuki Ito', 'takayuki ito')</td><td>{pankaj.mishra, rafik}@itolab.nitech.ac.jp, +<br/>ito.takayuki@nitech.ac.jp </td></tr><tr><td>6a5fe819d2b72b6ca6565a0de117c2b3be448b02</td><td>Supervised and Projected Sparse Coding for Image Classification <br/>Computer Science and Engineering Department <br/><b>University of Texas at Arlington</b><br/>Arlington,TX,76019 @@ -3429,6 +4133,9 @@ <br/>This Thesis is brought to you for free and open access by the Dietrich College of Humanities and Social Sciences at Research Showcase @ CMU. It has <br/>been accepted for inclusion in Dietrich College Honors Theses by an authorized administrator of Research Showcase @ CMU. For more information, <br/>please contact research-showcase@andrew.cmu.edu. +</td></tr><tr><td>6a4419ce2338ea30a570cf45624741b754fa52cb</td><td>Statistical transformer networks: learning shape +<br/>and appearance models via self supervision +<br/><b>University of York</b></td><td>('39180407', 'Anil Bas', 'anil bas')<br/>('1687021', 'William A. P. Smith', 'william a. p. smith')</td><td>{ab1792,william.smith}@york.ac.uk </td></tr><tr><td>6af65e2a1eba6bd62843e7bf717b4ccc91bce2b8</td><td>A New Weighted Sparse Representation Based <br/>on MSLBP and Its Application to Face Recognition <br/><b>School of IoT Engineering, Jiangnan University, Wuxi 214122, China</b></td><td>('1823451', 'He-Feng Yin', 'he-feng yin')<br/>('37020604', 'Xiao-Jun Wu', 'xiao-jun wu')</td><td>yinhefeng@126.com, wu_xiaojun@yahoo.com.cn @@ -3477,7 +4184,13 @@ <br/>Deep Belief Networks ∗ <br/>Instituto de Sistemas e Rob´otica <br/>Instituto Superior T´ecnico, Portugal -</td><td>('3259175', 'Jacinto C. Nascimento', 'jacinto c. nascimento')</td><td></td></tr><tr><td>6a4ebd91c4d380e21da0efb2dee276897f56467a</td><td>HOG ACTIVE APPEARANCE MODELS +</td><td>('3259175', 'Jacinto C. Nascimento', 'jacinto c. nascimento')</td><td></td></tr><tr><td>6a2ac4f831bd0f67db45e7d3cdaeaaa075e7180a</td><td>Excitation Dropout: +<br/>Encouraging Plasticity in Deep Neural Networks +<br/>1Pattern Analysis & Computer Vision (PAVIS), Istituto Italiano di Tecnologia +<br/><b>Boston University</b><br/>3Adobe Research +<br/><b>University of Verona</b></td><td>('40063519', 'Andrea Zunino', 'andrea zunino')<br/>('3298267', 'Sarah Adel Bargal', 'sarah adel bargal')<br/>('2322579', 'Pietro Morerio', 'pietro morerio')<br/>('1701293', 'Jianming Zhang', 'jianming zhang')<br/>('1749590', 'Stan Sclaroff', 'stan sclaroff')<br/>('1727204', 'Vittorio Murino', 'vittorio murino')</td><td>{andrea.zunino,vittorio.murino}@iit.it, +<br/>{sbargal,sclaroff}@bu.edu, jianmzha@adobe.com +</td></tr><tr><td>6a4ebd91c4d380e21da0efb2dee276897f56467a</td><td>HOG ACTIVE APPEARANCE MODELS <br/><b>cid:2)Imperial College London, U.K</b><br/><b>University of Lincoln, School of Computer Science, U.K</b></td><td>('2788012', 'Epameinondas Antonakos', 'epameinondas antonakos')<br/>('2575567', 'Joan Alabort-i-Medina', 'joan alabort-i-medina')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td></td></tr><tr><td>6a1beb34a2dfcdf36ae3c16811f1aef6e64abff2</td><td></td><td></td><td></td></tr><tr><td>6a7e464464f70afea78552c8386f4d2763ea1d9c</td><td>Review Article <br/>International Journal of Current Engineering and Technology <br/>E-ISSN 2277 – 4106, P-ISSN 2347 - 5161 @@ -3568,7 +4281,9 @@ </td><td>('3469125', 'Congzheng Song', 'congzheng song')<br/>('1723945', 'Vitaly Shmatikov', 'vitaly shmatikov')<br/>('1707461', 'Thomas Ristenpart', 'thomas ristenpart')</td><td>cs2296@cornell.edu <br/>ristenpart@cornell.edu <br/>shmat@cs.cornell.edu -</td></tr><tr><td>324f39fb5673ec2296d90142cf9a909e595d82cf</td><td>Hindawi Publishing Corporation +</td></tr><tr><td>3294e27356c3b1063595885a6d731d625b15505a</td><td>Illumination Face Spaces are Idiosyncratic +<br/>2, H. Kley1, C. Peterson1 ∗ +<br/><b>Colorado State University, Fort Collins, CO 80523, USA</b></td><td>('2640182', 'Jen-Mei Chang', 'jen-mei chang')</td><td></td></tr><tr><td>324f39fb5673ec2296d90142cf9a909e595d82cf</td><td>Hindawi Publishing Corporation <br/>Mathematical Problems in Engineering <br/>Volume 2011, Article ID 864540, 15 pages <br/>doi:10.1155/2011/864540 @@ -3612,7 +4327,10 @@ <br/>Entropy-weighted feature-fusion method <br/>for head-pose estimation <br/>Open Access -</td><td>('40579241', 'Kang Liu', 'kang liu')<br/>('2076553', 'Xu Qian', 'xu qian')</td><td></td></tr><tr><td>32b8c9fd4e3f44c371960eb0074b42515f318ee7</td><td></td><td></td><td></td></tr><tr><td>32575ffa69d85bbc6aef5b21d73e809b37bf376d</td><td>-)5741/ *1-641+ 5)2- 37)16; 1 6-45 . *1-641+ 1.4)61 +</td><td>('40579241', 'Kang Liu', 'kang liu')<br/>('2076553', 'Xu Qian', 'xu qian')</td><td></td></tr><tr><td>3240c9359061edf7a06bfeb7cc20c103a65904c2</td><td>PPR-FCN: Weakly Supervised Visual Relation Detection via Parallel Pairwise +<br/>R-FCN +<br/><b>Columbia University, National University of Singapore</b></td><td>('5462268', 'Hanwang Zhang', 'hanwang zhang')<br/>('26538630', 'Zawlin Kyaw', 'zawlin kyaw')<br/>('46380822', 'Jinyang Yu', 'jinyang yu')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>{hanwangzhang, kzl.zawlin, yjy941124}@gmail.com; shih.fu.chang@columbia.edu +</td></tr><tr><td>32b8c9fd4e3f44c371960eb0074b42515f318ee7</td><td></td><td></td><td></td></tr><tr><td>32575ffa69d85bbc6aef5b21d73e809b37bf376d</td><td>-)5741/ *1-641+ 5)2- 37)16; 1 6-45 . *1-641+ 1.4)61 <br/>7ELAHIEJO B JJ=M= <br/>)*564)+6 <br/>IKHA L=HE=JEI E >EAJHE? I=FA GK=EJO 9A >ACE MEJD @@ -3766,7 +4484,9 @@ <br/>Representation for Face Recognition with <br/>Margin Distribution Optimization <br/><b>Biometric Research Center</b><br/><b>The Hong Kong Polytechnic University</b><br/><b>School of Computer Science and Technology, Tianjin University</b></td><td>('2873638', 'Pengfei Zhu', 'pengfei zhu')<br/>('36685537', 'Lei Zhang', 'lei zhang')<br/>('1688792', 'Qinghua Hu', 'qinghua hu')</td><td>{cspzhu,cslzhang}@comp.polyu.edu.hk -</td></tr><tr><td>350da18d8f7455b0e2920bc4ac228764f8fac292</td><td>From: AAAI Technical Report SS-03-08. Compilation copyright © 2003, AAAI (www.aaai.org). All rights reserved. +</td></tr><tr><td>352d61eb66b053ae5689bd194840fd5d33f0e9c0</td><td>Analysis Dictionary Learning based +<br/>Classification: Structure for Robustness +</td><td>('49501811', 'Wen Tang', 'wen tang')<br/>('1733181', 'Ashkan Panahi', 'ashkan panahi')<br/>('1769928', 'Hamid Krim', 'hamid krim')<br/>('2622498', 'Liyi Dai', 'liyi dai')</td><td></td></tr><tr><td>350da18d8f7455b0e2920bc4ac228764f8fac292</td><td>From: AAAI Technical Report SS-03-08. Compilation copyright © 2003, AAAI (www.aaai.org). All rights reserved. <br/>Automatic Detecting Neutral Face for Face Authentication and <br/>Facial Expression Analysis <br/>Exploratory Computer Vision Group @@ -3791,7 +4511,12 @@ <br/>Unconstrained Still/Video-Based Face Verification with Deep <br/>Convolutional Neural Networks <br/>Received: date / Accepted: date -</td><td>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('2682056', 'Ching-Hui Chen', 'ching-hui chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('26988560', 'Rajeev Ranjan', 'rajeev ranjan')</td><td></td></tr><tr><td>35f03f5cbcc21a9c36c84e858eeb15c5d6722309</td><td>Placing Broadcast News Videos in their Social Media +</td><td>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('2682056', 'Ching-Hui Chen', 'ching-hui chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('26988560', 'Rajeev Ranjan', 'rajeev ranjan')</td><td></td></tr><tr><td>35b1c1f2851e9ac4381ef41b4d980f398f1aad68</td><td>Geometry Guided Convolutional Neural Networks for +<br/>Self-Supervised Video Representation Learning +</td><td>('2551285', 'Chuang Gan', 'chuang gan')<br/>('40206014', 'Boqing Gong', 'boqing gong')<br/>('2473509', 'Kun Liu', 'kun liu')<br/>('49466491', 'Hao Su', 'hao su')<br/>('1744254', 'Leonidas J. Guibas', 'leonidas j. guibas')</td><td></td></tr><tr><td>351c02d4775ae95e04ab1e5dd0c758d2d80c3ddd</td><td>ActionSnapping: Motion-based Video +<br/>Synchronization +<br/>Disney Research +</td><td>('2893744', 'Alexander Sorkine-Hornung', 'alexander sorkine-hornung')</td><td></td></tr><tr><td>35f03f5cbcc21a9c36c84e858eeb15c5d6722309</td><td>Placing Broadcast News Videos in their Social Media <br/>Context using Hashtags <br/><b>Columbia University</b></td><td>('2136860', 'Joseph G. Ellis', 'joseph g. ellis')<br/>('2602265', 'Svebor Karaman', 'svebor karaman')<br/>('1786871', 'Hongzhi Li', 'hongzhi li')<br/>('36009509', 'Hong Bin Shim', 'hong bin shim')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>{jge2105, svebor.karaman, hongzhi.li, h.shim, sc250}@columbia.edu </td></tr><tr><td>35e4b6c20756cd6388a3c0012b58acee14ffa604</td><td>Gender Classification in Large Databases @@ -3846,7 +4571,20 @@ <br/><b>University of Perugia</b><br/>Trento, Italy <br/>Perugia, Italy <br/><b>University of Trento</b><br/>Trento, Italy -</td><td>('2933565', 'Gloria Zen', 'gloria zen')<br/>('1716310', 'Enver Sangineto', 'enver sangineto')<br/>('40811261', 'Elisa Ricci', 'elisa ricci')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td></td></tr><tr><td>353a89c277cca3e3e4e8c6a199ae3442cdad59b5</td><td></td><td></td><td></td></tr><tr><td>35e87e06cf19908855a16ede8c79a0d3d7687b5c</td><td>Strategies for Multi-View Face Recognition for +</td><td>('2933565', 'Gloria Zen', 'gloria zen')<br/>('1716310', 'Enver Sangineto', 'enver sangineto')<br/>('40811261', 'Elisa Ricci', 'elisa ricci')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td></td></tr><tr><td>353a89c277cca3e3e4e8c6a199ae3442cdad59b5</td><td></td><td></td><td></td></tr><tr><td>35e0256b33212ddad2db548484c595334f15b4da</td><td>Attentive Fashion Grammar Network for +<br/>Fashion Landmark Detection and Clothing Category Classification +<br/><b>Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, China</b><br/><b>University of California, Los Angeles, USA</b></td><td>('2693875', 'Wenguan Wang', 'wenguan wang')<br/>('2762640', 'Yuanlu Xu', 'yuanlu xu')<br/>('34926055', 'Jianbing Shen', 'jianbing shen')<br/>('3133970', 'Song-Chun Zhu', 'song-chun zhu')</td><td></td></tr><tr><td>35e6f6e5f4f780508e5f58e87f9efe2b07d8a864</td><td>This paper is a preprint (IEEE accepted status). IEEE copyright notice. 2018 IEEE. +<br/>Personal use of this material is permitted. Permission from IEEE must be obtained for all +<br/><b>other uses, in any current or future media, including reprinting/republishing this material for</b><br/>advertising or promotional purposes, creating new collective works, for resale or redistribu- +<br/>tion to servers or lists, or reuse of any copyrighted. +<br/>A. Tejero-de-Pablos, Y. Nakashima, T. Sato, N. Yokoya, M. Linna and E. Rahtu, ”Sum- +<br/>marization of User-Generated Sports Video by Using Deep Action Recognition Features,” in +<br/>doi: 10.1109/TMM.2018.2794265 +<br/>keywords: Cameras; Feature extraction; Games; Hidden Markov models; Semantics; +<br/>Three-dimensional displays; 3D convolutional neural networks; Sports video summarization; +<br/>action recognition; deep learning; long short-term memory; user-generated video, +<br/>URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8259321&isnumber=4456689 +</td><td></td><td></td></tr><tr><td>35e87e06cf19908855a16ede8c79a0d3d7687b5c</td><td>Strategies for Multi-View Face Recognition for <br/>Identification of Human Faces: A Review <br/>Department of Computer Science <br/>Mahatma Gandhi Shikshan Mandal’s, @@ -3859,7 +4597,10 @@ </td></tr><tr><td>352110778d2cc2e7110f0bf773398812fd905eb1</td><td>TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, JUNE 2014 <br/>Matrix Completion for Weakly-supervised <br/>Multi-label Image Classification -</td><td>('31671904', 'Ricardo Cabral', 'ricardo cabral')<br/>('1683568', 'Fernando De la Torre', 'fernando de la torre')<br/>('2884203', 'Alexandre Bernardino', 'alexandre bernardino')</td><td></td></tr><tr><td>697b0b9630213ca08a1ae1d459fabc13325bdcbb</td><td></td><td></td><td></td></tr><tr><td>69ff40fd5ce7c3e6db95a2b63d763edd8db3a102</td><td>HUMAN AGE ESTIMATION VIA GEOMETRIC AND TEXTURAL +</td><td>('31671904', 'Ricardo Cabral', 'ricardo cabral')<br/>('1683568', 'Fernando De la Torre', 'fernando de la torre')<br/>('2884203', 'Alexandre Bernardino', 'alexandre bernardino')</td><td></td></tr><tr><td>6964af90cf8ac336a2a55800d9c510eccc7ba8e1</td><td>Temporal Relational Reasoning in Videos +<br/>MIT CSAIL +</td><td>('1804424', 'Bolei Zhou', 'bolei zhou')<br/>('50112310', 'Alex Andonian', 'alex andonian')<br/>('1690178', 'Antonio Torralba', 'antonio torralba')</td><td>{bzhou,aandonia,oliva,torralba}@csail.mit.edu +</td></tr><tr><td>697b0b9630213ca08a1ae1d459fabc13325bdcbb</td><td></td><td></td><td></td></tr><tr><td>69ff40fd5ce7c3e6db95a2b63d763edd8db3a102</td><td>HUMAN AGE ESTIMATION VIA GEOMETRIC AND TEXTURAL <br/>FEATURES <br/>Merve KILINC1 and Yusuf Sinan AKGUL2 <br/>1TUBITAK BILGEM UEKAE, Anibal Street, 41470, Gebze, Kocaeli, Turkey @@ -3867,13 +4608,22 @@ <br/>Keywords: <br/>Age estimation:age classification:geometric features:LBP:Gabor:LGBP:cross ratio:FGNET:MORPH </td><td></td><td>mkilinc@uekae.tubitak.gov.tr1, mkilinc@gyte.edu.tr2, akgul@bilmuh.gyte.edu.tr2 -</td></tr><tr><td>69d29012d17cdf0a2e59546ccbbe46fa49afcd68</td><td>Subspace clustering of dimensionality-reduced data +</td></tr><tr><td>69adbfa7b0b886caac15ebe53b89adce390598a3</td><td>Face hallucination using cascaded +<br/>super-resolution and identity priors +<br/><b>University of Ljubljana, Faculty of Electrical Engineering</b><br/><b>University of Notre Dame</b><br/>Fig. 1. Sample face hallucination results generated with the proposed method. +</td><td>('3387470', 'Klemen Grm', 'klemen grm')<br/>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')</td><td></td></tr><tr><td>69d29012d17cdf0a2e59546ccbbe46fa49afcd68</td><td>Subspace clustering of dimensionality-reduced data <br/>ETH Zurich, Switzerland </td><td>('1730683', 'Reinhard Heckel', 'reinhard heckel')<br/>('2208878', 'Michael Tschannen', 'michael tschannen')</td><td>Email: {heckel,boelcskei}@nari.ee.ethz.ch, michaelt@student.ethz.ch </td></tr><tr><td>69a68f9cf874c69e2232f47808016c2736b90c35</td><td>Learning Deep Representation for Imbalanced Classification <br/><b>The Chinese University of Hong Kong</b><br/>2SenseTime Group Limited <br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b></td><td>('2000034', 'Chen Huang', 'chen huang')<br/>('9263285', 'Yining Li', 'yining li')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{chuang,ly015,ccloy,xtang}@ie.cuhk.edu.hk -</td></tr><tr><td>69de532d93ad8099f4d4902c4cad28db958adfea</td><td></td><td></td><td></td></tr><tr><td>69b18d62330711bfd7f01a45f97aaec71e9ea6a5</td><td>RESEARCH ARTICLE +</td></tr><tr><td>69de532d93ad8099f4d4902c4cad28db958adfea</td><td></td><td></td><td></td></tr><tr><td>69a55c30c085ad1b72dd2789b3f699b2f4d3169f</td><td>International Journal of Computer Trends and Technology (IJCTT) – Volume 34 Number 3 - April 2016 +<br/>Automatic Happiness Strength Analysis of a +<br/>Group of People using Facial Expressions +<br/>Sagiri Prasanthi#1, Maddali M.V.M. Kumar*2, +<br/>#1PG Student, #2Assistant Professor +<br/><b>St. Ann s College of Engineering and Technology, Andhra Pradesh, India</b><br/>is a collective concern +</td><td></td><td></td></tr><tr><td>69b18d62330711bfd7f01a45f97aaec71e9ea6a5</td><td>RESEARCH ARTICLE <br/>M-Track: A New Software for Automated <br/>Detection of Grooming Trajectories in Mice <br/><b>State University of New York Polytechnic Institute, Utica, New York</b><br/><b>United States of America, State University of New York Albany, Albany, New York</b><br/><b>United States of America, State University of New York Albany, Albany</b><br/>New York, United States of America @@ -3909,11 +4659,17 @@ <br/>201 Broadway, Cambridge MA <br/>MIT Media Lab <br/>75 Amherst St, Cambridge, MA -</td><td>('1912905', 'Rohit Pandharkar', 'rohit pandharkar')<br/>('1785066', 'Ashok Veeraraghavan', 'ashok veeraraghavan')<br/>('1717566', 'Ramesh Raskar', 'ramesh raskar')</td><td></td></tr><tr><td>69eb6c91788e7c359ddd3500d01fb73433ce2e65</td><td>CAMGRAPH: Distributed Graph Processing for +</td><td>('1912905', 'Rohit Pandharkar', 'rohit pandharkar')<br/>('1785066', 'Ashok Veeraraghavan', 'ashok veeraraghavan')<br/>('1717566', 'Ramesh Raskar', 'ramesh raskar')</td><td></td></tr><tr><td>6993bca2b3471f26f2c8a47adfe444bfc7852484</td><td>The Do’s and Don’ts for CNN-based Face Verification +<br/>Carlos Castillo +<br/><b>University of Maryland, College Park</b><br/>UMIACS +</td><td>('2068427', 'Ankan Bansal', 'ankan bansal')<br/>('48467498', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{ankan,carlos,rranjan1,rama}@umiacs.umd.edu +</td></tr><tr><td>69eb6c91788e7c359ddd3500d01fb73433ce2e65</td><td>CAMGRAPH: Distributed Graph Processing for <br/>Camera Networks <br/><b>College of Computing</b><br/><b>Georgia Institute of Technology</b><br/>Atlanta, GA, USA </td><td>('3427189', 'Steffen Maass', 'steffen maass')<br/>('5540701', 'Kirak Hong', 'kirak hong')<br/>('1751741', 'Umakishore Ramachandran', 'umakishore ramachandran')</td><td>steffen.maass@gatech.edu,khong9@cc.gatech.edu,rama@cc.gatech.edu -</td></tr><tr><td>69063f7e0a60ad6ce16a877bc8f11b59e5f7348e</td><td>Class-Specific Image Deblurring +</td></tr><tr><td>691964c43bfd282f6f4d00b8b0310c554b613e3b</td><td>Temporal Hallucinating for Action Recognition with Few Still Images +<br/>2† +<br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China</b><br/><b>The Chinese University of Hong Kong 3 SenseTime Group Limited</b></td><td>('46696518', 'Lei Zhou', 'lei zhou')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>69063f7e0a60ad6ce16a877bc8f11b59e5f7348e</td><td>Class-Specific Image Deblurring <br/>2, Fatih Porikli1 <br/><b>The Australian National University Canberra ACT 2601, Australia</b><br/>2NICTA, Locked Bag 8001, Canberra ACT 2601, Australia </td><td>('33672969', 'Saeed Anwar', 'saeed anwar')<br/>('1774721', 'Cong Phuoc Huynh', 'cong phuoc huynh')</td><td></td></tr><tr><td>69a9da55bd20ce4b83e1680fbc6be2c976067631</td><td></td><td></td><td></td></tr><tr><td>69c2ac04693d53251500557316c854a625af84ee</td><td>JID: PATREC @@ -4003,7 +4759,33 @@ <br/>enhancing Human Action Recognition <br/>O.V. Ramana Murthy1 and Roland Goecke1,2 <br/><b>Vision and Sensing, HCC Lab, ESTeM, University of Canberra</b><br/><b>IHCC, RSCS, CECS, Australian National University</b></td><td></td><td>Email: O.V.RamanaMurthy@ieee.org, roland.goecke@ieee.org -</td></tr><tr><td>3c78b642289d6a15b0fb8a7010a1fb829beceee2</td><td>Analysis of Facial Dynamics +</td></tr><tr><td>3cb2841302af1fb9656f144abc79d4f3d0b27380</td><td>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/319928941 +<br/>When 3D-Aided 2D Face Recognition Meets Deep +<br/>Learning: An extended UR2D for Pose-Invariant +<br/>Face Recognition +<br/>Article · September 2017 +<br/>CITATIONS +<br/>4 authors: +<br/>READS +<br/>33 +<br/>Xiang Xu +<br/><b>University of Houston</b><br/>Pengfei Dou +<br/><b>University of Houston</b><br/>8 PUBLICATIONS 10 CITATIONS +<br/>9 PUBLICATIONS 29 CITATIONS +<br/>SEE PROFILE +<br/>SEE PROFILE +<br/>Ha Le +<br/><b>University of Houston</b><br/>7 PUBLICATIONS 2 CITATIONS +<br/>Ioannis A Kakadiaris +<br/><b>University of Houston</b><br/>468 PUBLICATIONS 5,233 CITATIONS +<br/>SEE PROFILE +<br/>SEE PROFILE +<br/>Some of the authors of this publication are also working on these related projects: +<br/>3D-Aided 2D Face Recognition View project +<br/>iRay: mobile medical AR View project +<br/>All content following this page was uploaded by Xiang Xu on 27 September 2017. +<br/>The user has requested enhancement of the downloaded file. +</td><td></td><td></td></tr><tr><td>3c78b642289d6a15b0fb8a7010a1fb829beceee2</td><td>Analysis of Facial Dynamics <br/>Using a Tensor Framework <br/><b>University of Bristol</b><br/>Department of Computer Science <br/>Bristol, United Kingdom @@ -4043,7 +4825,18 @@ <br/>M. Correa, J. Ruiz-del-Solar, S. Parra-Tsunekawa, R. Verschae <br/>Department of Electrical Engineering, Universidad de Chile <br/>Advanced Mining Technology Center, Universidad de Chile -</td><td></td><td></td></tr><tr><td>3c03d95084ccbe7bf44b6d54151625c68f6e74d0</td><td></td><td></td><td></td></tr><tr><td>3c57e28a4eb463d532ea2b0b1ba4b426ead8d9a0</td><td>Defeating Image Obfuscation with Deep Learning +</td><td></td><td></td></tr><tr><td>3c563542db664321aa77a9567c1601f425500f94</td><td>TV-GAN: Generative Adversarial Network Based Thermal to Visible Face +<br/>Recognition +<br/><b>The University of Queensland, School of ITEE, QLD 4072, Australia</b></td><td>('50615828', 'Teng Zhang', 'teng zhang')<br/>('2331880', 'Arnold Wiliem', 'arnold wiliem')<br/>('1973322', 'Siqi Yang', 'siqi yang')<br/>('2270092', 'Brian C. Lovell', 'brian c. lovell')</td><td>[patrick.zhang, a.williem, siqi.yang]@uq.edu.au, lovell@itee.uq.edu.au +</td></tr><tr><td>3c03d95084ccbe7bf44b6d54151625c68f6e74d0</td><td></td><td></td><td></td></tr><tr><td>3cd7b15f5647e650db66fbe2ce1852e00c05b2e4</td><td></td><td></td><td></td></tr><tr><td>3c6cac7ecf546556d7c6050f7b693a99cc8a57b3</td><td>Robust Facial Landmark Detection in the Wild +<br/>Submitted for the Degree of +<br/>Doctor of Philosophy +<br/>from the +<br/><b>University of Surrey</b><br/>Centre for Vision, Speech and Signal Processing +<br/>Faculty of Engineering and Physical Sciences +<br/><b>University of Surrey</b><br/>Guildford, Surrey GU2 7XH, U.K. +<br/>January 2016 +</td><td>('37705062', 'Zhenhua Feng', 'zhenhua feng')<br/>('37705062', 'Zhenhua Feng', 'zhenhua feng')</td><td></td></tr><tr><td>3c57e28a4eb463d532ea2b0b1ba4b426ead8d9a0</td><td>Defeating Image Obfuscation with Deep Learning <br/><b>The University of Texas at</b><br/>Austin <br/>Cornell Tech <br/>Cornell Tech @@ -4066,7 +4859,16 @@ <br/>Amherst MA 01003 </td><td>('40175280', 'Huaizu Jiang', 'huaizu jiang')</td><td>hzjiang@cs.umass.edu <br/>elm@cs.umass.edu -</td></tr><tr><td>3ce2ecf3d6ace8d80303daf67345be6ec33b3a93</td><td></td><td></td><td></td></tr><tr><td>3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8</td><td>Measuring Gaze Orientation for Human-Robot +</td></tr><tr><td>3ce2ecf3d6ace8d80303daf67345be6ec33b3a93</td><td></td><td></td><td></td></tr><tr><td>3c1aef7c2d32a219bdbc89a44d158bc2695e360a</td><td>Adversarial Attack Type I: Generating False Positives +<br/><b>Shanghai Jiao Tong University</b><br/>Shanghai, P.R. China 200240 +<br/><b>Shanghai Jiao Tong University</b><br/>Shanghai, P.R. China 200240 +<br/><b>Shanghai Jiao Tong University</b><br/>Shanghai, P.R. China 200240 +<br/><b>Shanghai Jiao Tong University</b><br/>Shanghai, P.R. China 200240 +</td><td>('51428687', 'Sanli Tang', 'sanli tang')<br/>('13858459', 'Mingjian Chen', 'mingjian chen')<br/>('2182657', 'Xiaolin Huang', 'xiaolin huang')<br/>('1688428', 'Jie Yang', 'jie yang')</td><td>tangsanli@sjtu.edu.cn +<br/>w179261466@sjtu.edu.cn +<br/>xiaolinhuang@sjtu.edu.cn +<br/>jieyang@sjtu.edu.cn +</td></tr><tr><td>3c374cb8e730b64dacb9fbf6eb67f5987c7de3c8</td><td>Measuring Gaze Orientation for Human-Robot <br/>Interaction <br/>∗ CNRS; LAAS; 7 avenue du Colonel Roche, 31077 Toulouse Cedex, France <br/>† Universit´e de Toulouse; UPS; LAAS-CNRS : F-31077 Toulouse, France @@ -4135,7 +4937,9 @@ <br/>TR4 8UN, UK. <br/><b>Moscow Institute of Physics and Technology, Institutskiy per., 9, Dolgoprudny, 141701, Russia</b></td><td>('3888942', 'Konstantin Chekanov', 'konstantin chekanov')<br/>('4017984', 'Polina Mamoshina', 'polina mamoshina')<br/>('1976753', 'Roman V. Yampolskiy', 'roman v. yampolskiy')<br/>('1732855', 'Radu Timofte', 'radu timofte')<br/>('40336662', 'Alex Zhavoronkov', 'alex zhavoronkov')</td><td>Morten Scheibye-Knudsen: mscheibye@sund.ku.dk <br/>Alex Zhavoronkov: alex@biogerontology.org -</td></tr><tr><td>3cc46bf79fb9225cf308815c7d41c8dd5625cc29</td><td>AGE INTERVAL AND GENDER PREDICTION USING PARAFAC2 APPLIED TO SPEECH +</td></tr><tr><td>3c56acaa819f4e2263638b67cea1ec37a226691d</td><td>Body Joint guided 3D Deep Convolutional +<br/>Descriptors for Action Recognition +</td><td>('3201156', 'Congqi Cao', 'congqi cao')<br/>('46867228', 'Yifan Zhang', 'yifan zhang')<br/>('1713887', 'Chunjie Zhang', 'chunjie zhang')<br/>('1694235', 'Hanqing Lu', 'hanqing lu')</td><td></td></tr><tr><td>3cc46bf79fb9225cf308815c7d41c8dd5625cc29</td><td>AGE INTERVAL AND GENDER PREDICTION USING PARAFAC2 APPLIED TO SPEECH <br/>UTTERANCES <br/><b>Aristotle University of Thessaloniki</b><br/>Thessaloniki 54124, GREECE <br/><b>Cyprus University of Technology</b><br/>3040 Limassol, Cyprus @@ -4184,7 +4988,12 @@ </td></tr><tr><td>56359d2b4508cc267d185c1d6d310a1c4c2cc8c2</td><td>Shape Driven Kernel Adaptation in <br/>Convolutional Neural Network for Robust Facial Trait Recognition <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), -<br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, 100190, China</b><br/><b>National University of Singapore, Singapore</b></td><td>('1688086', 'Shaoxin Li', 'shaoxin li')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('1773437', 'Zhiheng Niu', 'zhiheng niu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>56e6f472090030a6f172a3e2f46ef9daf6cad757</td><td>Asian Face Image Database PF01 +<br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, 100190, China</b><br/><b>National University of Singapore, Singapore</b></td><td>('1688086', 'Shaoxin Li', 'shaoxin li')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('1773437', 'Zhiheng Niu', 'zhiheng niu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>56e079f4eb40744728fd1d7665938b06426338e5</td><td>Bayesian Approaches to Distribution Regression +<br/><b>University of Oxford</b><br/><b>University College London</b><br/><b>University of Oxford</b><br/><b>Imperial College London</b></td><td>('35142231', 'Ho Chung Leon Law', 'ho chung leon law')<br/>('36326783', 'Dougal J. Sutherland', 'dougal j. sutherland')<br/>('1698032', 'Dino Sejdinovic', 'dino sejdinovic')<br/>('2127497', 'Seth Flaxman', 'seth flaxman')</td><td>ho.law@spc.ox.ac.uk +<br/>dougal@gmail.com +<br/>dino.sejdinovic@stats.ox.ac.uk +<br/>s.flaxman@imperial.ac.uk +</td></tr><tr><td>56e6f472090030a6f172a3e2f46ef9daf6cad757</td><td>Asian Face Image Database PF01 <br/>Intelligent Multimedia Lab. <br/>†Department of Computer Science and Engineering <br/><b>Pohang University of Science and Technology</b><br/>San 31, Hyoja-Dong, Nam-Gu, Pohang, 790-784, Korea @@ -4239,10 +5048,16 @@ <br/>Concepts Not Alone: Exploring Pairwise Relationships <br/>for Zero-Shot Video Activity Recognition <br/><b>IIIS, Tsinghua University, Beijing, China</b><br/><b>QCIS, University of Technology Sydney, Sydney, Australia</b><br/><b>DCMandB, University of Michigan, Ann Arbor, USA 4 SCS, Carnegie Mellon University, Pittsburgh, USA</b></td><td>('2551285', 'Chuang Gan', 'chuang gan')<br/>('2735055', 'Ming Lin', 'ming lin')<br/>('39033919', 'Yi Yang', 'yi yang')<br/>('1732213', 'Gerard de Melo', 'gerard de melo')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')</td><td></td></tr><tr><td>560e0e58d0059259ddf86fcec1fa7975dee6a868</td><td>Face Recognition in Unconstrained Videos with Matched Background Similarity -<br/><b>The Blavatnik School of Computer Science, Tel-Aviv University, Israel</b><br/><b>Computer Science Division, The Open University of Israel</b></td><td>('1776343', 'Lior Wolf', 'lior wolf')<br/>('3352629', 'Itay Maoz', 'itay maoz')</td><td></td></tr><tr><td>566038a3c2867894a08125efe41ef0a40824a090</td><td>978-1-4244-2354-5/09/$25.00 ©2009 IEEE +<br/><b>The Blavatnik School of Computer Science, Tel-Aviv University, Israel</b><br/><b>Computer Science Division, The Open University of Israel</b></td><td>('1776343', 'Lior Wolf', 'lior wolf')<br/>('3352629', 'Itay Maoz', 'itay maoz')</td><td></td></tr><tr><td>56a677c889e0e2c9f68ab8ca42a7e63acf986229</td><td>Mining Spatial and Spatio-Temporal ROIs for Action Recognition +<br/>Jiang Wang2 Alan Yuille1,3 +<br/><b>University of California, Los Angeles</b><br/><b>Baidu Research, USA 3John Hopkins University</b></td><td>('5964529', 'Xiaochen Lian', 'xiaochen lian')</td><td>{lianxiaochen@,yuille@stat.}ucla.edu +<br/>{chenzhuoyuan,yangyi05,wangjiang03}@baidu.com +</td></tr><tr><td>566038a3c2867894a08125efe41ef0a40824a090</td><td>978-1-4244-2354-5/09/$25.00 ©2009 IEEE <br/>1945 <br/>ICASSP 2009 -</td><td></td><td></td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>Distance Estimation of an Unknown Person +</td><td></td><td></td></tr><tr><td>56dca23481de9119aa21f9044efd7db09f618704</td><td>Riemannian Dictionary Learning and Sparse +<br/>Coding for Positive Definite Matrices +</td><td>('2691929', 'Anoop Cherian', 'anoop cherian')<br/>('3072326', 'Suvrit Sra', 'suvrit sra')</td><td></td></tr><tr><td>56ae6d94fc6097ec4ca861f0daa87941d1c10b70</td><td>Distance Estimation of an Unknown Person <br/>from a Portrait <br/>1 Technicolor - Cesson S´evign´e, France <br/><b>California Institute of Technology, Pasadena, CA, USA</b></td><td>('2232848', 'Xavier P. Burgos-Artizzu', 'xavier p. burgos-artizzu')<br/>('3339867', 'Matteo Ruggero Ronchi', 'matteo ruggero ronchi')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>xavier.burgos@technicolor.com, {mronchi,perona}@caltech.edu @@ -4257,7 +5072,12 @@ </td><td>('1708679', 'Yun Fu', 'yun fu')<br/>('37575012', 'Liangliang Cao', 'liangliang cao')<br/>('1822413', 'Guodong Guo', 'guodong guo')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>{yunfu2,cao4}@uiuc.edu <br/>gdguo@nccu.edu <br/>huang@ifp.uiuc.edu -</td></tr><tr><td>512befa10b9b704c9368c2fbffe0dc3efb1ba1bf</td><td>Evidence and a Computational Explanation of Cultural Differences in +</td></tr><tr><td>516a27d5dd06622f872f5ef334313350745eadc3</td><td>> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < +<br/>1 +<br/>Fine-Grained Facial Expression Analysis Us- +<br/>ing Dimensional Emotion Model +<br/> +</td><td>('41179750', 'Feng Zhou', 'feng zhou')<br/>('34362536', 'Shu Kong', 'shu kong')<br/>('3157443', 'Charless C. Fowlkes', 'charless c. fowlkes')<br/>('29889388', 'Tao Chen', 'tao chen')<br/>('40216538', 'Baiying Lei', 'baiying lei')</td><td></td></tr><tr><td>512befa10b9b704c9368c2fbffe0dc3efb1ba1bf</td><td>Evidence and a Computational Explanation of Cultural Differences in <br/>Facial Expression Recognition <br/>Matthew N. Dailey <br/>Computer Science and Information Management @@ -4330,7 +5150,9 @@ </td><td>('2635321', 'Josiah Wang', 'josiah wang')<br/>('1686341', 'Katja Markert', 'katja markert')<br/>('3056091', 'Mark Everingham', 'mark everingham')</td><td>scs6jwks@comp.leeds.ac.uk <br/>markert@comp.leeds.ac.uk <br/>me@comp.leeds.ac.uk -</td></tr><tr><td>51c7c5dfda47647aef2797ac3103cf0e108fdfb4</td><td>CS 395T: Celebrity Look-Alikes ∗ +</td></tr><tr><td>5180df9d5eb26283fb737f491623395304d57497</td><td>Scalable Angular Discriminative Deep Metric Learning +<br/>for Face Recognition +<br/><b>aCenter for Combinatorics, Nankai University, Tianjin 300071, China</b><br/><b>bCenter for Applied Mathematics, Tianjin University, Tianjin 300072, China</b></td><td>('2143751', 'Bowen Wu', 'bowen wu')</td><td></td></tr><tr><td>51c7c5dfda47647aef2797ac3103cf0e108fdfb4</td><td>CS 395T: Celebrity Look-Alikes ∗ </td><td>('2362854', 'Adrian Quark', 'adrian quark')</td><td>quark@mail.utexas.edu </td></tr><tr><td>519f4eb5fe15a25a46f1a49e2632b12a3b18c94d</td><td>Non-Lambertian Reflectance Modeling and <br/>Shape Recovery of Faces using Tensor Splines @@ -4362,14 +5184,27 @@ <br/>Fernando De la Torre, Co-chair <br/>Submitted in partial fulfillment of the requirements <br/>for the degree of Doctor of Philosophy in Robotics. -</td><td>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('1820249', 'Simon Lucey', 'simon lucey')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')<br/>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')<br/>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')</td><td></td></tr><tr><td>51cc78bc719d7ff2956b645e2fb61bab59843d2b</td><td>Face and Facial Expression Recognition with an +</td><td>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('1820249', 'Simon Lucey', 'simon lucey')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')<br/>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')<br/>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')</td><td></td></tr><tr><td>51faacfa4fb1e6aa252c6970e85ff35c5719f4ff</td><td>Zoom-Net: Mining Deep Feature Interactions for +<br/>Visual Relationship Recognition +<br/><b>University of Science and Technology of China, Key Laboratory of Electromagnetic</b><br/>Space Information, the Chinese Academy of Sciences, 2SenseTime Group Limited, +<br/><b>CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong</b><br/><b>SenseTime-NTU Joint AI Research Centre, Nanyang Technological University</b></td><td>('4332039', 'Guojun Yin', 'guojun yin')<br/>('37145669', 'Lu Sheng', 'lu sheng')<br/>('50677886', 'Bin Liu', 'bin liu')<br/>('1708598', 'Nenghai Yu', 'nenghai yu')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('49895575', 'Jing Shao', 'jing shao')<br/>('1717179', 'Chen Change Loy', 'chen change loy')</td><td>gjyin@mail.ustc.edu.cn, {flowice,ynh}@ustc.edu.cn, ccloy@ieee.org, +<br/>{lsheng,xgwang}@ee.cuhk.edu.hk, shaojing@sensetime.com +</td></tr><tr><td>51cc78bc719d7ff2956b645e2fb61bab59843d2b</td><td>Face and Facial Expression Recognition with an <br/>Embedded System for Human-Robot Interaction <br/><b>School of Computer Engineering, Sejong University, Seoul, Korea</b></td><td>('2241562', 'Yang-Bok Lee', 'yang-bok lee')<br/>('2706430', 'Yong-Guk Kim', 'yong-guk kim')</td><td>*ykim@sejong.ac.kr </td></tr><tr><td>511b06c26b0628175c66ab70dd4c1a4c0c19aee9</td><td>International Journal of Engineering Research and General ScienceVolume 2, Issue 5, August – September 2014 <br/>ISSN 2091-2730 <br/>Face Recognition using Laplace Beltrami Operator by Optimal Linear <br/>Approximations -<br/><b>Institute of Engineering and Technology, Alwar, Rajasthan Technical University, Kota(Raj</b><br/><b>Research Scholar (M.Tech, IT), Institute of Engineering and Technology</b></td><td></td><td></td></tr><tr><td>51528cdce7a92835657c0a616c0806594de7513b</td><td></td><td></td><td></td></tr><tr><td>514a74aefb0b6a71933013155bcde7308cad2b46</td><td><b>CARNEGIE MELLON UNIVERSITY</b><br/>OPTIMAL CLASSIFIER ENSEMBLES +<br/><b>Institute of Engineering and Technology, Alwar, Rajasthan Technical University, Kota(Raj</b><br/><b>Research Scholar (M.Tech, IT), Institute of Engineering and Technology</b></td><td></td><td></td></tr><tr><td>51528cdce7a92835657c0a616c0806594de7513b</td><td></td><td></td><td></td></tr><tr><td>51cb09ee04831b95ae02e1bee9b451f8ac4526e3</td><td>Beyond Short Snippets: Deep Networks for Video Classification +<br/>Matthew Hausknecht2 +<br/><b>University of Maryland, College Park</b><br/><b>University of Texas at Austin</b><br/><b>Google, Inc</b></td><td>('2340579', 'Joe Yue-Hei Ng', 'joe yue-hei ng')<br/>('1689108', 'Oriol Vinyals', 'oriol vinyals')<br/>('3089272', 'Rajat Monga', 'rajat monga')<br/>('2259154', 'Sudheendra Vijayanarasimhan', 'sudheendra vijayanarasimhan')<br/>('1805076', 'George Toderici', 'george toderici')</td><td>yhng@umiacs.umd.edu +<br/>mhauskn@cs.utexas.edu +<br/>svnaras@google.com +<br/>vinyals@google.com +<br/>rajatmonga@google.com +<br/>gtoderici@google.com +</td></tr><tr><td>514a74aefb0b6a71933013155bcde7308cad2b46</td><td><b>CARNEGIE MELLON UNIVERSITY</b><br/>OPTIMAL CLASSIFIER ENSEMBLES <br/>FOR IMPROVED BIOMETRIC VERIFICATION <br/>A Dissertation <br/>Submitted to the Faculty of Graduate School @@ -4466,9 +5301,17 @@ <br/>Manuscript received 23 June 2002; revised 27 January 2003 <br/>Communicated by Ladislav Hluch´y </td><td>('2366162', 'Yongzhong Lu', 'yongzhong lu')<br/>('1711876', 'Jingli Zhou', 'jingli zhou')<br/>('1714618', 'Shengsheng Yu', 'shengsheng yu')</td><td>e-mail: luyongz0@sohu.com -</td></tr><tr><td>5121f42de7cb9e41f93646e087df82b573b23311</td><td>CLASSIFYING ONLINE DATING PROFILES ON TINDER USING FACENET FACIAL +</td></tr><tr><td>5161e38e4ea716dcfb554ccb88901b3d97778f64</td><td>SSPP-DAN: DEEP DOMAIN ADAPTATION NETWORK FOR +<br/>FACE RECOGNITION WITH SINGLE SAMPLE PER PERSON +<br/>School of Computing, KAIST, Republic of Korea +</td><td>('2487892', 'Sungeun Hong', 'sungeun hong')<br/>('40506942', 'Woobin Im', 'woobin im')</td><td></td></tr><tr><td>5121f42de7cb9e41f93646e087df82b573b23311</td><td>CLASSIFYING ONLINE DATING PROFILES ON TINDER USING FACENET FACIAL <br/>EMBEDDINGS <br/><b>FL</b></td><td></td><td>Charles F. Jekel (cjekel@ufl.edu; cj@jekel.me) and Raphael T. Haftka +</td></tr><tr><td>51d1a6e15936727e8dd487ac7b7fd39bd2baf5ee</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>A Fast and Accurate System for Face Detection, +<br/>Identification, and Verification +</td><td>('48467498', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('2068427', 'Ankan Bansal', 'ankan bansal')<br/>('7674316', 'Jingxiao Zheng', 'jingxiao zheng')<br/>('2680836', 'Hongyu Xu', 'hongyu xu')<br/>('35199438', 'Joshua Gleason', 'joshua gleason')<br/>('2927406', 'Boyu Lu', 'boyu lu')<br/>('8435884', 'Anirudh Nanduri', 'anirudh nanduri')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>5141cf2e59fb2ec9bb489b9c1832447d3cd93110</td><td>Learning Person Trajectory Representations for Team Activity Analysis +<br/><b>Simon Fraser University</b></td><td>('10386960', 'Nazanin Mehrasa', 'nazanin mehrasa')<br/>('19198359', 'Yatao Zhong', 'yatao zhong')<br/>('2123865', 'Frederick Tung', 'frederick tung')<br/>('3004771', 'Luke Bornn', 'luke bornn')<br/>('10771328', 'Greg Mori', 'greg mori')</td><td>{nmehrasa, yataoz, ftung, lbornn}@sfu.ca, mori@cs.sfu.ca </td></tr><tr><td>5185f2a40836a754baaa7419a1abdd1e7ffaf2ad</td><td>A Multimodality Framework for Creating Speaker/Non-Speaker Profile <br/>Databases for Real-World Video <br/><b>Beckman Institute</b><br/><b>University of Illinois</b><br/>Urbana, IL 61801 @@ -4477,18 +5320,101 @@ </td><td>('3082579', 'Jehanzeb Abbas', 'jehanzeb abbas')<br/>('1804874', 'Charlie K. Dagli', 'charlie k. dagli')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>jabbas2@ifp.uiuc.edu <br/>dagli@ifp.uiuc.edu <br/>huang@ifp.uiuc.edu -</td></tr><tr><td>5160569ca88171d5fa257582d161e9063c8f898d</td><td>Local Binary Patterns as an Image Preprocessing for Face Authentication +</td></tr><tr><td>511a8cdf2127ef8aa07cbdf9660fe9e0e2dfbde7</td><td>Hindawi +<br/>Computational Intelligence and Neuroscience +<br/>Volume 2018, Article ID 4512473, 10 pages +<br/>https://doi.org/10.1155/2018/4512473 +<br/>Research Article +<br/>A Community Detection Approach to Cleaning Extremely +<br/>Large Face Database +<br/><b>Computer School, University of South China, Hengyang, China</b><br/><b>National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, China</b><br/>Received 11 December 2017; Accepted 12 March 2018; Published 22 April 2018 +<br/>Academic Editor: Amparo Alonso-Betanzos +<br/>permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +<br/>Though it has been easier to build large face datasets by collecting images from the Internet in this Big Data era, the time-consuming +<br/>manual annotation process prevents researchers from constructing larger ones, which makes the automatic cleaning of noisy labels +<br/>highly desirable. However, identifying mislabeled faces by machine is quite challenging because the diversity of a person’s face +<br/>images that are captured wildly at all ages is extraordinarily rich. In view of this, we propose a graph-based cleaning method that +<br/>mainly employs the community detection algorithm and deep CNN models to delete mislabeled images. As the diversity of faces is +<br/>preserved in multiple large communities, our cleaning results have both high cleanness and rich data diversity. With our method, we +<br/>clean the extremely large MS-Celeb-1M face dataset (approximately 10 million images with noisy labels) and obtain a clean version +<br/>of it called C-MS-Celeb (6,464,018 images of 94,682 celebrities). By training a single-net model using our C-MS-Celeb dataset, +<br/>without fine-tuning, we achieve 99.67% at Equal Error Rate on the LFW face recognition benchmark, which is comparable to other +<br/>state-of-the-art results. This demonstrates the data cleaning positive effects on the model training. To the best of our knowledge, +<br/>our C-MS-Celeb is the largest clean face dataset that is publicly available so far, which will benefit face recognition researchers. +<br/>1. Introduction +<br/>In the last few years, researchers have witnessed the remark- +<br/>able progress in face recognition due to the significant success +<br/>of deep convolutional neural networks [1] and the emergence +<br/>of large scale face datasets [2]. Although the data explosion +<br/>has made it easier to build datasets by collecting real world +<br/>images from the Internet [3], constructing a large scale face +<br/>dataset remains a highly time-consuming and costly task +<br/>because the mislabeled images returned by search engines +<br/>need to be manually removed [4]. Thus, automatic cleaning +<br/>of noisy labels in the raw dataset is strongly desirable. +<br/>However, identifying mislabeled faces automatically by +<br/>machine is by no means easy. The main reason for this is that, +<br/>for faces that are captured wildly, the variation of a man’s faces +<br/>can be so large that some of his images may easily be identified +<br/>as someone else’s [5]. Thus, a machine may be misled by this +<br/>rich data diversity within one person and delete correctly +<br/>labeled images. For example, if old faces of a man are the +<br/>majority in the dataset, a young face of him may be regarded +<br/>as someone else and removed. Another challenge is that, due +<br/>to the ambiguity of people’s names, searching for someone’s +<br/>pictures online usually returns images from multiple people +<br/>[2], which requires the cleaning method to be tolerant to the +<br/>high proportion of noisy labels in the raw dataset constructed +<br/>by online searching. +<br/>In order to clean noisy labels and meanwhile preserve +<br/>the rich data diversity of various faces, we propose a three- +<br/>stage graph-based method to clean large face datasets using +<br/>the community detection algorithm. For each image in the +<br/>raw dataset, we firstly use pretrained deep CNN models to +<br/>align the face and extract a feature vector to represent each +<br/>face. Secondly, for features of the same identity, based on the +<br/>cosine similarity between different features, we construct an +<br/>undirected graph, named “face similarity graph,” to quantify +<br/>the similarity between different images. After deleting weak +<br/>edges and applying the community detection algorithm, we +<br/>delete mislabeled images by removing minor communities. In +<br/>the last stage, we try to relabel each previously deleted image +</td><td>('3335298', 'Chi Jin', 'chi jin')<br/>('9856301', 'Ruochun Jin', 'ruochun jin')<br/>('38536592', 'Kai Chen', 'kai chen')<br/>('1791001', 'Yong Dou', 'yong dou')<br/>('3335298', 'Chi Jin', 'chi jin')</td><td>Correspondence should be addressed to Ruochun Jin; sczjrc@163.com +</td></tr><tr><td>51d048b92f6680aca4a8adf07deb380c0916c808</td><td>This is the accepted version of the following article: "State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications", +<br/>which has been published in final form at http://onlinelibrary.wiley.com. This article may be used for non-commercial purposes in accordance +<br/>with the Wiley Self-Archiving Policy [http://olabout.wiley.com/WileyCDA/Section/id-820227.html]. +<br/>EUROGRAPHICS 2018 +<br/>K. Hildebrandt and C. Theobalt +<br/>(Guest Editors) +<br/>Volume 37 (2018), Number 2 +<br/>STAR – State of The Art Report +<br/>State of the Art on Monocular 3D Face +<br/>Reconstruction, Tracking, and Applications +<br/>M. Zollhöfer1,2 +<br/>J. Thies3 P. Garrido1,5 D. Bradley4 T. Beeler4 P. Pérez5 M. Stamminger6 M. Nießner3 C. Theobalt1 +<br/><b>Max Planck Institute for Informatics</b><br/><b>Stanford University</b><br/><b>Technical University of Munich</b><br/>4Disney Research +<br/>5Technicolor +<br/><b>University of Erlangen-Nuremberg</b><br/>Figure 1: This state-of-the-art report provides an overview of monocular 3D face reconstruction and tracking, and highlights applications. +</td><td></td><td></td></tr><tr><td>5134353bd01c4ea36bd007c460e8972b1541d0ad</td><td>Face Recognition with Multi-Resolution Spectral Feature +<br/>Images +<br/><b>School of Electrical Engineering and Automation, Anhui University, Hefei, China, Hong Kong Polytechnic</b><br/><b>University, Hong Kong, China, 3 Center for Intelligent Electricity Networks, University of Newcastle, Newcastle, Australia, 4 School of Electrical and Electronic Engineering</b><br/><b>Nanyang Technological University, Singapore, Singapore</b></td><td>('31443079', 'Zhan-Li Sun', 'zhan-li sun')<br/>('1703078', 'Kin-Man Lam', 'kin-man lam')<br/>('50067626', 'Zhao-yang Dong', 'zhao-yang dong')<br/>('40465036', 'Han Wang', 'han wang')<br/>('29927490', 'Qing-wei Gao', 'qing-wei gao')</td><td></td></tr><tr><td>5160569ca88171d5fa257582d161e9063c8f898d</td><td>Local Binary Patterns as an Image Preprocessing for Face Authentication <br/><b>IDIAP Research Institute, Martigny, Switzerland</b><br/>Ecole Polytechnique F´ed´erale de Lausanne (EPFL), Switzerland </td><td>('16602458', 'Guillaume Heusch', 'guillaume heusch')<br/>('2820403', 'Yann Rodriguez', 'yann rodriguez')</td><td>fheusch, rodrig, marcelg@idiap.ch </td></tr><tr><td>5157dde17a69f12c51186ffc20a0a6c6847f1a29</td><td>Evolutionary Cost-sensitive Extreme Learning <br/>Machine <br/>1 -</td><td>('40613723', 'Lei Zhang', 'lei zhang')<br/>('1698371', 'David Zhang', 'david zhang')</td><td></td></tr><tr><td>51dc127f29d1bb076d97f515dca4cc42dda3d25b</td><td></td><td></td><td></td></tr><tr><td>3d143cfab13ecd9c485f19d988242e7240660c86</td><td>Discriminative Collaborative Representation for +</td><td>('40613723', 'Lei Zhang', 'lei zhang')<br/>('1698371', 'David Zhang', 'david zhang')</td><td></td></tr><tr><td>51dc127f29d1bb076d97f515dca4cc42dda3d25b</td><td></td><td></td><td></td></tr><tr><td>3d18ce183b5a5b4dcaa1216e30b774ef49eaa46f</td><td>Face Alignment Across Large Poses: A 3D Solution +<br/>Hailin Shi1 +<br/><b>Institute of Automation, Chinese Academy of Sciences</b><br/><b>Michigan State University</b></td><td>('8362374', 'Xiangyu Zhu', 'xiangyu zhu')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{xiangyu.zhu,zlei,hailin.shi,szli}@nlpr.ia.ac.cn +<br/>liuxm@msu.edu +</td></tr><tr><td>3d143cfab13ecd9c485f19d988242e7240660c86</td><td>Discriminative Collaborative Representation for <br/>Classification <br/><b>Academic Center for Computing and Media Studies, Kyoto University, Kyoto 606-8501, Japan</b><br/><b>Institute of Scienti c and Industrial Research, Osaka University, Ibaraki-shi 567-0047, Japan</b><br/>3 OMRON Social Solutions Co., LTD, Kyoto 619-0283, Japan </td><td>('2549020', 'Yang Wu', 'yang wu')<br/>('40400215', 'Wei Li', 'wei li')<br/>('1707934', 'Masayuki Mukunoki', 'masayuki mukunoki')<br/>('1681266', 'Michihiko Minoh', 'michihiko minoh')<br/>('1710195', 'Shihong Lao', 'shihong lao')</td><td>yangwu@mm.media.kyoto-u.ac.jp,seuliwei@126.com, <br/>{minoh,mukunoki}@media.kyoto-u.ac.jp,lao_shihong@oss.omron.co.jp -</td></tr><tr><td>3dabf7d853769cfc4986aec443cc8b6699136ed0</td><td>In A. Esposito, N. Bourbakis, N. Avouris, and I. Hatzilygeroudis. (Eds.) Lecture Notes in +</td></tr><tr><td>3daafe6389d877fe15d8823cdf5ac15fd919676f</td><td>Human Action Localization +<br/>with Sparse Spatial Supervision +</td><td>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')<br/>('49142153', 'Xavier Martin', 'xavier martin')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>3dabf7d853769cfc4986aec443cc8b6699136ed0</td><td>In A. Esposito, N. Bourbakis, N. Avouris, and I. Hatzilygeroudis. (Eds.) Lecture Notes in <br/>Computer Science, Vol 5042: Verbal and Nonverbal Features of Human-human and Human- <br/>machine Interaction, Springer Verlag, p. 1-21. <br/>Data mining spontaneous facial behavior with @@ -4560,7 +5486,7 @@ <br/><b>Center for Arti cial Vision Research, Korea University</b><br/>Anam-dong, Seongbuk-ku, Seoul 136-713, Korea </td><td>('2348968', 'Sang-Woong Lee', 'sang-woong lee')<br/>('1703007', 'Seong-Whan Lee', 'seong-whan lee')</td><td>rhiephil@cs.cmu.edu <br/>swlee@image.korea.ac.kr -</td></tr><tr><td>3d0c21d4780489bd624a74b07e28c16175df6355</td><td>Deep or Shallow Facial Descriptors? A Case for +</td></tr><tr><td>3d6ee995bc2f3e0f217c053368df659a5d14d5b5</td><td></td><td></td><td></td></tr><tr><td>3d0c21d4780489bd624a74b07e28c16175df6355</td><td>Deep or Shallow Facial Descriptors? A Case for <br/>Facial Attribute Classification and Face Retrieval <br/>1 Faculty of Engineering, <br/><b>Multimedia University, Cyberjaya, Malaysia</b><br/>2 Faculty of Computing & Informatics, @@ -4600,7 +5526,11 @@ <br/>Revised: February 2010 <br/><b>A Thesis submitted to McGill University in partial fulfillment of the requirements for the</b><br/>degree of Master of Engineering <br/>i -</td><td>('2376514', 'Malika Meghjani', 'malika meghjani')<br/>('2376514', 'Malika Meghjani', 'malika meghjani')</td><td></td></tr><tr><td>3d1af6c531ebcb4321607bcef8d9dc6aa9f0dc5a</td><td>1892 +</td><td>('2376514', 'Malika Meghjani', 'malika meghjani')<br/>('2376514', 'Malika Meghjani', 'malika meghjani')</td><td></td></tr><tr><td>3dfb822e16328e0f98a47209d7ecd242e4211f82</td><td>Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in +<br/>Unconstrained Environments +<br/><b>Beijing University of Posts and Telecommunications</b><br/>Beijing 100876,China +</td><td>('15523767', 'Tianyue Zheng', 'tianyue zheng')<br/>('1774956', 'Weihong Deng', 'weihong deng')<br/>('23224233', 'Jiani Hu', 'jiani hu')</td><td>2231135739@qq.com, whdeng@bupt.edu.cn, 40902063@qq.com +</td></tr><tr><td>3d1af6c531ebcb4321607bcef8d9dc6aa9f0dc5a</td><td>1892 <br/>Random Multispace Quantization as <br/>an Analytic Mechanism for BioHashing <br/>of Biometric and Random Identity Inputs @@ -4675,6 +5605,14 @@ <br/>Frontiers in ICT | www.frontiersin.org <br/>June 2016 | Volume 3 | Article 11 </td><td>('30772945', 'Chunfeng Liu', 'chunfeng liu')<br/>('1742162', 'Rafael A. Calvo', 'rafael a. calvo')<br/>('36807976', 'Renee Lim', 'renee lim')<br/>('1742162', 'Rafael A. Calvo', 'rafael a. calvo')</td><td>rafael.calvo@sydney.edu.au +</td></tr><tr><td>580f86f1ace1feed16b592d05c2b07f26c429b4b</td><td>Dense-Captioning Events in Videos +<br/><b>Stanford University</b></td><td>('2580593', 'Ranjay Krishna', 'ranjay krishna')<br/>('35163655', 'Kenji Hata', 'kenji hata')<br/>('3260219', 'Frederic Ren', 'frederic ren')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')</td><td>{ranjaykrishna, kenjihata, fren, feifeili, jniebles}@cs.stanford.edu +</td></tr><tr><td>58d47c187b38b8a2bad319c789a09781073d052d</td><td>Factorizable Net: An Efficient Subgraph-based +<br/>Framework for Scene Graph Generation +<br/><b>The Chinese University of Hong Kong, Hong Kong SAR, China</b><br/><b>The University of Sydney, SenseTime Computer Vision Research Group</b><br/>3 MIT CSAIL, USA +<br/>4 Sensetime Ltd, Beijing, China +<br/><b>Samsung Telecommunication Research Institute, Beijing, China</b></td><td>('2180892', 'Yikang Li', 'yikang li')<br/>('3001348', 'Wanli Ouyang', 'wanli ouyang')<br/>('1804424', 'Bolei Zhou', 'bolei zhou')<br/>('1788070', 'Jianping Shi', 'jianping shi')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')</td><td>{ykli, xgwang}@ee.cuhk.edu.hk, wanli.ouyang@sydney.edu.au, +<br/>bzhou@csail.mit.edu, shijianping@sensetime.com, c0502.zhang@samsung.com </td></tr><tr><td>582edc19f2b1ab2ac6883426f147196c8306685a</td><td>Do We Really Need to Collect Millions of Faces <br/>for Effective Face Recognition? <br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b></td><td>('11269472', 'Iacopo Masi', 'iacopo masi')<br/>('2955822', 'Jatuporn Toy Leksut', 'jatuporn toy leksut')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>5859774103306113707db02fe2dd3ac9f91f1b9e</td><td></td><td></td><td></td></tr><tr><td>5892f8367639e9c1e3cf27fdf6c09bb3247651ed</td><td>Estimating Missing Features to Improve Multimedia Information Retrieval @@ -4784,7 +5722,17 @@ </td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('1776343', 'Lior Wolf', 'lior wolf')<br/>('1759551', 'Nachum Dershowitz', 'nachum dershowitz')</td><td>Email: hassner@openu.ac.il <br/>Email: wolf@cs.tau.ac.il <br/>Email: nachumd@tau.ac.il -</td></tr><tr><td>58823377757e7dc92f3b70a973be697651089756</td><td>Technical Report +</td></tr><tr><td>58bf72750a8f5100e0c01e55fd1b959b31e7dbce</td><td>PyramidBox: A Context-assisted Single Shot +<br/>Face Detector. +<br/>Baidu Inc. +</td><td>('48785141', 'Xu Tang', 'xu tang')<br/>('14931829', 'Daniel K. Du', 'daniel k. du')<br/>('31239588', 'Zeqiang He', 'zeqiang he')<br/>('2272123', 'Jingtuo Liu', 'jingtuo liu')</td><td>tangxu02@baidu.com,daniel.kang.du@gmail.com,{hezeqiang,liujingtuo}@baidu.com +</td></tr><tr><td>58542eeef9317ffab9b155579256d11efb4610f2</td><td>International Journal of Science and Research (IJSR) +<br/>ISSN (Online): 2319-7064 +<br/>Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +<br/>Face Recognition Revisited on Pose, Alignment, +<br/>Color, Illumination and Expression-PyTen +<br/>Computer Science, BIT Noida, India +</td><td></td><td></td></tr><tr><td>58823377757e7dc92f3b70a973be697651089756</td><td>Technical Report <br/>UCAM-CL-TR-861 <br/>ISSN 1476-2986 <br/>Number 861 @@ -4950,7 +5898,9 @@ <br/>i∈Y <br/>yi, j . <br/>(2) -</td><td>('2682056', 'Ching-Hui Chen', 'ching-hui chen')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>676f9eabf4cfc1fd625228c83ff72f6499c67926</td><td>FACE IDENTIFICATION AND CLUSTERING +</td><td>('2682056', 'Ching-Hui Chen', 'ching-hui chen')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>677585ccf8619ec2330b7f2d2b589a37146ffad7</td><td>A flexible model for training action localization +<br/>with varying levels of supervision +</td><td>('1902524', 'Guilhem Chéron', 'guilhem chéron')<br/>('2285263', 'Jean-Baptiste Alayrac', 'jean-baptiste alayrac')<br/>('1785596', 'Ivan Laptev', 'ivan laptev')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>676f9eabf4cfc1fd625228c83ff72f6499c67926</td><td>FACE IDENTIFICATION AND CLUSTERING <br/>A thesis submitted to the <br/>Graduate School—New Brunswick <br/><b>Rutgers, The State University of New Jersey</b><br/>in partial fulfillment of the requirements @@ -4962,10 +5912,15 @@ <br/>and approved by <br/>New Brunswick, New Jersey <br/>May, 2017 -</td><td>('34805991', 'Atul Dhingra', 'atul dhingra')</td><td></td></tr><tr><td>677477e6d2ba5b99633aee3d60e77026fb0b9306</td><td></td><td></td><td></td></tr><tr><td>679b7fa9e74b2aa7892eaea580def6ed4332a228</td><td>Communication and automatic +</td><td>('34805991', 'Atul Dhingra', 'atul dhingra')</td><td></td></tr><tr><td>677477e6d2ba5b99633aee3d60e77026fb0b9306</td><td></td><td></td><td></td></tr><tr><td>6789bddbabf234f31df992a3356b36a47451efc7</td><td>Unsupervised Generation of Free-Form and +<br/>Parameterized Avatars +</td><td>('33964593', 'Adam Polyak', 'adam polyak')<br/>('2188620', 'Yaniv Taigman', 'yaniv taigman')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td></td></tr><tr><td>679b7fa9e74b2aa7892eaea580def6ed4332a228</td><td>Communication and automatic <br/>interpretation of affect from facial <br/>expressions1 -<br/><b>University of Amsterdam, the Netherlands</b><br/><b>University of Trento, Italy</b><br/><b>University of Amsterdam, the Netherlands</b></td><td>('1764521', 'Albert Ali Salah', 'albert ali salah')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td></td></tr><tr><td>670637d0303a863c1548d5b19f705860a23e285c</td><td>Face Swapping: Automatically Replacing Faces in Photographs +<br/><b>University of Amsterdam, the Netherlands</b><br/><b>University of Trento, Italy</b><br/><b>University of Amsterdam, the Netherlands</b></td><td>('1764521', 'Albert Ali Salah', 'albert ali salah')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td></td></tr><tr><td>675b2caee111cb6aa7404b4d6aa371314bf0e647</td><td>AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions +<br/>Carl Vondrick∗ +</td><td>('39599498', 'Chunhui Gu', 'chunhui gu')<br/>('1758054', 'Yeqing Li', 'yeqing li')<br/>('1726241', 'Chen Sun', 'chen sun')<br/>('48536531', 'David A. Ross', 'david a. ross')<br/>('2259154', 'Sudheendra Vijayanarasimhan', 'sudheendra vijayanarasimhan')<br/>('1805076', 'George Toderici', 'george toderici')<br/>('2997956', 'Caroline Pantofaru', 'caroline pantofaru')<br/>('2262946', 'Susanna Ricco', 'susanna ricco')<br/>('1694199', 'Rahul Sukthankar', 'rahul sukthankar')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td></td></tr><tr><td>679b72d23a9cfca8a7fe14f1d488363f2139265f</td><td></td><td></td><td></td></tr><tr><td>67484723e0c2cbeb936b2e863710385bdc7d5368</td><td>Anchor Cascade for Efficient Face Detection +</td><td>('2425630', 'Baosheng Yu', 'baosheng yu')<br/>('1692693', 'Dacheng Tao', 'dacheng tao')</td><td></td></tr><tr><td>670637d0303a863c1548d5b19f705860a23e285c</td><td>Face Swapping: Automatically Replacing Faces in Photographs <br/><b>Columbia University</b><br/>Peter Belhumeur <br/>Figure 1: We have developed a system that automatically replaces faces in an input image with ones selected from a large collection of <br/>face images, obtained by applying face detection to publicly available photographs on the internet. In this example, the faces of (a) two @@ -5015,12 +5970,27 @@ <br/>Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . <br/>Arthur C. Smith <br/>Chairman, Department Committee on Graduate Students -</td><td></td><td></td></tr><tr><td>67c703a864aab47eba80b94d1935e6d244e00bcb</td><td> (IJACSA) International Journal of Advanced Computer Science and Applications +</td><td></td><td></td></tr><tr><td>673d4885370b27c863e11a4ece9189a6a45931cc</td><td>Recurrent Residual Module for Fast Inference in Videos +<br/><b>Shanghai Jiao Tong University, 2Zhejiang University, 3Massachusetts Institute of Technology</b><br/>networks for video recognition are more challenging. For +<br/>example, for Youtube-8M dataset [1] with over 8 million +<br/>video clips, it will take 50 years for a CPU to extract the +<br/>deep features using a standard CNN model. +</td><td>('35654996', 'Bowen Pan', 'bowen pan')<br/>('35992009', 'Wuwei Lin', 'wuwei lin')<br/>('2126444', 'Xiaolin Fang', 'xiaolin fang')<br/>('35933894', 'Chaoqin Huang', 'chaoqin huang')<br/>('1804424', 'Bolei Zhou', 'bolei zhou')<br/>('1830034', 'Cewu Lu', 'cewu lu')</td><td>†{googletornado,linwuwei13, huangchaoqin}@sjtu.edu.cn, ¶fxlfang@gmail.com +<br/>§bzhou@csail.mit.edu; ‡lu-cw@cs.sjtu.edu.cn +</td></tr><tr><td>67c703a864aab47eba80b94d1935e6d244e00bcb</td><td> (IJACSA) International Journal of Advanced Computer Science and Applications <br/>Vol. 7, No. 6, 2016 <br/>Face Retrieval Based On Local Binary Pattern and Its <br/>Variants: A Comprehensive Study <br/><b>University of Science, VNU-HCM, Viet Nam</b><br/>face searching, -</td><td>('3911040', 'Phan Khoi', 'phan khoi')</td><td></td></tr><tr><td>677ebde61ba3936b805357e27fce06c44513a455</td><td>Facial Expression Recognition Based on Facial +</td><td>('3911040', 'Phan Khoi', 'phan khoi')</td><td></td></tr><tr><td>6754c98ba73651f69525c770fb0705a1fae78eb5</td><td>Joint Cascade Face Detection and Alignment +<br/><b>University of Science and Technology of China</b><br/>2 Microsoft Research +</td><td>('39447786', 'Dong Chen', 'dong chen')<br/>('3080683', 'Shaoqing Ren', 'shaoqing ren')<br/>('1732264', 'Yichen Wei', 'yichen wei')<br/>('47300766', 'Xudong Cao', 'xudong cao')<br/>('40055995', 'Jian Sun', 'jian sun')</td><td>{chendong,sqren}@mail.ustc.edu.cn +<br/>{yichenw,xudongca,jiansun}@microsoft.com +</td></tr><tr><td>672fae3da801b2a0d2bad65afdbbbf1b2320623e</td><td>Pose-Selective Max Pooling for Measuring Similarity +<br/>1Dept. of Computer Science +<br/>2Dept. of Electrical & Computer Engineering +<br/><b>Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b></td><td>('40031188', 'Xiang Xiang', 'xiang xiang')<br/>('1709073', 'Trac D. Tran', 'trac d. tran')</td><td>xxiang@cs.jhu.edu +</td></tr><tr><td>677ebde61ba3936b805357e27fce06c44513a455</td><td>Facial Expression Recognition Based on Facial <br/>Components Detection and HOG Features <br/><b>The Hong Kong Polytechnic University, Hong Kong</b><br/><b>Chu Hai College of Higher Education, Hong Kong</b></td><td>('2366262', 'Junkai Chen', 'junkai chen')<br/>('1715231', 'Zenghai Chen', 'zenghai chen')<br/>('8590720', 'Zheru Chi', 'zheru chi')<br/>('1965426', 'Hong Fu', 'hong fu')</td><td>Email: Junkai.Chen@connect.polyu.hk </td></tr><tr><td>67ba3524e135c1375c74fe53ebb03684754aae56</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE @@ -5028,6 +5998,20 @@ <br/>ICASSP 2017 </td><td></td><td></td></tr><tr><td>6769cfbd85329e4815bb1332b118b01119975a95</td><td>Tied factor analysis for face recognition across <br/>large pose changes +</td><td></td><td></td></tr><tr><td>0be43cf4299ce2067a0435798ef4ca2fbd255901</td><td>Title +<br/>A temporal latent topic model for facial expression recognition +<br/>Author(s) +<br/>Shang, L; Chan, KP +<br/>Citation +<br/>The 10th Asian Conference on Computer Vision (ACCV 2010), +<br/>Queenstown, New Zealand, 8-12 November 2010. In Lecture +<br/>Notes in Computer Science, 2010, v. 6495, p. 51-63 +<br/>Issued Date +<br/>2011 +<br/>URL +<br/>http://hdl.handle.net/10722/142604 +<br/>Rights +<br/>Creative Commons: Attribution 3.0 Hong Kong License </td><td></td><td></td></tr><tr><td>0bc53b338c52fc635687b7a6c1e7c2b7191f42e5</td><td>ZHANG, BHALERAO: LOGLET SIFT FOR PART DESCRIPTION <br/>Loglet SIFT for Part Description in <br/>Deformable Part Models: Application to Face @@ -5097,7 +6081,9 @@ <br/><b>Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore</b><br/><b>College of Computer Science, Sichuan University, Chengdu 610065, P.R. China</b></td><td>('8249791', 'Xi Peng', 'xi peng')<br/>('9276020', 'Zhang Yi', 'zhang yi')<br/>('3134548', 'Huajin Tang', 'huajin tang')</td><td>pangsaai@gmail.com, zhangyi@scu.edu.cn, htang@i2r.a-star.edu.sg. </td></tr><tr><td>0b20f75dbb0823766d8c7b04030670ef7147ccdd</td><td>1 <br/>Feature selection using nearest attributes -</td><td>('1744784', 'Alex Pappachen James', 'alex pappachen james')<br/>('1697594', 'Sima Dimitrijev', 'sima dimitrijev')</td><td></td></tr><tr><td>0b174d4a67805b8796bfe86cd69a967d357ba9b6</td><td> Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502 +</td><td>('1744784', 'Alex Pappachen James', 'alex pappachen james')<br/>('1697594', 'Sima Dimitrijev', 'sima dimitrijev')</td><td></td></tr><tr><td>0b5a82f8c0ee3640503ba24ef73e672d93aeebbf</td><td>On Learning 3D Face Morphable Model +<br/>from In-the-wild Images +</td><td>('1849929', 'Luan Tran', 'luan tran')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td></td></tr><tr><td>0b174d4a67805b8796bfe86cd69a967d357ba9b6</td><td> Research Journal of Recent Sciences _________________________________________________ ISSN 2277-2502 <br/> Vol. 3(4), 56-62, April (2014) <br/>Res.J.Recent Sci. </td><td></td><td></td></tr><tr><td>0ba449e312894bca0d16348f3aef41ca01872383</td><td></td><td></td><td></td></tr><tr><td>0b87d91fbda61cdea79a4b4dcdcb6d579f063884</td><td>The Open Automation and Control Systems Journal, 2015, 7, 569-579 @@ -5119,7 +6105,9 @@ <br/>Cambridge, MA </td><td>('1780935', 'Baback Moghaddam', 'baback moghaddam')<br/>('1768120', 'Tony Jebara', 'tony jebara')<br/>('1682773', 'Alex Pentland', 'alex pentland')</td><td>baback@merl.com <br/>fjebara,sandyg@media.mit.edu -</td></tr><tr><td>0b85b50b6ff03a7886c702ceabad9ab8c8748fdc</td><td>http://www.journalofvision.org/content/11/3/17 +</td></tr><tr><td>0b572a2b7052b15c8599dbb17d59ff4f02838ff7</td><td>Automatic Subspace Learning via Principal +<br/>Coefficients Embedding +</td><td>('8249791', 'Xi Peng', 'xi peng')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('1709367', 'Zhang Yi', 'zhang yi')<br/>('1680126', 'Rui Yan', 'rui yan')</td><td></td></tr><tr><td>0b85b50b6ff03a7886c702ceabad9ab8c8748fdc</td><td>http://www.journalofvision.org/content/11/3/17 <br/>Is there a dynamic advantage for facial expressions? <br/><b>Institute of Child Health, University College London, UK</b><br/>Laboratory of Neuromotor Physiology, Santa Lucia <br/>Foundation, Rome, Italy @@ -5209,7 +6197,9 @@ <br/>How Important is Weight Symmetry in <br/>Backpropagation? <br/>by -<br/><b>Center for Brains, Minds and Machines, McGovern Institute, MIT</b></td><td>('1694846', 'Qianli Liao', 'qianli liao')<br/>('1700356', 'Joel Z. Leibo', 'joel z. leibo')</td><td></td></tr><tr><td>0b50e223ad4d9465bb92dbf17a7b79eccdb997fb</td><td>Implicit Elastic Matching with Random Projections for Pose-Variant Face +<br/><b>Center for Brains, Minds and Machines, McGovern Institute, MIT</b></td><td>('1694846', 'Qianli Liao', 'qianli liao')<br/>('1700356', 'Joel Z. Leibo', 'joel z. leibo')</td><td></td></tr><tr><td>0ba1d855cd38b6a2c52860ae4d1a85198b304be4</td><td>Variable-state Latent Conditional Random Fields +<br/>for Facial Expression Recognition and Action Unit Detection +<br/><b>Imperial College London, UK</b><br/><b>Rutgers University, USA</b></td><td>('2616466', 'Robert Walecki', 'robert walecki')<br/>('1729713', 'Ognjen Rudovic', 'ognjen rudovic')<br/>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>0b50e223ad4d9465bb92dbf17a7b79eccdb997fb</td><td>Implicit Elastic Matching with Random Projections for Pose-Variant Face <br/>Recognition <br/>Electrical and Computer Engineering <br/><b>University of Illinois at Urbana-Champaign</b><br/>Microsoft Live Labs Research @@ -5222,6 +6212,12 @@ <br/>under Pose Variations <br/><b>Computer vision and Remote Sensing, Berlin university of Technology</b><br/>Sekr. FR-3-1, Franklinstr. 28/29, Berlin, Germany </td><td>('2326207', 'M. Saquib', 'm. saquib')<br/>('2962236', 'Olaf Hellwich', 'olaf hellwich')</td><td>{saquib;hellwich}@fpk.tu-berlin.de +</td></tr><tr><td>0bce54bfbd8119c73eb431559fc6ffbba741e6aa</td><td>Published as a conference paper at ICLR 2018 +<br/>SKIP RNN: LEARNING TO SKIP STATE UPDATES IN +<br/>RECURRENT NEURAL NETWORKS +<br/>†Barcelona Supercomputing Center, ‡Google Inc, +<br/><b>Universitat Polit`ecnica de Catalunya, Columbia University</b></td><td>('2447185', 'Brendan Jou', 'brendan jou')<br/>('1711068', 'Jordi Torres', 'jordi torres')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>{victor.campos, jordi.torres}@bsc.es, bjou@google.com, +<br/>xavier.giro@upc.edu, shih.fu.chang@columbia.edu </td></tr><tr><td>0b2966101fa617b90510e145ed52226e79351072</td><td>Beyond Verbs: Understanding Actions in Videos <br/>with Text <br/>Department of Computer Science @@ -5354,6 +6350,12 @@ <br/><b>Harvard University</b><br/><b>Stony Brook University</b></td><td>('2321406', 'Le Hou', 'le hou')<br/>('2576295', 'Chen-Ping Yu', 'chen-ping yu')<br/>('1686020', 'Dimitris Samaras', 'dimitris samaras')</td><td>lehhou@cs.stonybrook.edu <br/>chenpingyu@fas.harvard.edu <br/>samaras@cs.stonybrook.edu +</td></tr><tr><td>0bf0029c9bdb0ac61fda35c075deb1086c116956</td><td>Article +<br/>Modelling of Orthogonal Craniofacial Profiles +<br/><b>University of York, Heslington, York YO10 5GH, UK</b><br/>Received: 20 October 2017; Accepted: 23 November 2017; Published: 30 November 2017 +</td><td>('1694260', 'Hang Dai', 'hang dai')<br/>('1737428', 'Nick Pears', 'nick pears')<br/>('1678859', 'Christian Duncan', 'christian duncan')</td><td>nick.pears@york.ac.uk +<br/>2 Alder Hey Children’s Hospital, Liverpool L12 2AP, UK; Christian.Duncan@alderhey.nhs.uk +<br/>* Correspondence: hd816@york.ac.uk; Tel.: +44-1904-325-643 </td></tr><tr><td>0b3f354e6796ef7416bf6dde9e0779b2fcfabed2</td><td></td><td></td><td></td></tr><tr><td>9391618c09a51f72a1c30b2e890f4fac1f595ebd</td><td>Globally Tuned Cascade Pose Regression via <br/>Back Propagation with Application in 2D Face <br/>Pose Estimation and Heart Segmentation in 3D @@ -5433,6 +6435,19 @@ <br/>1920 Martigny </td><td>('2121764', 'Laurent El Shafey', 'laurent el shafey')</td><td>laurent.el-shafey@idiap.ch <br/>sebastien.marcel@idiap.ch +</td></tr><tr><td>93420d9212dd15b3ef37f566e4d57e76bb2fab2f</td><td>An All-In-One Convolutional Neural Network for Face Analysis +<br/><b>Center for Automation Research, UMIACS, University of Maryland, College Park, MD</b></td><td>('48467498', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{rranjan1,swamiviv,carlos,rama}@umiacs.umd.edu +</td></tr><tr><td>93af36da08bf99e68c9b0d36e141ed8154455ac2</td><td>Workshop track - ICLR 2018 +<br/>ADDITIVE MARGIN SOFTMAX +<br/>FOR FACE VERIFICATION +<br/>Department of Information and Communication Engineering +<br/><b>University of Electronic Science and Technology of China</b><br/>Chengdu, Sichuan 611731 China +<br/><b>College of Computing</b><br/><b>Georgia Institute of Technology</b><br/>Atlanta, United States. +<br/>Department of Information and Communication Engineering +<br/><b>University of Electronic Science and Technology of China</b><br/>Chengdu, Sichuan 611731 China +</td><td>('47939378', 'Feng Wang', 'feng wang')<br/>('51094998', 'Weiyang Liu', 'weiyang liu')<br/>('8424682', 'Haijun Liu', 'haijun liu')</td><td>feng.wff@gmail.com +<br/>{wyliu, hanjundai}@gatech.edu +<br/>haijun liu@126.com chengjian@uestc.edu.cn </td></tr><tr><td>93cbb3b3e40321c4990c36f89a63534b506b6daf</td><td>IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005 <br/>477 <br/>Learning From Examples in the Small Sample Case: @@ -5440,6 +6455,14 @@ </td><td>('1822413', 'Guodong Guo', 'guodong guo')<br/>('1724754', 'Charles R. Dyer', 'charles r. dyer')</td><td></td></tr><tr><td>937ffb1c303e0595317873eda5ce85b1a17f9943</td><td>Eyes Do Not Lie: Spontaneous versus Posed Smiles <br/><b>Intelligent Systems Lab Amsterdam, University of Amsterdam</b><br/>Science Park 107, Amsterdam, The Netherlands </td><td>('9301018', 'Roberto Valenti', 'roberto valenti')<br/>('1764521', 'Albert Ali Salah', 'albert ali salah')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td>h.dibeklioglu@uva.nl, r.valenti@uva.nl, a.a.salah@uva.nl, th.gevers@uva.nl +</td></tr><tr><td>93f37c69dd92c4e038710cdeef302c261d3a4f92</td><td>Compressed Video Action Recognition +<br/>Philipp Kr¨ahenb¨uhl1 +<br/><b>The University of Texas at Austin, 2Carnegie Mellon University</b><br/><b>University of Southern California, 4A9, 5Amazon</b></td><td>('2978413', 'Chao-Yuan Wu', 'chao-yuan wu')<br/>('1771307', 'Manzil Zaheer', 'manzil zaheer')<br/>('2804000', 'Hexiang Hu', 'hexiang hu')<br/>('1691629', 'Alexander J. Smola', 'alexander j. smola')<br/>('1758550', 'R. Manmatha', 'r. manmatha')</td><td>cywu@cs.utexas.edu +<br/>manzil@cmu.edu +<br/>smola@amazon.com +<br/>hexiangh@usc.edu +<br/>philkr@cs.utexas.edu +<br/>manmatha@a9.com </td></tr><tr><td>936227f7483938097cc1cdd3032016df54dbd5b6</td><td>Learning to generalize to new compositions in image understanding <br/><b>Gonda Brain Research Center, Bar Ilan University, Israel</b><br/>3Google Research, Mountain View CA, USA <br/><b>Tel Aviv University, Israel</b></td><td>('34815079', 'Yuval Atzmon', 'yuval atzmon')<br/>('1750652', 'Jonathan Berant', 'jonathan berant')<br/>('3451674', 'Vahid Kezami', 'vahid kezami')<br/>('1786843', 'Amir Globerson', 'amir globerson')<br/>('1732280', 'Gal Chechik', 'gal chechik')</td><td>yuval.atzmon@biu.ac.il @@ -5447,12 +6470,31 @@ <br/>Classification via BeFIT Protocols <br/><b>Idiap Research Institute</b><br/>Centre du Parc, Rue Marconi 19, CH-1920, Martigny, Switzerland </td><td>('2128163', 'Nesli Erdogmus', 'nesli erdogmus')<br/>('2059725', 'Matthias Vanoni', 'matthias vanoni')</td><td>Email: nesli.erdogmus, matthias.vanoni, marcel@idiap.ch +</td></tr><tr><td>938ae9597f71a21f2e47287cca318d4a2113feb2</td><td>Classifier Learning with Prior Probabilities +<br/>for Facial Action Unit Recognition +<br/>1National Laboratory of Pattern Recognition, CASIA +<br/><b>University of Chinese Academy of Sciences</b><br/><b>Rensselaer Polytechnic Institute</b></td><td>('49889545', 'Yong Zhang', 'yong zhang')<br/>('38690089', 'Weiming Dong', 'weiming dong')<br/>('39495638', 'Bao-Gang Hu', 'bao-gang hu')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>zhangyong201303@gmail.com, weiming.dong@ia.ac.cn, hubg@nlpr.ia.ac.cn, qji@ecse.rpi.edu </td></tr><tr><td>94b9c0a6515913bad345f0940ee233cdf82fffe1</td><td>International Journal of Science and Research (IJSR) <br/>ISSN (Online): 2319-7064 <br/>Impact Factor (2012): 3.358 <br/>Face Recognition using Local Ternary Pattern for <br/>Low Resolution Image -<br/><b>Research Scholar, CGC Group of Colleges, Gharuan, Punjab, India</b><br/><b>Chandigarh University, Gharuan, Punjab, India</b></td><td>('40440964', 'Amanpreet Kaur', 'amanpreet kaur')</td><td></td></tr><tr><td>9458c518a6e2d40fb1d6ca1066d6a0c73e1d6b73</td><td>5967 +<br/><b>Research Scholar, CGC Group of Colleges, Gharuan, Punjab, India</b><br/><b>Chandigarh University, Gharuan, Punjab, India</b></td><td>('40440964', 'Amanpreet Kaur', 'amanpreet kaur')</td><td></td></tr><tr><td>946017d5f11aa582854ac4c0e0f1b18b06127ef1</td><td>Tracking Persons-of-Interest +<br/>via Adaptive Discriminative Features +<br/><b>Xi an Jiaotong University</b><br/><b>Hanyang University</b><br/><b>University of Illinois, Urbana-Champaign</b><br/><b>University of California, Merced</b><br/>http://shunzhang.me.pn/papers/eccv2016/ +</td><td>('2481388', 'Shun Zhang', 'shun zhang')<br/>('1698965', 'Yihong Gong', 'yihong gong')<br/>('3068086', 'Jia-Bin Huang', 'jia-bin huang')<br/>('33047058', 'Jongwoo Lim', 'jongwoo lim')<br/>('32014778', 'Jinjun Wang', 'jinjun wang')<br/>('1752333', 'Narendra Ahuja', 'narendra ahuja')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>94eeae23786e128c0635f305ba7eebbb89af0023</td><td>Journal of Machine Learning Research 18 (2018) 1-34 +<br/>Submitted 01/17; Revised 4/18; Published 6/18 +<br/>Emergence of Invariance and Disentanglement +<br/>in Deep Representations∗ +<br/>Department of Computer Science +<br/><b>University of California</b><br/>Los Angeles, CA 90095, USA +<br/>Department of Computer Science +<br/><b>University of California</b><br/>Los Angeles, CA 90095, USA +<br/>Editor: Yoshua Bengio +</td><td>('16163297', 'Alessandro Achille', 'alessandro achille')<br/>('1715959', 'Stefano Soatto', 'stefano soatto')</td><td>achille@cs.ucla.edu +<br/>soatto@cs.ucla.edu +</td></tr><tr><td>944faf7f14f1bead911aeec30cc80c861442b610</td><td>Action Tubelet Detector for Spatio-Temporal Action Localization +</td><td>('1881509', 'Vicky Kalogeiton', 'vicky kalogeiton')<br/>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')<br/>('1749692', 'Vittorio Ferrari', 'vittorio ferrari')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>9458c518a6e2d40fb1d6ca1066d6a0c73e1d6b73</td><td>5967 <br/>A Benchmark and Comparative Study of <br/>Video-Based Face Recognition <br/>on COX Face Database @@ -5461,7 +6503,8 @@ <br/>International Symposium on Robotics and Intelligent Sensors 2012 (IRIS 2012) <br/>Face Recognition From Single Sample Per Person by Learning of <br/>Generic Discriminant Vectors -<br/><b>aFaculty of Electrical Engineering, University of Technology MARA, Shah Alam, 40450 Selangor, Malaysia</b><br/><b>bFaculty of Engineering, International Islamic University, Jalan Gombak, 53100 Kuala Lumpur, Malaysia</b></td><td>('7453141', 'Fadhlan Hafiz', 'fadhlan hafiz')<br/>('2412523', 'Amir A. Shafie', 'amir a. shafie')<br/>('9146253', 'Yasir Mohd Mustafah', 'yasir mohd mustafah')</td><td></td></tr><tr><td>94aa8a3787385b13ee7c4fdd2b2b2a574ffcbd81</td><td></td><td></td><td></td></tr><tr><td>9441253b638373a0027a5b4324b4ee5f0dffd670</td><td>A Novel Scheme for Generating Secure Face +<br/><b>aFaculty of Electrical Engineering, University of Technology MARA, Shah Alam, 40450 Selangor, Malaysia</b><br/><b>bFaculty of Engineering, International Islamic University, Jalan Gombak, 53100 Kuala Lumpur, Malaysia</b></td><td>('7453141', 'Fadhlan Hafiz', 'fadhlan hafiz')<br/>('2412523', 'Amir A. Shafie', 'amir a. shafie')<br/>('9146253', 'Yasir Mohd Mustafah', 'yasir mohd mustafah')</td><td></td></tr><tr><td>94aa8a3787385b13ee7c4fdd2b2b2a574ffcbd81</td><td></td><td></td><td></td></tr><tr><td>94325522c9be8224970f810554611d6a73877c13</td><td></td><td></td><td></td></tr><tr><td>9487cea80f23afe9bccc94deebaa3eefa6affa99</td><td>Fast, Dense Feature SDM on an iPhone +<br/><b>Queensland University of Technology, Brisbane, Queensland, Australia</b><br/><b>Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>('3231493', 'Ashton Fagg', 'ashton fagg')<br/>('1820249', 'Simon Lucey', 'simon lucey')<br/>('1729760', 'Sridha Sridharan', 'sridha sridharan')</td><td></td></tr><tr><td>9441253b638373a0027a5b4324b4ee5f0dffd670</td><td>A Novel Scheme for Generating Secure Face <br/>Templates Using BDA <br/>P.G. Student, Department of Computer Engineering, <br/>Associate Professor, Department of Computer @@ -5481,7 +6524,7 @@ <br/>2 Matsushita Electric Industrial Co., Ltd. <br/><b>Okayama University</b><br/>Okayama-shi, Okayama 700-8530, JAPAN </td><td>('3155610', 'Yasuhiro Mukaigawa', 'yasuhiro mukaigawa')<br/>('2740479', 'Yasunori Ishii', 'yasunori ishii')<br/>('1695509', 'Takeshi Shakunaga', 'takeshi shakunaga')</td><td>mukaigaw@am.sanken.osaka-u.ac.jp -</td></tr><tr><td>0efdd82a4753a8309ff0a3c22106c570d8a84c20</td><td>LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL +</td></tr><tr><td>94a11b601af77f0ad46338afd0fa4ccbab909e82</td><td></td><td></td><td></td></tr><tr><td>0efdd82a4753a8309ff0a3c22106c570d8a84c20</td><td>LDA WITH SUBGROUP PCA METHOD FOR FACIAL IMAGE RETRIEVAL <br/><b>Human Computer Interaction Lab., Samsung Advanced Institute of Technology, Korea</b></td><td>('34600044', 'Wonjun Hwang', 'wonjun hwang')<br/>('1700968', 'Tae-Kyun Kim', 'tae-kyun kim')<br/>('37980373', 'Seokcheol Kee', 'seokcheol kee')</td><td>wjhwang@sait.samsung.co.kr </td></tr><tr><td>0e5dcc6ae52625fd0637c6bba46a973e46d58b9c</td><td>Pareto Models for Multiclass Discriminative Linear <br/>Dimensionality Reduction @@ -5758,7 +6801,9 @@ <br/><b>School of Computing, National University of Singapore, Singapore</b><br/><b>Electrical and Computer Engineering, National University of Singapore, Singapore</b><br/><b>Beijing Institute of Technology University, P. R. China</b><br/>4 SAP Innovation Center Network Singapore, Singapore </td><td>('2757639', 'Jianshu Li', 'jianshu li')<br/>('2052311', 'Jian Zhao', 'jian zhao')<br/>('1715286', 'Terence Sim', 'terence sim')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('3124720', 'Shengtao Xiao', 'shengtao xiao')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('40345914', 'Fang Zhao', 'fang zhao')<br/>('1943724', 'Jianan Li', 'jianan li')</td><td>{jianshu,xiao_shengtao,zhaojian90}@u.nus.edu,lijianan15@gmail.com <br/>{elezhf,elefjia,eleyans}@nus.edu.sg,tsim@comp.nus.edu.sg -</td></tr><tr><td>0ee661a1b6bbfadb5a482ec643573de53a9adf5e</td><td>JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MONTH YEAR +</td></tr><tr><td>0ee737085af468f264f57f052ea9b9b1f58d7222</td><td>SiGAN: Siamese Generative Adversarial Network +<br/>for Identity-Preserving Face Hallucination +</td><td>('3192517', 'Chih-Chung Hsu', 'chih-chung hsu')<br/>('1685088', 'Chia-Wen Lin', 'chia-wen lin')<br/>('3404171', 'Weng-Tai Su', 'weng-tai su')<br/>('1705205', 'Gene Cheung', 'gene cheung')</td><td></td></tr><tr><td>0ee661a1b6bbfadb5a482ec643573de53a9adf5e</td><td>JOURNAL OF LATEX CLASS FILES, VOL. X, NO. X, MONTH YEAR <br/>On the Use of Discriminative Cohort Score <br/>Normalization for Unconstrained Face Recognition </td><td>('1725688', 'Massimo Tistarelli', 'massimo tistarelli')<br/>('2384894', 'Yunlian Sun', 'yunlian sun')<br/>('2404207', 'Norman Poh', 'norman poh')</td><td></td></tr><tr><td>0e36ada8cb9c91f07c9dcaf196d036564e117536</td><td>Much Ado About Time: Exhaustive Annotation of Temporal Data @@ -5791,7 +6836,11 @@ <br/><b>Multimedia University (MMU), Cyberjaya, Malaysia</b><br/>2 Faculty of Computing & Informatics, <br/><b>Multimedia University (MMU), Cyberjaya, Malaysia</b></td><td>('2339975', 'John See', 'john see')</td><td>lengoanhcat@gmail.com, raphael@mmu.edu.my <br/>johnsee@mmu.edu.my -</td></tr><tr><td>0ed1c1589ed284f0314ed2aeb3a9bbc760dcdeb5</td><td>Max-Margin Early Event Detectors +</td></tr><tr><td>0e93a5a7f6dbdb3802173dca05717d27d72bfec0</td><td>Attribute Recognition by Joint Recurrent Learning of Context and Correlation +<br/><b>Queen Mary University of London</b><br/>Vision Semantics Ltd.2 +</td><td>('48093957', 'Jingya Wang', 'jingya wang')<br/>('2171228', 'Xiatian Zhu', 'xiatian zhu')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('47113208', 'Wei Li', 'wei li')</td><td>{jingya.wang, s.gong, wei.li}@qmul.ac.uk +<br/>eddy@visionsemantics.com +</td></tr><tr><td>0e2ea7af369dbcaeb5e334b02dd9ba5271b10265</td><td></td><td></td><td></td></tr><tr><td>0ed1c1589ed284f0314ed2aeb3a9bbc760dcdeb5</td><td>Max-Margin Early Event Detectors <br/>Minh Hoai <br/><b>Robotics Institute, Carnegie Mellon University</b></td><td>('1707876', 'Fernando De la Torre', 'fernando de la torre')</td><td></td></tr><tr><td>0e7c70321462694757511a1776f53d629a1b38f3</td><td>NIST Special Publication 1136 <br/>2012 Proceedings of the @@ -5895,6 +6944,10 @@ <br/>light source direction makes with the camera's axis. <br/>1039 </td><td>('13801076', 'Feng Xie', 'feng xie')<br/>('3265275', 'Linmi Tao', 'linmi tao')</td><td>xiefeng97@mails.tsinghua.edu.cn <br/>{linmi, xgy-dcs}@tsinghua.edu.cn +</td></tr><tr><td>0ee5c4112208995bf2bb0fb8a87efba933a94579</td><td>Understanding Clothing Preference Based on Body Shape From Online Sources +<br/>Fashion is Taking Shape: +<br/>1Scalable Learning and Perception Group, 2Real Virtual Humans +<br/><b>Max Planck Institute for Informatics, Saarbr ucken, Germany</b></td><td>('26879574', 'Hosnieh Sattar', 'hosnieh sattar')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('2635816', 'Gerard Pons-Moll', 'gerard pons-moll')</td><td>{sattar,mfritz,gpons}@mpi-inf.mpg.de </td></tr><tr><td>0e1a18576a7d3b40fe961ef42885101f4e2630f8</td><td>Automated Detection and Identification of <br/>Persons in Video <br/>Visual Geometry Group @@ -5918,7 +6971,20 @@ <br/>Department of Computer Science and Engineering <br/><b>Ultra College of Engineering and Technology for Women, India</b><br/>2Assistant Professor <br/>Department of Computer Science and Engineering -<br/><b>Vickram College of Engineering, Enathi, Tamil Nadu, India</b></td><td></td><td></td></tr><tr><td>60d765f2c0a1a674b68bee845f6c02741a49b44e</td><td></td><td></td><td></td></tr><tr><td>60d4cef56efd2f5452362d4d9ac1ae05afa970d1</td><td>Learning End-to-end Video Classification with Rank-Pooling +<br/><b>Vickram College of Engineering, Enathi, Tamil Nadu, India</b></td><td></td><td></td></tr><tr><td>60d765f2c0a1a674b68bee845f6c02741a49b44e</td><td></td><td></td><td></td></tr><tr><td>60c24e44fce158c217d25c1bae9f880a8bd19fc3</td><td>Controllable Image-to-Video Translation: +<br/>A Case Study on Facial Expression Generation +<br/>MIT CSAIL +<br/>Wenbing Huang +<br/>Tencent AI Lab +<br/>MIT-Waston Lab +<br/>Tencent AI Lab +<br/>Tencent AI Lab +</td><td>('2548303', 'Lijie Fan', 'lijie fan')<br/>('2551285', 'Chuang Gan', 'chuang gan')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('40206014', 'Boqing Gong', 'boqing gong')</td><td></td></tr><tr><td>60e2b9b2e0db3089237d0208f57b22a3aac932c1</td><td>Frankenstein: Learning Deep Face Representations +<br/>using Small Data +</td><td>('38819702', 'Guosheng Hu', 'guosheng hu')<br/>('1766837', 'Xiaojiang Peng', 'xiaojiang peng')<br/>('2653152', 'Yongxin Yang', 'yongxin yang')<br/>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')<br/>('34602236', 'Jakob Verbeek', 'jakob verbeek')</td><td></td></tr><tr><td>60542b1a857024c79db8b5b03db6e79f74ec8f9f</td><td>Learning to Detect Human-Object Interactions +<br/><b>University of Michigan, Ann Arbor</b><br/><b>Washington University in St. Louis</b></td><td>('2820136', 'Yu-Wei Chao', 'yu-wei chao')<br/>('1860829', 'Yunfan Liu', 'yunfan liu')<br/>('9539636', 'Xieyang Liu', 'xieyang liu')<br/>('9344937', 'Huayi Zeng', 'huayi zeng')<br/>('8342699', 'Jia Deng', 'jia deng')</td><td>{ywchao,yunfan,lxieyang,jiadeng}@umich.edu +<br/>{zengh}@wustl.edu +</td></tr><tr><td>60d4cef56efd2f5452362d4d9ac1ae05afa970d1</td><td>Learning End-to-end Video Classification with Rank-Pooling <br/><b>Research School of Engineering, The Australian National University, ACT 2601, Australia</b><br/><b>Research School of Computer Science, The Australian National University, ACT 2601, Australia</b></td><td>('1688071', 'Basura Fernando', 'basura fernando')<br/>('2377076', 'Stephen Gould', 'stephen gould')</td><td>BASURA.FERNANDO@ANU.EDU.AU <br/>STEPHEN.GOULD@ANU.EDU.AU </td></tr><tr><td>60ce4a9602c27ad17a1366165033fe5e0cf68078</td><td>TECHNICAL NOTE @@ -6164,7 +7230,10 @@ <br/><b>National University of Singapore</b><br/>4 State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science <br/><b>and Engineering, Beihang University, Beijing, China</b></td><td>('1719250', 'Xiaochun Cao', 'xiaochun cao')<br/>('38188331', 'Hua Zhang', 'hua zhang')<br/>('33465926', 'Xiaojie Guo', 'xiaojie guo')<br/>('2705801', 'Si Liu', 'si liu')<br/>('33610144', 'Xiaowu Chen', 'xiaowu chen')</td><td>caoxiaochun@iie.ac.cn, huazhang@tju.edu.cn, xj.max.guo@gmail.com, <br/>dcslius@nus.edu.sg, chen@buaa.edu.cn -</td></tr><tr><td>34d484b47af705e303fc6987413dc0180f5f04a9</td><td>RI:Medium: Unsupervised and Weakly-Supervised +</td></tr><tr><td>345cc31c85e19cea9f8b8521be6a37937efd41c2</td><td>Deep Manifold Traversal: Changing Labels with +<br/>Convolutional Features +<br/><b>Cornell University, Washington University in St. Louis</b><br/>*Authors contributing equally +</td><td>('31693738', 'Jacob R. Gardner', 'jacob r. gardner')<br/>('3222840', 'Paul Upchurch', 'paul upchurch')<br/>('1940272', 'Matt J. Kusner', 'matt j. kusner')<br/>('7769997', 'Yixuan Li', 'yixuan li')<br/>('1706504', 'John E. Hopcroft', 'john e. hopcroft')</td><td></td></tr><tr><td>34d484b47af705e303fc6987413dc0180f5f04a9</td><td>RI:Medium: Unsupervised and Weakly-Supervised <br/>Discovery of Facial Events <br/>1 Introduction <br/>The face is one of the most powerful channels of nonverbal communication. Facial expression has been a @@ -6204,11 +7273,18 @@ <br/>possible facial movement combinations, and characterization of subtle facial behavior. <br/>• We propose two novel non-parametric algorithms for unsupervised and weakly-supervised time-series <br/>analysis. In preliminary experiments these algorithms were able to discover meaningful facial events -</td><td></td><td></td></tr><tr><td>345bea5f7d42926f857f395c371118a00382447f</td><td>Transfiguring Portraits +</td><td></td><td></td></tr><tr><td>341002fac5ae6c193b78018a164d3c7295a495e4</td><td>von Mises-Fisher Mixture Model-based Deep +<br/>learning: Application to Face Verification +</td><td>('1773090', 'Md. Abul Hasnat', 'md. abul hasnat')<br/>('34767162', 'Jonathan Milgram', 'jonathan milgram')<br/>('34086868', 'Liming Chen', 'liming chen')</td><td></td></tr><tr><td>34ce703b7e79e3072eed7f92239a4c08517b0c55</td><td>What impacts skin color in digital photos? +<br/><b>Advanced Digital Sciences Center, University of Illinois at Urbana-Champaign, Singapore</b></td><td>('3213946', 'Albrecht Lindner', 'albrecht lindner')<br/>('1702224', 'Stefan Winkler', 'stefan winkler')</td><td></td></tr><tr><td>345bea5f7d42926f857f395c371118a00382447f</td><td>Transfiguring Portraits <br/><b>Computer Science and Engineering, University of Washington</b><br/>Figure 1: Our system’s goal is to let people imagine and explore how they may look like in a different country, era, hair style, hair color, age, <br/>and anything else that can be queried in an image search engine. The examples above show a single input photo (left) and automatically <br/>synthesized appearances of the input person with ”curly hair” (top row), in ”india” (2nd row), and at ”1930” (3rd row). -</td><td>('2419955', 'Ira Kemelmacher-Shlizerman', 'ira kemelmacher-shlizerman')</td><td></td></tr><tr><td>3463f12ad434d256cd5f94c1c1bfd2dd6df36947</td><td>Article +</td><td>('2419955', 'Ira Kemelmacher-Shlizerman', 'ira kemelmacher-shlizerman')</td><td></td></tr><tr><td>34ec83c8ff214128e7a4a4763059eebac59268a6</td><td>Action Anticipation By Predicting Future +<br/>Dynamic Images +<br/>Australian Centre for Robotic Vision, ANU, Canberra, Australia +</td><td>('46771280', 'Cristian Rodriguez', 'cristian rodriguez')<br/>('1688071', 'Basura Fernando', 'basura fernando')<br/>('40124570', 'Hongdong Li', 'hongdong li')</td><td>{cristian.rodriguez, basura.fernando, hongdong.li}@.anu.edu.au +</td></tr><tr><td>3463f12ad434d256cd5f94c1c1bfd2dd6df36947</td><td>Article <br/>Facial Expression Recognition with Fusion Features <br/>Extracted from Salient Facial Areas <br/><b>School of Control Science and Engineering, Shandong University, Jinan 250061, China</b><br/>Academic Editors: Xue-Bo Jin; Shuli Sun; Hong Wei and Feng-Bao Yang @@ -6327,7 +7403,9 @@ <br/>Dimensional Data on Large Scale Dictionaries <br/><b>Princeton University</b><br/>Princeton, NJ 08544, USA </td><td>('1730249', 'Zhen James Xiang', 'zhen james xiang')<br/>('1693135', 'Peter J. Ramadge', 'peter j. ramadge')</td><td>{zxiang,haoxu,ramadge}@princeton.edu -</td></tr><tr><td>5a93f9084e59cb9730a498ff602a8c8703e5d8a5</td><td>HUSSAIN ET. AL: FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS +</td></tr><tr><td>5a3da29970d0c3c75ef4cb372b336fc8b10381d7</td><td>CNN-based Real-time Dense Face Reconstruction +<br/>with Inverse-rendered Photo-realistic Face Images +</td><td>('8280113', 'Yudong Guo', 'yudong guo')<br/>('2938279', 'Juyong Zhang', 'juyong zhang')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')<br/>('15679675', 'Boyi Jiang', 'boyi jiang')<br/>('48510441', 'Jianmin Zheng', 'jianmin zheng')</td><td></td></tr><tr><td>5a93f9084e59cb9730a498ff602a8c8703e5d8a5</td><td>HUSSAIN ET. AL: FACE RECOGNITION USING LOCAL QUANTIZED PATTERNS <br/>Face Recognition using Local Quantized <br/>Patterns <br/>Fréderic Jurie @@ -6372,7 +7450,17 @@ <br/>gassassa@coeia.edu.sa <br/>monmursi@coeia.edu.sa </td></tr><tr><td>5a34a9bb264a2594c02b5f46b038aa1ec3389072</td><td>Label-Embedding for Image Classification -</td><td>('2893664', 'Zeynep Akata', 'zeynep akata')<br/>('1723883', 'Florent Perronnin', 'florent perronnin')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>5a4c6246758c522f68e75491eb65eafda375b701</td><td>978-1-4244-4296-6/10/$25.00 ©2010 IEEE +</td><td>('2893664', 'Zeynep Akata', 'zeynep akata')<br/>('1723883', 'Florent Perronnin', 'florent perronnin')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>5a5f9e0ed220ce51b80cd7b7ede22e473a62062c</td><td>Videos as Space-Time Region Graphs +<br/><b>Robotics Institute, Carnegie Mellon University</b><br/>Figure 1. How do you recognize simple actions such as opening book? We argue action +<br/>understanding requires appearance modeling but also capturing temporal dynamics +<br/>(how shape of book changes) and functional relationships. We propose to represent +<br/>videos as space-time region graphs followed by graph convolutions for inference. +</td><td>('39849136', 'Xiaolong Wang', 'xiaolong wang')<br/>('1737809', 'Abhinav Gupta', 'abhinav gupta')</td><td></td></tr><tr><td>5ac946fc6543a445dd1ee6d5d35afd3783a31353</td><td>FEATURELESS: BYPASSING FEATURE EXTRACTION IN ACTION CATEGORIZATION +<br/>S. L. Pinteaa, P. S. Mettesa +<br/>J. C. van Gemerta,b, A. W. M. Smeuldersa +<br/>aIntelligent Sensory Information Systems, +<br/><b>University of Amsterdam</b><br/>Amsterdam, Netherlands +</td><td></td><td></td></tr><tr><td>5a4c6246758c522f68e75491eb65eafda375b701</td><td>978-1-4244-4296-6/10/$25.00 ©2010 IEEE <br/>1118 <br/>ICASSP 2010 </td><td></td><td></td></tr><tr><td>5aad5e7390211267f3511ffa75c69febe3b84cc7</td><td>Driver Gaze Estimation @@ -6390,7 +7478,8 @@ <br/>Facial Emotion Recognition and Classification Using Hybridization <br/>Method <br/><b>Chandigarh Engg. College, Mohali, Punjab, India</b></td><td>('6010530', 'Anchal Garg', 'anchal garg')<br/>('9744572', 'Rohit Bajaj', 'rohit bajaj')</td><td>anchalgarg949@gmail.com, 07696449500 -</td></tr><tr><td>5aa57a12444dbde0f5645bd9bcec8cb2f573c6a0</td><td>The International Arab Journal of Information Technology, Vol. 11, No. 2, March 2014 +</td></tr><tr><td>5a4ec5c79f3699ba037a5f06d8ad309fb4ee682c</td><td>Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 12/17/2017 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +<br/>AutomaticageandgenderclassificationusingsupervisedappearancemodelAliMainaBukarHassanUgailDavidConnahAliMainaBukar,HassanUgail,DavidConnah,“Automaticageandgenderclassificationusingsupervisedappearancemodel,”J.Electron.Imaging25(6),061605(2016),doi:10.1117/1.JEI.25.6.061605. </td><td></td><td></td></tr><tr><td>5aa57a12444dbde0f5645bd9bcec8cb2f573c6a0</td><td>The International Arab Journal of Information Technology, Vol. 11, No. 2, March 2014 <br/> <br/>149 <br/> @@ -6398,9 +7487,43 @@ <br/>Criterion and Linear Discriminant Analysis <br/> <br/>(AMFC-LDA) -<br/><b>COMSATS Institute of Information Technology, Pakistan</b></td><td>('2151799', 'Marryam Murtaza', 'marryam murtaza')<br/>('33088042', 'Muhammad Sharif', 'muhammad sharif')<br/>('36739230', 'Mudassar Raza', 'mudassar raza')<br/>('1814986', 'Jamal Hussain Shah', 'jamal hussain shah')</td><td></td></tr><tr><td>5a7520380d9960ff3b4f5f0fe526a00f63791e99</td><td>The Indian Spontaneous Expression +<br/><b>COMSATS Institute of Information Technology, Pakistan</b></td><td>('2151799', 'Marryam Murtaza', 'marryam murtaza')<br/>('33088042', 'Muhammad Sharif', 'muhammad sharif')<br/>('36739230', 'Mudassar Raza', 'mudassar raza')<br/>('1814986', 'Jamal Hussain Shah', 'jamal hussain shah')</td><td></td></tr><tr><td>5aed0f26549c6e64c5199048c4fd5fdb3c5e69d6</td><td>International Journal of Computer Applications® (IJCA) (0975 – 8887) +<br/>International Conference on Knowledge Collaboration in Engineering, ICKCE-2014 +<br/>Human Expression Recognition using Facial Features +<br/>G.Saranya +<br/>Post graduate student, Dept. of ECE +<br/><b>Parisutham Institute of Technology and Science</b><br/>Thanjavur. +<br/><b>Affiliated to Anna university, Chennai</b><br/>recognition can be used +</td><td></td><td></td></tr><tr><td>5a7520380d9960ff3b4f5f0fe526a00f63791e99</td><td>The Indian Spontaneous Expression <br/>Database for Emotion Recognition -</td><td>('38657440', 'Priyadarshi Patnaik', 'priyadarshi patnaik')<br/>('2680543', 'Aurobinda Routray', 'aurobinda routray')<br/>('2730256', 'Rajlakshmi Guha', 'rajlakshmi guha')</td><td></td></tr><tr><td>5f871838710a6b408cf647aacb3b198983719c31</td><td>1716 +</td><td>('38657440', 'Priyadarshi Patnaik', 'priyadarshi patnaik')<br/>('2680543', 'Aurobinda Routray', 'aurobinda routray')<br/>('2730256', 'Rajlakshmi Guha', 'rajlakshmi guha')</td><td></td></tr><tr><td>5a07945293c6b032e465d64f2ec076b82e113fa6</td><td>Pulling Actions out of Context: Explicit Separation for Effective Combination +<br/><b>Stony Brook University, Stony Brook, NY 11794, USA</b></td><td>('50874742', 'Yang Wang', 'yang wang')</td><td>{wang33, minhhoai}@cs.stonybrook.edu +</td></tr><tr><td>5fff61302adc65d554d5db3722b8a604e62a8377</td><td>Additive Margin Softmax for Face Verification +<br/>UESTC +<br/>Georgia Tech +<br/>UESTC +<br/>UESTC +</td><td>('47939378', 'Feng Wang', 'feng wang')<br/>('51094998', 'Weiyang Liu', 'weiyang liu')<br/>('8424682', 'Haijun Liu', 'haijun liu')<br/>('1709439', 'Jian Cheng', 'jian cheng')</td><td>feng.wff@gmail.com +<br/>wyliu@gatech.edu +<br/>haijun liu@126.com +<br/>chengjian@uestc.edu.cn +</td></tr><tr><td>5f771fed91c8e4b666489ba2384d0705bcf75030</td><td>Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning +<br/>and A New Benchmark for Multi-Human Parsing +<br/><b>National University of Singapore</b><br/><b>National University of Defense Technology</b><br/><b>Qihoo 360 AI Institute</b></td><td>('46509484', 'Jian Zhao', 'jian zhao')<br/>('2757639', 'Jianshu Li', 'jianshu li')<br/>('48207454', 'Li Zhou', 'li zhou')<br/>('1715286', 'Terence Sim', 'terence sim')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')</td><td>chengyu996@gmail.com zhouli2025@gmail.com +<br/>{eleyans, elefjia}@nus.edu.sg +<br/>{zhaojian90, jianshu}@u.nus.edu +<br/>tsim@comp.nus.edu.sg +</td></tr><tr><td>5fa04523ff13a82b8b6612250a39e1edb5066521</td><td>Dockerface: an Easy to Install and Use Faster R-CNN Face Detector in a Docker +<br/>Container +<br/>Center for Behavioral Imaging +<br/><b>College of Computing</b><br/><b>Georgia Institute of Technology</b></td><td>('31601235', 'Nataniel Ruiz', 'nataniel ruiz')<br/>('1692956', 'James M. Rehg', 'james m. rehg')</td><td>nataniel.ruiz@gatech.edu +<br/>rehg@gatech.edu +</td></tr><tr><td>5fa6e4a23da0b39e4b35ac73a15d55cee8608736</td><td>IJCV special issue (Best papers of ECCV 2016) manuscript No. +<br/>(will be inserted by the editor) +<br/>RED-Net: +<br/>A Recurrent Encoder-Decoder Network for Video-based Face Alignment +<br/>Submitted: April 19 2017 / Revised: December 12 2017 +</td><td>('4340744', 'Xi Peng', 'xi peng')</td><td></td></tr><tr><td>5f871838710a6b408cf647aacb3b198983719c31</td><td>1716 <br/>Locally Linear Regression for Pose-Invariant <br/>Face Recognition </td><td>('1695600', 'Xiujuan Chai', 'xiujuan chai')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')<br/>('1698902', 'Wen Gao', 'wen gao')</td><td></td></tr><tr><td>5f64a2a9b6b3d410dd60dc2af4a58a428c5d85f9</td><td></td><td></td><td></td></tr><tr><td>5f344a4ef7edfd87c5c4bc531833774c3ed23542</td><td>c @@ -6415,12 +7538,128 @@ </td><td>('8060096', 'Sheng-hung Hu', 'sheng-hung hu')<br/>('2180892', 'Yikang Li', 'yikang li')<br/>('2913552', 'Baoxin Li', 'baoxin li')</td><td>Email:shenghun@asu.edu <br/>Email:yikangli@asu.edu <br/>Email:Baoxin.Li@asu.edu -</td></tr><tr><td>5fa0e6da81acece7026ac1bc6dcdbd8b204a5f0a</td><td></td><td></td><td></td></tr><tr><td>5feb1341a49dd7a597f4195004fe9b59f67e6707</td><td>A Deep Ranking Model for Spatio-Temporal Highlight Detection +</td></tr><tr><td>5f7c4c20ae2731bfb650a96b69fd065bf0bb950e</td><td>Turk J Elec Eng & Comp Sci +<br/>(2016) 24: 1797 { 1814 +<br/>c⃝ T (cid:127)UB_ITAK +<br/>doi:10.3906/elk-1310-253 +<br/>A new fuzzy membership assignment and model selection approach based on +<br/>dynamic class centers for fuzzy SVM family using the (cid:12)re(cid:13)y algorithm +<br/><b>Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran</b><br/><b>Faculty of Engineering, Ferdowsi University, Mashhad, Iran</b><br/>Received: 01.11.2013 +<br/>(cid:15) +<br/>Accepted/Published Online: 30.06.2014 +<br/>(cid:15) +<br/>Final Version: 23.03.2016 +</td><td>('9437627', 'Omid Naghash Almasi', 'omid naghash almasi')<br/>('4945660', 'Modjtaba Rouhani', 'modjtaba rouhani')</td><td></td></tr><tr><td>5f94969b9491db552ffebc5911a45def99026afe</td><td>Multimodal Learning and Reasoning for Visual +<br/>Question Answering +<br/>Integrative Sciences and Engineering +<br/><b>National University of Singapore</b><br/>Electrical and Computer Engineering +<br/><b>National University of Singapore</b></td><td>('3393294', 'Ilija Ilievski', 'ilija ilievski')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')</td><td>ilija.ilievski@u.nus.edu +<br/>elefjia@nus.edu.sg +</td></tr><tr><td>5f758a29dae102511576c0a5c6beda264060a401</td><td>Fine-grained Video Attractiveness Prediction Using Multimodal +<br/>Deep Learning on a Large Real-world Dataset +<br/><b>Wuhan University, Tencent AI Lab, National University of Singapore, University of Rochester</b></td><td>('3179887', 'Xinpeng Chen', 'xinpeng chen')<br/>('47740660', 'Jingyuan Chen', 'jingyuan chen')<br/>('34264361', 'Lin Ma', 'lin ma')<br/>('1849993', 'Jian Yao', 'jian yao')<br/>('46641573', 'Wei Liu', 'wei liu')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')<br/>('38144094', 'Tong Zhang', 'tong zhang')</td><td></td></tr><tr><td>5fa0e6da81acece7026ac1bc6dcdbd8b204a5f0a</td><td></td><td></td><td></td></tr><tr><td>5feb1341a49dd7a597f4195004fe9b59f67e6707</td><td>A Deep Ranking Model for Spatio-Temporal Highlight Detection <br/>from a 360◦ Video <br/><b>Seoul National University</b></td><td>('7877122', 'Youngjae Yu', 'youngjae yu')<br/>('1693291', 'Sangho Lee', 'sangho lee')<br/>('35272603', 'Joonil Na', 'joonil na')<br/>('35365676', 'Jaeyun Kang', 'jaeyun kang')<br/>('1743920', 'Gunhee Kim', 'gunhee kim')</td><td>{yj.yu, sangho.lee, joonil}@vision.snu.ac.kr, {kjy13411}@gmail.com, gunhee@snu.ac.kr -</td></tr><tr><td>5f57a1a3a1e5364792b35e8f5f259f92ad561c1f</td><td>Implicit Sparse Code Hashing +</td></tr><tr><td>5f0d4a0b5f72d8700cdf8cb179263a8fa866b59b</td><td>CBMM Memo No. 85 +<br/>06/2018 +<br/>Deep Regression Forests for Age Estimation +<br/><b>Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University</b><br/><b>Johns Hopkins University</b><br/><b>College of Computer and Control Engineering, Nankai University 4: Hikvision Research</b></td><td>('41187410', 'Wei Shen', 'wei shen')<br/>('9544564', 'Yilu Guo', 'yilu guo')<br/>('46394340', 'Yan Wang', 'yan wang')<br/>('1681247', 'Kai Zhao', 'kai zhao')<br/>('46172451', 'Bo Wang', 'bo wang')<br/>('35922327', 'Alan Yuille', 'alan yuille')</td><td></td></tr><tr><td>5f57a1a3a1e5364792b35e8f5f259f92ad561c1f</td><td>Implicit Sparse Code Hashing <br/><b>Institute of Information Science</b><br/>Academia Sinica, Taiwan -</td><td>('2144284', 'Tsung-Yu Lin', 'tsung-yu lin')<br/>('2301765', 'Tsung-Wei Ke', 'tsung-wei ke')<br/>('1805102', 'Tyng-Luh Liu', 'tyng-luh liu')</td><td></td></tr><tr><td>5fa932be4d30cad13ea3f3e863572372b915bec8</td><td></td><td></td><td></td></tr><tr><td>5f5906168235613c81ad2129e2431a0e5ef2b6e4</td><td>Noname manuscript No. +</td><td>('2144284', 'Tsung-Yu Lin', 'tsung-yu lin')<br/>('2301765', 'Tsung-Wei Ke', 'tsung-wei ke')<br/>('1805102', 'Tyng-Luh Liu', 'tyng-luh liu')</td><td></td></tr><tr><td>5f27ed82c52339124aa368507d66b71d96862cb7</td><td>Semi-supervised Learning of Classifiers: Theory, Algorithms +<br/>and Their Application to Human-Computer Interaction +<br/>This work has been partially funded by NSF Grant IIS 00-85980. +<br/>DRAFT +</td><td>('1774778', 'Ira Cohen', 'ira cohen')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>Ira Cohen: Hewlett-Packard Labs, Palo Alto, CA, USA, ira.cohen@hp.com +<br/>Fabio G. Cozman and Marcelo C. Cirelo: Escola Polit´ecnica, Universidade de S˜ao Paulo, S˜ao Paulo,Brazil. fgcozman@usp.br, +<br/>marcelo.cirelo@poli.usp.br +<br/>Nicu Sebe: Faculty of Science, University of Amsterdam, The Netherlands. nicu@science.uva.nl +<br/>Thomas S. Huang: Beckman Institute, University of Illinois at Urbana-Champaign, USA. huang@ifp.uiuc.edu +</td></tr><tr><td>5fa932be4d30cad13ea3f3e863572372b915bec8</td><td></td><td></td><td></td></tr><tr><td>5fea26746f3140b12317fcf3bc1680f2746e172e</td><td>Dense Supervision for Visual Comparisons via Synthetic Images +<br/>Semantic Jitter: +<br/><b>University of Texas at Austin</b><br/><b>University of Texas at Austin</b><br/>Distinguishing subtle differences in attributes is valuable, yet +<br/>learning to make visual comparisons remains non-trivial. Not +<br/>only is the number of possible comparisons quadratic in the +<br/>number of training images, but also access to images adequately +<br/>spanning the space of fine-grained visual differences is limited. +<br/>We propose to overcome the sparsity of supervision problem +<br/>via synthetically generated images. Building on a state-of-the- +<br/>art image generation engine, we sample pairs of training images +<br/>exhibiting slight modifications of individual attributes. Augment- +<br/>ing real training image pairs with these examples, we then train +<br/>attribute ranking models to predict the relative strength of an +<br/>attribute in novel pairs of real images. Our results on datasets of +<br/>faces and fashion images show the great promise of bootstrapping +<br/>imperfect image generators to counteract sample sparsity for +<br/>learning to rank. +<br/>INTRODUCTION +<br/>Fine-grained analysis of images often entails making visual +<br/>comparisons. For example, given two products in a fashion +<br/>catalog, a shopper may judge which shoe appears more pointy +<br/>at the toe. Given two selfies, a teen may gauge in which one he +<br/>is smiling more. Given two photos of houses for sale on a real +<br/>estate website, a home buyer may analyze which facade looks +<br/>better maintained. Given a series of MRI scans, a radiologist +<br/>may judge which pair exhibits the most shape changes. +<br/>In these and many other such cases, we are interested in +<br/>inferring how a pair of images compares in terms of a par- +<br/>ticular property, or “attribute”. That is, which is more pointy, +<br/>smiling, well-maintained, etc. Importantly, the distinctions of +<br/>interest are often quite subtle. Subtle comparisons arise both +<br/>in image pairs that are very similar in almost every regard +<br/>(e.g., two photos of the same individual wearing the same +<br/>clothing, yet smiling more in one photo than the other), as +<br/>well as image pairs that are holistically different yet exhibit +<br/>only slight differences in the attribute in question (e.g., two +<br/>individuals different in appearance, and one is smiling slightly +<br/>more than the other). +<br/>A growing body of work explores computational models +<br/>for visual comparisons [1], [2], [3], [4], [5], [6], [7], [8], [9], +<br/>[10], [11], [12]. In particular, ranking models for “relative +<br/>attributes” [2], [3], [4], [5], [9], [11] use human-ordered pairs +<br/>of images to train a system to predict the relative ordering in +<br/>novel image pairs. +<br/>A major challenge in training a ranking model is the sparsity +<br/>of supervision. That sparsity stems from two factors: label +<br/>availability and image availability. Because training instances +<br/>consist of pairs of images—together with the ground truth +<br/>human judgment about which exhibits the property more +<br/>Fig. 1: Our method “densifies” supervision for training ranking functions to +<br/>make visual comparisons, by generating ordered pairs of synthetic images. +<br/>Here, when learning the attribute smiling, real training images need not be +<br/>representative of the entire attribute space (e.g., Web photos may cluster +<br/>around commonly photographed expressions, like toothy smiles). Our idea +<br/>“fills in” the sparsely sampled regions to enable fine-grained supervision. +<br/>Given a novel pair (top), the nearest synthetic pairs (right) may present better +<br/>training data than the nearest real pairs (left). +<br/>or less—the space of all possible comparisons is quadratic +<br/>in the number of potential +<br/>training images. This quickly +<br/>makes it intractable to label an image collection exhaustively +<br/>for its comparative properties. At the same time, attribute +<br/>comparisons entail a greater cognitive load than, for example, +<br/>object category labeling. Indeed, the largest existing relative +<br/>attribute datasets sample only less than 0.1% of all image pairs +<br/>for ground truth labels [11], and there is a major size gap +<br/>between standard datasets labeled for classification (now in +<br/>the millions [13]) and those for comparisons (at best in the +<br/>thousands [11]). A popular shortcut is to propagate category- +<br/>level comparisons down to image instances [4], [14]—e.g., +<br/>deem all ocean scenes as “more open” than all forest scenes— +<br/>but +<br/>label noise and in practice +<br/>underperforms training with instance-level comparisons [2]. +<br/>this introduces substantial +<br/>Perhaps more insidious than the annotation cost, however, +<br/>is the problem of even curating training images that suf- +<br/>ficiently illustrate fine-grained differences. Critically, sparse +<br/>supervision arises not simply because 1) we lack resources +<br/>to get enough image pairs labeled, but also because 2) we +<br/>lack a direct way to curate photos demonstrating all sorts +<br/>of subtle attribute changes. For example, how might we +<br/>gather unlabeled image pairs depicting all subtle differences +<br/>Novel PairReal PairsSynthetic Pairsvs. </td><td>('2206630', 'Aron Yu', 'aron yu')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>aron.yu@utexas.edu +<br/>grauman@cs.utexas.edu +</td></tr><tr><td>5f5906168235613c81ad2129e2431a0e5ef2b6e4</td><td>Noname manuscript No. <br/>(will be inserted by the editor) <br/>A Unified Framework for Compositional Fitting of <br/>Active Appearance Models @@ -6437,6 +7676,19 @@ <br/>of Online Advertising (SARA) for Audience Behavior Analysis <br/><b>College of Electronics and Information Engineering, Sichuan University, Chengdu 610064, China</b><br/><b>BRIC, University of North Carolina at Chapel Hill, NC 27599, USA</b><br/>3 HP Labs, Palo Alto, CA 94304, USA <br/><b>Center for Research in Intelligent Systems, University of California, Riverside, CA 92521, USA</b></td><td>('1803478', 'Songfan Yang', 'songfan yang')<br/>('39776603', 'Le An', 'le an')<br/>('1784929', 'Mehran Kafai', 'mehran kafai')<br/>('1707159', 'Bir Bhanu', 'bir bhanu')</td><td>syang@scu.edu.cn, lan004@unc.edu, mehran.kafai@hp.com, bhanu@cris.ucr.edu +</td></tr><tr><td>5f453a35d312debfc993d687fd0b7c36c1704b16</td><td><b>Clemson University</b><br/>TigerPrints +<br/>All Theses +<br/>12-2015 +<br/>Theses +<br/>A Training Assistant Tool for the Automated Visual +<br/>Inspection System +<br/>Follow this and additional works at: http://tigerprints.clemson.edu/all_theses +<br/>Part of the Electrical and Computer Engineering Commons +<br/>Recommended Citation +<br/>Ramaraj, Mohan Karthik, "A Training Assistant Tool for the Automated Visual Inspection System" (2015). All Theses. Paper 2285. +<br/>This Thesis is brought to you for free and open access by the Theses at TigerPrints. It has been accepted for inclusion in All Theses by an authorized +</td><td>('4154752', 'Mohan Karthik Ramaraj', 'mohan karthik ramaraj')</td><td>Clemson University, rmohankarthik91@gmail.com +<br/>administrator of TigerPrints. For more information, please contact awesole@clemson.edu. </td></tr><tr><td>5fc664202208aaf01c9b62da5dfdcd71fdadab29</td><td>arXiv:1504.05308v1 [cs.CV] 21 Apr 2015 </td><td></td><td></td></tr><tr><td>5fac62a3de11125fc363877ba347122529b5aa50</td><td>AMTnet: Action-Micro-Tube Regression by <br/>End-to-end Trainable Deep Architecture @@ -6451,7 +7703,20 @@ <br/>in the Continuous Pose Space <br/><b>Boston University, USA</b><br/>2 Disney Research Pittsburgh, USA </td><td>('1702188', 'Kun He', 'kun he')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')</td><td>{hekun,sclaroff}@cs.bu.edu, lsigal@disneyresearch.com -</td></tr><tr><td>33ac7fd3a622da23308f21b0c4986ae8a86ecd2b</td><td>Building an On-Demand Avatar-Based Health Intervention for Behavior Change +</td></tr><tr><td>33548531f9ed2ce6f87b3a1caad122c97f1fd2e9</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 104 – No.2, October 2014 +<br/>Facial Expression Recognition in Video using +<br/>Adaboost and SVM +<br/>Surabhi Prabhakar +<br/>Department of CSE +<br/><b>Amity University</b><br/>Noida, India +<br/>Jaya Sharma +<br/>Shilpi Gupta +<br/>Department of CSE +<br/>Department of CSE +<br/><b>Amity University</b><br/>Noida, India +<br/><b>Amity University</b><br/>Noida, India +</td><td></td><td></td></tr><tr><td>33ac7fd3a622da23308f21b0c4986ae8a86ecd2b</td><td>Building an On-Demand Avatar-Based Health Intervention for Behavior Change <br/>School of Computing and Information Sciences <br/><b>Florida International University</b><br/>Miami, FL, 33199, USA <br/>Department of Computer Science @@ -6507,6 +7772,12 @@ <br/>Phone: 650-428-1805,650-723-5499 <br/>Fax: 650-725-2472 </td><td></td><td>brave,nass@stanford.edu +</td></tr><tr><td>3328413ee9944de1cc7c9c1d1bf2fece79718ba1</td><td>Co-Training of Audio and Video Representations +<br/>from Self-Supervised Temporal Synchronization +<br/><b>Dartmouth College</b><br/>Facebook Research +<br/><b>Dartmouth College</b></td><td>('3443095', 'Bruno Korbar', 'bruno korbar')<br/>('1687325', 'Du Tran', 'du tran')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')</td><td>bruno.18@dartmouth.edu +<br/>trandu@fb.com +<br/>LT@dartmouth.edu </td></tr><tr><td>3399f8f0dff8fcf001b711174d29c9d4fde89379</td><td>Face R-CNN <br/>Tencent AI Lab, China </td><td>('39049654', 'Hao Wang', 'hao wang')</td><td>{hawelwang,michaelzfli,denisji,yitongwang}@tencent.com @@ -6533,10 +7804,12 @@ <br/>gshine@stanford.edu <br/>chriseng@stanford.edu </td></tr><tr><td>33402ee078a61c7d019b1543bb11cc127c2462d2</td><td>Self-Supervised Video Representation Learning With Odd-One-Out Networks -<br/><b>ACRV, The Australian National University University of Oxford QUVA Lab, University of Amsterdam</b></td><td>('1688071', 'Basura Fernando', 'basura fernando')</td><td></td></tr><tr><td>33ae696546eed070717192d393f75a1583cd8e2c</td><td></td><td></td><td></td></tr><tr><td>33f2b44742cc828347ccc5ec488200c25838b664</td><td>Pooling the Convolutional Layers in Deep ConvNets for Action Recognition +<br/><b>ACRV, The Australian National University University of Oxford QUVA Lab, University of Amsterdam</b></td><td>('1688071', 'Basura Fernando', 'basura fernando')</td><td></td></tr><tr><td>33aa980544a9d627f305540059828597354b076c</td><td></td><td></td><td></td></tr><tr><td>33ae696546eed070717192d393f75a1583cd8e2c</td><td></td><td></td><td></td></tr><tr><td>33f2b44742cc828347ccc5ec488200c25838b664</td><td>Pooling the Convolutional Layers in Deep ConvNets for Action Recognition <br/><b>School of Computer Science and Technology, Tianjin University, China</b><br/><b>School of Computer and Information, Hefei University of Technology, China</b></td><td>('2905510', 'Shichao Zhao', 'shichao zhao')<br/>('1732242', 'Yanbin Liu', 'yanbin liu')<br/>('2302512', 'Yahong Han', 'yahong han')<br/>('2248826', 'Richang Hong', 'richang hong')</td><td>{zhaoshichao, csyanbin, yahong}@tju.edu.cn, hongrc.hfut@gmail.com </td></tr><tr><td>3393459600368be2c4c9878a3f65a57dcc0c2cfa</td><td>Eigen-PEP for Video Face Recognition -<br/><b>Stevens Institute of Technology Adobe Systems Inc</b></td><td>('3131569', 'Haoxiang Li', 'haoxiang li')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('1720987', 'Xiaohui Shen', 'xiaohui shen')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')</td><td></td></tr><tr><td>334d6c71b6bce8dfbd376c4203004bd4464c2099</td><td>BICONVEX RELAXATION FOR SEMIDEFINITE PROGRAMMING IN +<br/><b>Stevens Institute of Technology Adobe Systems Inc</b></td><td>('3131569', 'Haoxiang Li', 'haoxiang li')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('1720987', 'Xiaohui Shen', 'xiaohui shen')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')</td><td></td></tr><tr><td>3352426a67eabe3516812cb66a77aeb8b4df4d1b</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 4, NO. 5, APRIL 2015 +<br/>Joint Multi-view Face Alignment in the Wild +</td><td>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('2814229', 'George Trigeorgis', 'george trigeorgis')<br/>('47943220', 'Yuxiang Zhou', 'yuxiang zhou')</td><td></td></tr><tr><td>334d6c71b6bce8dfbd376c4203004bd4464c2099</td><td>BICONVEX RELAXATION FOR SEMIDEFINITE PROGRAMMING IN <br/>COMPUTER VISION </td><td>('36861219', 'Sohil Shah', 'sohil shah')<br/>('1746575', 'Christoph Studer', 'christoph studer')<br/>('1962083', 'Tom Goldstein', 'tom goldstein')</td><td></td></tr><tr><td>33695e0779e67c7722449e9a3e2e55fde64cfd99</td><td>Riemannian Coding and Dictionary Learning: Kernels to the Rescue <br/><b>Australian National University and NICTA</b><br/>While sparse coding on non-flat Riemannian manifolds has recently become @@ -6623,7 +7896,9 @@ <br/>Facial Expression Analysis using Deep Learning <br/><b>M.Tech Student, SSG Engineering College, Odisha, India</b><br/>---------------------------------------------------------------------***--------------------------------------------------------------------- <br/>examination structures need to analyse the facial exercises -</td><td>('13518951', 'Raman Patel', 'raman patel')</td><td></td></tr><tr><td>33403e9b4bbd913ae9adafc6751b52debbd45b0e</td><td></td><td></td><td></td></tr><tr><td>33ad23377eaead8955ed1c2b087a5e536fecf44e</td><td>Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling +</td><td>('13518951', 'Raman Patel', 'raman patel')</td><td></td></tr><tr><td>33403e9b4bbd913ae9adafc6751b52debbd45b0e</td><td></td><td></td><td></td></tr><tr><td>33ef419dffef85443ec9fe89a93f928bafdc922e</td><td>SelfKin: Self Adjusted Deep Model For +<br/>Kinship Verification +<br/><b>Faculty of Engineering, Bar-Ilan University, Israel</b></td><td>('32450996', 'Eran Dahan', 'eran dahan')<br/>('1926432', 'Yosi Keller', 'yosi keller')</td><td></td></tr><tr><td>33ad23377eaead8955ed1c2b087a5e536fecf44e</td><td>Augmenting CRFs with Boltzmann Machine Shape Priors for Image Labeling <br/>∗ indicates equal contribution </td><td>('2177037', 'Andrew Kae', 'andrew kae')<br/>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')<br/>('1697141', 'Honglak Lee', 'honglak lee')</td><td>1 University of Massachusetts, Amherst, MA, USA, {akae,elm}@cs.umass.edu <br/>2 University of Michigan, Ann Arbor, MI, USA, {kihyuks,honglak}@umich.edu @@ -6722,7 +7997,12 @@ <br/>© Impact Journals <br/>PERFORMANCE EVALUATION OF ILLUMINATION NORMALIZATION TECHNIQUES <br/>FOR FACE RECOGNITION -<br/><b>PSG College of Technology, Coimbatore, Tamil Nadu, India</b></td><td></td><td></td></tr><tr><td>0568fc777081cbe6de95b653644fec7b766537b2</td><td>Learning Expressionlets on Spatio-Temporal Manifold for Dynamic Facial +<br/><b>PSG College of Technology, Coimbatore, Tamil Nadu, India</b></td><td></td><td></td></tr><tr><td>05891725f5b27332836cf058f04f18d74053803f</td><td>One-shot Action Localization by Learning Sequence Matching Network +<br/><b>The Australian National University</b><br/><b>ShanghaiTech University</b><br/>Fatih Porikli +<br/><b>The Australian National University</b></td><td>('51050729', 'Hongtao Yang', 'hongtao yang')<br/>('33913193', 'Xuming He', 'xuming he')</td><td>u5226028@anu.edu.au +<br/>hexm@shanghaitech.edu.cn +<br/>fatih.porikli@anu.edu.au +</td></tr><tr><td>0568fc777081cbe6de95b653644fec7b766537b2</td><td>Learning Expressionlets on Spatio-Temporal Manifold for Dynamic Facial <br/>Expression Recognition <br/>1Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), <br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China</b><br/><b>University of Oulu, Finland</b></td><td>('1730228', 'Mengyi Liu', 'mengyi liu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('3373117', 'Ruiping Wang', 'ruiping wang')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>mengyi.liu@vipl.ict.ac.cn, {sgshan, wangruiping, xlchen}@ict.ac.cn @@ -7061,11 +8341,15 @@ <br/>lips, eyelids, and eyebrows as well as facial skin texture patterns (Pantic & Rothkrantz, <br/>2000). Typical facial expressions last for a few seconds, normally between 250 milliseconds <br/>and five seconds (Fasel & Luettin, 2003). According to psychologists Ekman and Friesen -</td><td>('2647218', 'Bogdan J. Matuszewski', 'bogdan j. matuszewski')<br/>('2343120', 'Wei Quan', 'wei quan')</td><td></td></tr><tr><td>05a7be10fa9af8fb33ae2b5b72d108415519a698</td><td>Multilayer and Multimodal Fusion of Deep Neural Networks +</td><td>('2647218', 'Bogdan J. Matuszewski', 'bogdan j. matuszewski')<br/>('2343120', 'Wei Quan', 'wei quan')</td><td></td></tr><tr><td>052f994898c79529955917f3dfc5181586282cf8</td><td>Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos +<br/>1NEC Labs America +<br/>2UC Merced +<br/><b>Dalian University of Technology</b><br/>4UC San Diego +</td><td>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')</td><td></td></tr><tr><td>05a7be10fa9af8fb33ae2b5b72d108415519a698</td><td>Multilayer and Multimodal Fusion of Deep Neural Networks <br/>for Video Classification <br/>NVIDIA </td><td>('2214162', 'Xiaodong Yang', 'xiaodong yang')</td><td>{xiaodongy, pmolchanov, jkautz}@nvidia.com -</td></tr><tr><td>05318a267226f6d855d83e9338eaa9e718b2a8dd</td><td>_______________________________________________________PROCEEDING OF THE 16TH CONFERENCE OF FRUCT ASSOCIATION +</td></tr><tr><td>050a149051a5d268fcc5539e8b654c2240070c82</td><td>MAGISTERSKÉ A DOKTORSKÉSTUDIJNÍ PROGRAMY31. 5. 2018SBORNÍKSTUDENTSKÁ VĚDECKÁ KONFERENCE </td><td></td><td></td></tr><tr><td>05318a267226f6d855d83e9338eaa9e718b2a8dd</td><td>_______________________________________________________PROCEEDING OF THE 16TH CONFERENCE OF FRUCT ASSOCIATION <br/>Age Estimation from Face Images: Challenging <br/>Problem for Audience Measurement Systems <br/><b>Yaroslavl State University</b><br/>Russia @@ -7086,6 +8370,10 @@ <br/>1 Tel.: 023-65112784, fax: 023-65112784 <br/>Received: 26 April 2013 /Accepted: 14 June 2013 /Published: 25 June 2013 </td><td>('2623870', 'Lifang Zhou', 'lifang zhou')<br/>('1713814', 'Bin Fang', 'bin fang')<br/>('1964987', 'Weisheng Li', 'weisheng li')<br/>('2103166', 'Lidou Wang', 'lidou wang')</td><td>1 E-mail: zhoulf@cqupt.edu.cn +</td></tr><tr><td>053931267af79a89791479b18d1b9cde3edcb415</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Attributes for Improved Attributes: A Multi-Task Network +<br/>Utilizing Implicit and Explicit Relationships for Facial Attribute Classification +<br/><b>University of Maryland, College Park</b><br/><b>College Park, MD</b></td><td>('3351637', 'Emily M. Hand', 'emily m. hand')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{emhand, rama}@umiacs.umd.edu </td></tr><tr><td>05f3d1e9fb254b275354ca69018e9ed321dd8755</td><td>Face Recognition using Optimal Representation <br/>Ensemble <br/><b>NICTA , Queensland Research Laboratory, QLD, Australia</b><br/><b>Grif th University, QLD, Australia</b><br/><b>University of Adelaide, SA, Australia</b><br/>29·4·2013 @@ -7093,6 +8381,11 @@ <br/>Partial Face Recognition: An Alignment Free Approach <br/>Department of Computer Science and Engineering <br/><b>Michigan State University, East Lansing, MI 48824, U.S.A</b></td><td>('40397682', 'Shengcai Liao', 'shengcai liao')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td>{scliao,jain}@cse.msu.edu +</td></tr><tr><td>9d58e8ab656772d2c8a99a9fb876d5611fe2fe20</td><td>Beyond Temporal Pooling: Recurrence and Temporal +<br/>Convolutions for Gesture Recognition in Video +<br/>{lionel.pigou,aaron.vandenoord,sander.dieleman, +<br/><b>Ghent University</b><br/>February 11, 2016 +</td><td>('2660640', 'Lionel Pigou', 'lionel pigou')<br/>('48373216', 'Sander Dieleman', 'sander dieleman')<br/>('10182287', 'Mieke Van Herreweghe', 'mieke van herreweghe')</td><td>mieke.vanherreweghe, joni.dambre}@ugent.be </td></tr><tr><td>9d8ff782f68547cf72b7f3f3beda9dc3e8ecfce6</td><td>International Journal of Pattern Recognition <br/>and Arti¯cial Intelligence <br/>Vol. 26, No. 1 (2012) 1250002 (9 pages) @@ -7176,7 +8469,9 @@ <br/><b>Savitribai Phule Pune University</b><br/><b>D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune</b><br/>Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India <br/><b>D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune</b><br/>Computer Department, D.Y.PIET, Pimpri, Pune-18, MH, India <br/>presents -</td><td>('15731441', 'Shital Shinde', 'shital shinde')<br/>('3392505', 'Archana Chaugule', 'archana chaugule')</td><td></td></tr><tr><td>9d941a99e6578b41e4e32d57ece580c10d578b22</td><td>Sensors 2015, 15, 4326-4352; doi:10.3390/s150204326 +</td><td>('15731441', 'Shital Shinde', 'shital shinde')<br/>('3392505', 'Archana Chaugule', 'archana chaugule')</td><td></td></tr><tr><td>9d57c4036a0e5f1349cd11bc342ac515307b6720</td><td>Landmark Weighting for 3DMM Shape Fitting +<br/><b>aSchool of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China</b><br/><b>bCVSSP, University of Surrey, Guildford, GU2 7XH, UK</b><br/>A B S T R A C T +</td><td>('51232704', 'Yu Yanga', 'yu yanga')<br/>('37020604', 'Xiao-Jun Wu', 'xiao-jun wu')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td></td></tr><tr><td>9d941a99e6578b41e4e32d57ece580c10d578b22</td><td>Sensors 2015, 15, 4326-4352; doi:10.3390/s150204326 <br/>OPEN ACCESS <br/>sensors <br/>ISSN 1424-8220 @@ -7215,6 +8510,9 @@ <br/>Intelligence <br/><b>Cyprus University of Technology</b><br/>P.O Box 50329, Lemesos, 3066, Cyprus </td><td>('1830709', 'Andreas Lanitis', 'andreas lanitis')</td><td>andreas.lanitis@cut.ac.cy +</td></tr><tr><td>9db4b25df549555f9ffd05962b5adf2fd9c86543</td><td>Nonlinear 3D Face Morphable Model +<br/>Department of Computer Science and Engineering +<br/><b>Michigan State University, East Lansing MI</b></td><td>('1849929', 'Luan Tran', 'luan tran')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>{tranluan, liuxm}@msu.edu </td></tr><tr><td>9d06d43e883930ddb3aa6fe57c6a865425f28d44</td><td>Clustering Appearances of Objects Under Varying Illumination Conditions <br/>Computer Science & Engineering <br/><b>University of California at San Diego</b><br/><b>cid:1) Honda Research Institute</b><br/>David Kriegman @@ -7244,7 +8542,35 @@ <br/>Regression for Object Part Localization <br/>Center for Biometrics and Security Research & National Laboratory <br/><b>of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China</b></td><td>('1721677', 'Junjie Yan', 'junjie yan')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1708973', 'Yang Yang', 'yang yang')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{jjyan,zlei,yang.yang,szli}@nlpr.ia.ac.cn -</td></tr><tr><td>9c25e89c80b10919865b9c8c80aed98d223ca0c6</td><td>GENDER PREDICTION BY GAIT ANALYSIS BASED ON TIME SERIES VARIATION OF +</td></tr><tr><td>9ca7899338129f4ba6744f801e722d53a44e4622</td><td>Deep Neural Networks Regularization for Structured +<br/>Output Prediction +<br/>Soufiane Belharbi∗ +<br/>INSA Rouen, LITIS +<br/>76000 Rouen, France +<br/>INSA Rouen, LITIS +<br/>76000 Rouen, France +<br/>INSA Rouen, LITIS +<br/>76000 Rouen, France +<br/>INSA Rouen, LITIS +<br/>76000 Rouen, France +<br/>Normandie Univ, UNIROUEN, UNIHAVRE, +<br/>Normandie Univ, UNIROUEN, UNIHAVRE, +<br/>Normandie Univ, UNIROUEN, UNIHAVRE, +<br/>Normandie Univ, UNIROUEN, UNIHAVRE, +</td><td>('1712446', 'Clément Chatelain', 'clément chatelain')<br/>('1782268', 'Romain Hérault', 'romain hérault')<br/>('37078795', 'Sébastien Adam', 'sébastien adam')</td><td>soufiane.belharbi@insa-rouen.fr +<br/>romain.herault@insa-rouen.fr +<br/>clement.chatelain@insa-rouen.fr +<br/>sebastien.adam@univ-rouen.fr +</td></tr><tr><td>9c1664f69d0d832e05759e8f2f001774fad354d6</td><td>Action representations in robotics: A +<br/>taxonomy and systematic classification +<br/>Journal Title +<br/>XX(X):1–32 +<br/>c(cid:13)The Author(s) 2016 +<br/>Reprints and permission: +<br/>sagepub.co.uk/journalsPermissions.nav +<br/>DOI: 10.1177/ToBeAssigned +<br/>www.sagepub.com/ +</td><td>('33237072', 'Philipp Zech', 'philipp zech')<br/>('2898615', 'Erwan Renaudo', 'erwan renaudo')<br/>('36081156', 'Simon Haller', 'simon haller')<br/>('46447747', 'Xiang Zhang', 'xiang zhang')</td><td></td></tr><tr><td>9c25e89c80b10919865b9c8c80aed98d223ca0c6</td><td>GENDER PREDICTION BY GAIT ANALYSIS BASED ON TIME SERIES VARIATION OF <br/>JOINT POSITIONS <br/>Dept. of Computer Science <br/>School of Science and Technology @@ -7261,7 +8587,11 @@ <br/>© 2009 Science Publications <br/>Boosting Kernel Discriminative Common Vectors for Face Recognition <br/>1Department of Computer Science and Engineering, -<br/><b>SRM University, Kattankulathur, Chennai-603 203, Tamilnadu, India</b><br/><b>Bharathidasan University, Trichy, India</b></td><td>('34608395', 'C. Lakshmi', 'c. lakshmi')<br/>('2594379', 'M. Ponnavaikko', 'm. ponnavaikko')</td><td></td></tr><tr><td>9c781f7fd5d8168ddae1ce5bb4a77e3ca12b40b6</td><td> International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 +<br/><b>SRM University, Kattankulathur, Chennai-603 203, Tamilnadu, India</b><br/><b>Bharathidasan University, Trichy, India</b></td><td>('34608395', 'C. Lakshmi', 'c. lakshmi')<br/>('2594379', 'M. Ponnavaikko', 'm. ponnavaikko')</td><td></td></tr><tr><td>9c065dfb26ce280610a492c887b7f6beccf27319</td><td>Learning from Video and Text via Large-Scale Discriminative Clustering +<br/>1 ´Ecole Normale Sup´erieure +<br/>2Inria +<br/>3CIIRC +</td><td>('19200186', 'Antoine Miech', 'antoine miech')<br/>('2285263', 'Jean-Baptiste Alayrac', 'jean-baptiste alayrac')<br/>('2329288', 'Piotr Bojanowski', 'piotr bojanowski')<br/>('1785596', 'Ivan Laptev', 'ivan laptev')<br/>('1782755', 'Josef Sivic', 'josef sivic')</td><td></td></tr><tr><td>9c781f7fd5d8168ddae1ce5bb4a77e3ca12b40b6</td><td> International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 <br/> Volume: 03 Issue: 07 | July-2016 www.irjet.net p-ISSN: 2395-0072 <br/>Attribute Based Face Classification Using Support Vector Machine <br/><b>Research Scholar, PSGR Krishnammal College for Women, Coimbatore</b><br/><b>PSGR Krishnammal College for Women, Coimbatore</b></td><td></td><td></td></tr><tr><td>9c373438285101d47ab9332cdb0df6534e3b93d1</td><td>Occupancy Detection in Vehicles Using Fisher Vector @@ -7271,7 +8601,26 @@ </td><td>('1762503', 'Yusuf Artan', 'yusuf artan')<br/>('5942563', 'Peter Paul', 'peter paul')</td><td>Yusuf.Artan@xerox.com <br/>Peter.Paul@xerox.com </td></tr><tr><td>9cbb6e42a35f26cf1d19f4875cd7f6953f10b95d</td><td>Expression Recognition with Ri-HOG Cascade -<br/><b>Graduate School of System Informatics, Kobe University, Kobe, 657-8501, Japan</b><br/><b>RIEB, Kobe University, Kobe, 657-8501, Japan</b></td><td>('2866465', 'Jinhui Chen', 'jinhui chen')<br/>('2834542', 'Zhaojie Luo', 'zhaojie luo')<br/>('1744026', 'Tetsuya Takiguchi', 'tetsuya takiguchi')<br/>('1678564', 'Yasuo Ariki', 'yasuo ariki')</td><td></td></tr><tr><td>9c4cc11d0df2de42d6593f5284cfdf3f05da402a</td><td>Appears in the 14th International Conference on Pattern Recognition, ICPR’98, Queensland, Australia, August 17-20, 1998. +<br/><b>Graduate School of System Informatics, Kobe University, Kobe, 657-8501, Japan</b><br/><b>RIEB, Kobe University, Kobe, 657-8501, Japan</b></td><td>('2866465', 'Jinhui Chen', 'jinhui chen')<br/>('2834542', 'Zhaojie Luo', 'zhaojie luo')<br/>('1744026', 'Tetsuya Takiguchi', 'tetsuya takiguchi')<br/>('1678564', 'Yasuo Ariki', 'yasuo ariki')</td><td></td></tr><tr><td>9ce0d64125fbaf625c466d86221505ad2aced7b1</td><td>Saliency Based Framework for Facial Expression +<br/>Recognition +<br/>To cite this version: +<br/>Facial Expression Recognition. Frontiers of Computer Science, 2017, <10.1007/s11704-017-6114-9>. +<br/><hal-01546192> +<br/>HAL Id: hal-01546192 +<br/>https://hal.archives-ouvertes.fr/hal-01546192 +<br/>Submitted on 23 Jun 2017 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('1943666', 'Rizwan Ahmed Khan', 'rizwan ahmed khan')<br/>('39469581', 'Alexandre Meyer', 'alexandre meyer')<br/>('1971616', 'Hubert Konik', 'hubert konik')<br/>('1768560', 'Saïda Bouakaz', 'saïda bouakaz')<br/>('1943666', 'Rizwan Ahmed Khan', 'rizwan ahmed khan')<br/>('39469581', 'Alexandre Meyer', 'alexandre meyer')<br/>('1971616', 'Hubert Konik', 'hubert konik')<br/>('1768560', 'Saïda Bouakaz', 'saïda bouakaz')</td><td></td></tr><tr><td>9c4cc11d0df2de42d6593f5284cfdf3f05da402a</td><td>Appears in the 14th International Conference on Pattern Recognition, ICPR’98, Queensland, Australia, August 17-20, 1998. <br/>Enhanced Fisher Linear Discriminant Models for Face Recognition <br/><b>George Mason University</b><br/><b>University Drive, Fairfax, VA 22030-4444, USA</b><br/> </td><td>('39664966', 'Chengjun Liu', 'chengjun liu')<br/>('1781577', 'Harry Wechsler', 'harry wechsler')</td><td>@cs.gmu.edu @@ -7385,7 +8734,9 @@ </td><td>('40845190', 'L. Jason Anastasopoulos', 'l. jason anastasopoulos')<br/>('2007721', 'Dhruvil Badani', 'dhruvil badani')<br/>('2647307', 'Crystal Lee', 'crystal lee')<br/>('2361255', 'Shiry Ginosar', 'shiry ginosar')<br/>('40411568', 'Jake Williams', 'jake williams')</td><td></td></tr><tr><td>02e133aacde6d0977bca01ffe971c79097097b7f</td><td></td><td></td><td></td></tr><tr><td>02567fd428a675ca91a0c6786f47f3e35881bcbd</td><td>ACCEPTED BY IEEE TIP <br/>Deep Label Distribution Learning <br/>With Label Ambiguity -</td><td>('2226422', 'Bin-Bin Gao', 'bin-bin gao')<br/>('1694501', 'Chao Xing', 'chao xing')<br/>('3407628', 'Chen-Wei Xie', 'chen-wei xie')<br/>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('1735299', 'Xin Geng', 'xin geng')</td><td></td></tr><tr><td>029b53f32079063047097fa59cfc788b2b550c4b</td><td></td><td></td><td></td></tr><tr><td>02bd665196bd50c4ecf05d6852a4b9ba027cd9d0</td><td></td><td></td><td></td></tr><tr><td>026b5b8062e5a8d86c541cfa976f8eee97b30ab8</td><td>MDLFace: Memorability Augmented Deep Learning for Video Face Recognition +</td><td>('2226422', 'Bin-Bin Gao', 'bin-bin gao')<br/>('1694501', 'Chao Xing', 'chao xing')<br/>('3407628', 'Chen-Wei Xie', 'chen-wei xie')<br/>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('1735299', 'Xin Geng', 'xin geng')</td><td></td></tr><tr><td>02f4b900deabbe7efa474f2815dc122a4ddb5b76</td><td>Local and Global Optimization Techniques in Graph-based Clustering +<br/><b>The University of Tokyo, Japan</b></td><td>('11682769', 'Daiki Ikami', 'daiki ikami')<br/>('2759239', 'Toshihiko Yamasaki', 'toshihiko yamasaki')<br/>('1712839', 'Kiyoharu Aizawa', 'kiyoharu aizawa')</td><td>{ikami, yamasaki, aizawa}@hal.t.u-tokyo.ac.jp +</td></tr><tr><td>029b53f32079063047097fa59cfc788b2b550c4b</td><td></td><td></td><td></td></tr><tr><td>02bd665196bd50c4ecf05d6852a4b9ba027cd9d0</td><td></td><td></td><td></td></tr><tr><td>026b5b8062e5a8d86c541cfa976f8eee97b30ab8</td><td>MDLFace: Memorability Augmented Deep Learning for Video Face Recognition <br/>IIIT-Delhi, India </td><td>('1931069', 'Gaurav Goswami', 'gaurav goswami')<br/>('1875774', 'Romil Bhardwaj', 'romil bhardwaj')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td>{gauravgs,romil11092,rsingh,mayank}@iiitd.ac.in </td></tr><tr><td>0235b2d2ae306b7755483ac4f564044f46387648</td><td>Recognition of Facial Attributes @@ -7448,6 +8799,11 @@ <br/>1Department of Electrical and Computer Engineering and the Center for Automation Research, <br/><b>UMIACS, University of Maryland, College Park, MD</b><br/><b>Rutgers, The State University of New Jersey, 508 CoRE, 94 Brett Rd, Piscataway, NJ</b></td><td>('3152615', 'Upal Mahbub', 'upal mahbub')<br/>('40599829', 'Sayantan Sarkar', 'sayantan sarkar')</td><td>{umahbub, ssarkar2, rama}@umiacs.umd.edu <br/>vishal.m.patel@rutgers.edu∗ +</td></tr><tr><td>a40edf6eb979d1ddfe5894fac7f2cf199519669f</td><td>Improving Facial Attribute Prediction using Semantic Segmentation +<br/>Center for Research in Computer Vision +<br/><b>University of Central Florida</b></td><td>('3222250', 'Mahdi M. Kalayeh', 'mahdi m. kalayeh')<br/>('40206014', 'Boqing Gong', 'boqing gong')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>Mahdi@eecs.ucf.edu +<br/>bgong@crcv.ucf.edu +<br/>shah@crcv.ucf.edu </td></tr><tr><td>a46283e90bcdc0ee35c680411942c90df130f448</td><td></td><td></td><td></td></tr><tr><td>a4a5ad6f1cc489427ac1021da7d7b70fa9a770f2</td><td>Yudistira and Kurita EURASIP Journal on Image and Video <br/>Processing (2017) 2017:85 <br/>DOI 10.1186/s13640-017-0235-9 @@ -7582,7 +8938,13 @@ <br/>ASL4GUP 2017 <br/>Held in conjunction with IEEE FG 2017, in May 30, 2017, <br/>Washington DC, USA -</td><td></td><td></td></tr><tr><td>a3017bb14a507abcf8446b56243cfddd6cdb542b</td><td>Face Localization and Recognition in Varied +</td><td></td><td></td></tr><tr><td>a3d8b5622c4b9af1f753aade57e4774730787a00</td><td>Pose-Aware Person Recognition +<br/>Anoop Namboodiri (cid:63) +<br/>(cid:63) CVIT, IIIT Hyderabad, India +<br/>† Facebook AI Research +</td><td>('37956314', 'Vijay Kumar', 'vijay kumar')<br/>('2210374', 'Manohar Paluri', 'manohar paluri')<br/>('1694502', 'C. V. Jawahar', 'c. v. jawahar')</td><td></td></tr><tr><td>a322479a6851f57a3d74d017a9cb6d71395ed806</td><td>Towards Pose Invariant Face Recognition in the Wild +<br/><b>National University of Singapore</b><br/><b>National University of Defense Technology</b><br/><b>Nanyang Technological University</b><br/>4Panasonic R&D Center Singapore +<br/><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b><br/><b>Qihoo 360 AI Institute</b></td><td>('2668358', 'Sugiri Pranata', 'sugiri pranata')<br/>('3493398', 'Shengmei Shen', 'shengmei shen')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('46509407', 'Jian Zhao', 'jian zhao')<br/>('5524736', 'Yu Cheng', 'yu cheng')<br/>('33419682', 'Lin Xiong', 'lin xiong')<br/>('2757639', 'Jianshu Li', 'jianshu li')<br/>('40345914', 'Fang Zhao', 'fang zhao')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')</td><td></td></tr><tr><td>a3017bb14a507abcf8446b56243cfddd6cdb542b</td><td>Face Localization and Recognition in Varied <br/>Expressions and Illumination <br/>Hui-Yu Huang, Shih-Hang Hsu <br/> @@ -7603,7 +8965,11 @@ </td><td>('1848243', 'Erjin Zhou', 'erjin zhou')<br/>('2695115', 'Zhimin Cao', 'zhimin cao')<br/>('2274228', 'Qi Yin', 'qi yin')</td><td>zej@megvii.com <br/>czm@megvii.com <br/>yq@megvii.com -</td></tr><tr><td>a3dc109b1dff3846f5a2cc1fe2448230a76ad83f</td><td>J.Savitha et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 722-731 +</td></tr><tr><td>a301ddc419cbd900b301a95b1d9e4bb770afc6a3</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>DECK: Discovering Event Composition Knowledge from +<br/>Web Images for Zero-Shot Event Detection and Recounting in Videos +<br/><b>University of Southern California</b><br/><b>IIIS, Tsinghua University</b><br/>‡ Google Research +</td><td>('2551285', 'Chuang Gan', 'chuang gan')<br/>('1726241', 'Chen Sun', 'chen sun')</td><td></td></tr><tr><td>a3dc109b1dff3846f5a2cc1fe2448230a76ad83f</td><td>J.Savitha et al, International Journal of Computer Science and Mobile Computing, Vol.4 Issue.4, April- 2015, pg. 722-731 <br/>Available Online at www.ijcsmc.com <br/>International Journal of Computer Science and Mobile Computing <br/>A Monthly Journal of Computer Science and Information Technology @@ -7616,6 +8982,23 @@ <br/><b>Ph.D Research Scholar, Karpagam University, Coimbatore, Tamil Nadu, India</b><br/>Dr. A.V.Senthil Kumar <br/><b>Director, Hindustan College of Arts and Science, Coimbatore, Tamil Nadu, India</b></td><td></td><td>Email: savitha.sanjay1@gmail.com <br/>Email: avsenthilkumar@gmail.com +</td></tr><tr><td>a3f69a073dcfb6da8038607a9f14eb28b5dab2db</td><td>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18) +<br/>1184 +</td><td></td><td></td></tr><tr><td>a38045ed82d6800cbc7a4feb498e694740568258</td><td>UNLV Theses, Dissertations, Professional Papers, and Capstones +<br/>5-2010 +<br/>African American and Caucasian males' evaluation +<br/>of racialized female facial averages +<br/>Rhea M. Watson +<br/><b>University of Nevada Las Vegas</b><br/>Follow this and additional works at: http://digitalscholarship.unlv.edu/thesesdissertations +<br/>Part of the Cognition and Perception Commons, Race and Ethnicity Commons, and the Social +<br/>Psychology Commons +<br/>Repository Citation +<br/>Watson, Rhea M., "African American and Caucasian males' evaluation of racialized female facial averages" (2010). UNLV Theses, +<br/>Dissertations, Professional Papers, and Capstones. 366. +<br/>http://digitalscholarship.unlv.edu/thesesdissertations/366 +</td><td></td><td>This Thesis is brought to you for free and open access by Digital Scholarship@UNLV. It has been accepted for inclusion in UNLV Theses, Dissertations, +<br/>Professional Papers, and Capstones by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact +<br/>digitalscholarship@unlv.edu. </td></tr><tr><td>a3f684930c5c45fcb56a2b407d26b63879120cbf</td><td>LPM for Fast Action Recognition with Large Number of Classes <br/>School of Electrical Engineering and Computer Scinece <br/><b>University of Ottawa, Ottawa, On, Canada</b><br/>Department of Electronics and Information Engineering @@ -7689,12 +9072,15 @@ <br/>3https://github.com/fshi/actionMBH </td><td>('36925389', 'Feng Shi', 'feng shi')<br/>('1745632', 'Emil Petriu', 'emil petriu')</td><td>fshi98@gmail.com, {laganier, petriu}@site.uottawa.ca <br/>zhenhaiyu@mail.hust.edu.cn -</td></tr><tr><td>a33f20773b46283ea72412f9b4473a8f8ad751ae</td><td></td><td></td><td></td></tr><tr><td>a3a6a6a2eb1d32b4dead9e702824375ee76e3ce7</td><td>Multiple Local Curvature Gabor Binary +</td></tr><tr><td>a3f78cc944ac189632f25925ba807a0e0678c4d5</td><td>Action Recognition in Realistic Sports Videos +</td><td>('1799979', 'Khurram Soomro', 'khurram soomro')<br/>('40029556', 'Amir Roshan Zamir', 'amir roshan zamir')</td><td></td></tr><tr><td>a33f20773b46283ea72412f9b4473a8f8ad751ae</td><td></td><td></td><td></td></tr><tr><td>a3a6a6a2eb1d32b4dead9e702824375ee76e3ce7</td><td>Multiple Local Curvature Gabor Binary <br/>Patterns for Facial Action Recognition <br/>Signal Processing Laboratory (LTS5), <br/>´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland </td><td>('2383305', 'Nuri Murat Arar', 'nuri murat arar')<br/>('1710257', 'Jean-Philippe Thiran', 'jean-philippe thiran')</td><td>{anil.yuce,murat.arar,jean-philippe.thiran}@epfl.ch -</td></tr><tr><td>a32d4195f7752a715469ad99cb1e6ebc1a099de6</td><td>Hindawi Publishing Corporation +</td></tr><tr><td>a32c5138c6a0b3d3aff69bcab1015d8b043c91fb</td><td>Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/19/2018 +<br/>Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +<br/>Videoredaction:asurveyandcomparisonofenablingtechnologiesShaganSahAmeyaShringiRaymondPtuchaAaronBurryRobertLoceShaganSah,AmeyaShringi,RaymondPtucha,AaronBurry,RobertLoce,“Videoredaction:asurveyandcomparisonofenablingtechnologies,”J.Electron.Imaging26(5),051406(2017),doi:10.1117/1.JEI.26.5.051406. </td><td></td><td></td></tr><tr><td>a32d4195f7752a715469ad99cb1e6ebc1a099de6</td><td>Hindawi Publishing Corporation <br/>e Scientific World Journal <br/>Volume 2014, Article ID 749096, 10 pages <br/>http://dx.doi.org/10.1155/2014/749096 @@ -7856,7 +9242,15 @@ <br/><b>University of California at Berkeley</b><br/>Technical Report No. UCB/EECS-2012-52 <br/>http://www.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-52.html <br/>May 1, 2012 -</td><td></td><td></td></tr><tr><td>a3a97bb5131e7e67316b649bbc2432aaa1a6556e</td><td>Cogn Affect Behav Neurosci +</td><td></td><td></td></tr><tr><td>a36c8a4213251d3fd634e8893ad1b932205ad1ca</td><td>Videos from the 2013 Boston Marathon: +<br/>An Event Reconstruction Dataset for +<br/>Synchronization and Localization +<br/>CMU-LTI-018 +<br/><b>Language Technologies Institute</b><br/>School of Computer Science +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave., Pittsburgh, PA 15213 +<br/>www.lti.cs.cmu.edu +<br/>© October 1, 2016 +</td><td>('1915796', 'Junwei Liang', 'junwei liang')<br/>('47896638', 'Han Lu', 'han lu')<br/>('2927024', 'Shoou-I Yu', 'shoou-i yu')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')</td><td></td></tr><tr><td>a3a97bb5131e7e67316b649bbc2432aaa1a6556e</td><td>Cogn Affect Behav Neurosci <br/>DOI 10.3758/s13415-013-0170-x <br/>Role of the hippocampus and orbitofrontal cortex <br/>during the disambiguation of social cues in working memory @@ -7918,12 +9312,19 @@ <br/>Yining Wang (ynwang.yining@gmail.com) <br/>Zhulin Li (li-zl12@mails.tsinghua.edu.cn) <br/>Zhuowen Tu (ztu@ucsd.edu) -</td></tr><tr><td>b5cd9e5d81d14868f1a86ca4f3fab079f63a366d</td><td>Tag-based Video Retrieval by Embedding Semantic Content in a Continuous +</td></tr><tr><td>b5968e7bb23f5f03213178c22fd2e47af3afa04c</td><td>Multi-Human Parsing in the Wild +<br/><b>National University of Singapore</b><br/><b>Beijing Jiaotong University</b><br/>March 16, 2018 +</td><td>('2757639', 'Jianshu Li', 'jianshu li')<br/>('2263674', 'Yidong Li', 'yidong li')<br/>('46509407', 'Jian Zhao', 'jian zhao')<br/>('1715286', 'Terence Sim', 'terence sim')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>b5cd9e5d81d14868f1a86ca4f3fab079f63a366d</td><td>Tag-based Video Retrieval by Embedding Semantic Content in a Continuous <br/>Word Space <br/><b>University of Southern California</b><br/>Ram Nevatia <br/>Cees G.M. Snoek <br/><b>University of Amsterdam</b></td><td>('3407713', 'Arnav Agharwal', 'arnav agharwal')<br/>('3407447', 'Rama Kovvuri', 'rama kovvuri')</td><td>{agharwal,nkovvuri,nevatia}@usc.edu <br/>cgmsnoek@uva.nl +</td></tr><tr><td>b558be7e182809f5404ea0fcf8a1d1d9498dc01a</td><td>Bottom-up and top-down reasoning with convolutional latent-variable models +<br/>UC Irvine +<br/>UC Irvine +</td><td>('2894848', 'Peiyun Hu', 'peiyun hu')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td>peiyunh@ics.uci.edu +<br/>dramanan@ics.uci.edu </td></tr><tr><td>b5cd8151f9354ee38b73be1d1457d28e39d3c2c6</td><td>Finding Celebrities in Video <br/>Electrical Engineering and Computer Sciences <br/><b>University of California at Berkeley</b><br/>Technical Report No. UCB/EECS-2006-77 @@ -7935,7 +9336,7 @@ <br/>Significance of image representation for face verification <br/>Received: 29 August 2006 / Revised: 28 March 2007 / Accepted: 28 March 2007 / Published online: 1 May 2007 <br/>© Springer-Verlag London Limited 2007 -</td><td>('2627097', 'Anil Kumar Sao', 'anil kumar sao')<br/>('1783087', 'B. V. K. Vijaya Kumar', 'b. v. k. vijaya kumar')</td><td></td></tr><tr><td>b506aa23949b6d1f0c868ad03aaaeb5e5f7f6b57</td><td><b>UNIVERSITY OF CALIFORNIA</b><br/>RIVERSIDE +</td><td>('2627097', 'Anil Kumar Sao', 'anil kumar sao')<br/>('1783087', 'B. V. K. Vijaya Kumar', 'b. v. k. vijaya kumar')</td><td></td></tr><tr><td>b562def2624f59f7d3824e43ecffc990ad780898</td><td></td><td></td><td></td></tr><tr><td>b506aa23949b6d1f0c868ad03aaaeb5e5f7f6b57</td><td><b>UNIVERSITY OF CALIFORNIA</b><br/>RIVERSIDE <br/>Modeling Social and Temporal Context for Video Analysis <br/>A Dissertation submitted in partial satisfaction <br/>of the requirements for the degree of @@ -7960,7 +9361,15 @@ <br/>Spring Term <br/>2015 <br/>Major Professor: Gita R. Sukthankar -</td><td></td><td></td></tr><tr><td>b5da4943c348a6b4c934c2ea7330afaf1d655e79</td><td>Facial Landmarks Detection by Self-Iterative Regression based +</td><td></td><td></td></tr><tr><td>b5f2846a506fc417e7da43f6a7679146d99c5e96</td><td>UCF101: A Dataset of 101 Human Actions +<br/>Classes From Videos in The Wild +<br/>CRCV-TR-12-01 +<br/>November 2012 +<br/>Keywords: Action Dataset, UCF101, UCF50, Action Recognition +<br/>Center for Research in Computer Vision +<br/><b>University of Central Florida</b><br/>4000 Central Florida Blvd. +<br/>Orlando, FL 32816-2365 USA +</td><td>('1799979', 'Khurram Soomro', 'khurram soomro')<br/>('40029556', 'Amir Roshan Zamir', 'amir roshan zamir')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td></td></tr><tr><td>b5da4943c348a6b4c934c2ea7330afaf1d655e79</td><td>Facial Landmarks Detection by Self-Iterative Regression based <br/>Landmarks-Attention Network <br/><b>University of Chinese Academy of Sciences, Beijing, China</b><br/>2 Microsoft Research Asia, Beijing, China </td><td>('33325349', 'Tao Hu', 'tao hu')<br/>('3245785', 'Honggang Qi', 'honggang qi')<br/>('1697982', 'Jizheng Xu', 'jizheng xu')<br/>('1689702', 'Qingming Huang', 'qingming huang')</td><td>hutao16@mails.ucas.ac.cn, hgqi@ucas.ac.cn @@ -8076,7 +9485,7 @@ <br/>1Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil <br/>2IRISA & Inria Rennes , CNRS, Rennes, France </td><td>('2823797', 'Cassio E. dos Santos', 'cassio e. dos santos')<br/>('1708671', 'Guillaume Gravier', 'guillaume gravier')<br/>('1679142', 'William Robson Schwartz', 'william robson schwartz')</td><td>cass@dcc.ufmg.br, guig@irisa.fr, william@dcc.ufmg.br -</td></tr><tr><td>b51e3d59d1bcbc023f39cec233f38510819a2cf9</td><td>CBMM Memo No. 003 +</td></tr><tr><td>b59f441234d2d8f1765a20715e227376c7251cd7</td><td></td><td></td><td></td></tr><tr><td>b51e3d59d1bcbc023f39cec233f38510819a2cf9</td><td>CBMM Memo No. 003 <br/>March 27, 2014 <br/>Can a biologically-plausible hierarchy effectively <br/>replace face detection, alignment, and @@ -8204,6 +9613,15 @@ <br/>for <br/>techniques </td><td>('29695322', 'Ben Fielding', 'ben fielding')<br/>('1921534', 'Philip Kinghorn', 'philip kinghorn')<br/>('2801063', 'Kamlesh Mistry', 'kamlesh mistry')<br/>('1712838', 'Li Zhang', 'li zhang')</td><td>{ben.fielding, philip.kinghorn, kamlesh.mistry, li.zhang (corr. author)}@northumbria.ac.uk +</td></tr><tr><td>b59cee1f647737ec3296ccb3daa25c890359c307</td><td>Continuously Reproducing Toolchains in Pattern +<br/>Recognition and Machine Learning Experiments +<br/>A. Anjos +<br/><b>Idiap Research Institute</b><br/>Martigny, Switzerland +<br/>M. G¨unther +<br/>Vision and Security Technology +<br/><b>University of Colorado</b><br/>Colorado Springs, USA +</td><td></td><td>andre.anjos@idiap.ch +<br/>mgunther@vast.uccs.edu </td></tr><tr><td>b249f10a30907a80f2a73582f696bc35ba4db9e2</td><td>Improved graph-based SFA: Information preservation <br/>complements the slowness principle <br/>Institut f¨ur Neuroinformatik @@ -8318,7 +9736,14 @@ <br/>For Rapid Annotation <br/>1 CSIRO, Brisbane, QLD, Australia <br/><b>Queensland University of Technology, Brisbane, QLD, Australia</b><br/><b>Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>('3231493', 'Ashton Fagg', 'ashton fagg')<br/>('1729760', 'Sridha Sridharan', 'sridha sridharan')<br/>('1820249', 'Simon Lucey', 'simon lucey')</td><td>ashton@fagg.id.au, s.sridharan@qut.edu.au, slucey@cs.cmu.edu -</td></tr><tr><td>b235b4ccd01a204b95f7408bed7a10e080623d2e</td><td>Regularizing Flat Latent Variables with Hierarchical Structures +</td></tr><tr><td>b2c60061ad32e28eb1e20aff42e062c9160786be</td><td>Diverse and Controllable Image Captioning with +<br/>Part-of-Speech Guidance +<br/><b>University of Illinois at Urbana-Champaign</b></td><td>('2118997', 'Aditya Deshpande', 'aditya deshpande')<br/>('29956361', 'Jyoti Aneja', 'jyoti aneja')<br/>('46659761', 'Liwei Wang', 'liwei wang')</td><td>{ardeshp2, janeja2, lwang97, aschwing, daf}@illinois.edu +</td></tr><tr><td>b2b535118c5c4dfcc96f547274cdc05dde629976</td><td>JOURNAL OF IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. XX, NO. X, XXX 2017 +<br/>Automatic Recognition of Facial Displays of +<br/>Unfelt Emotions +<br/>Escalera, Xavier Bar´o, Sylwia Hyniewska, Member, IEEE, J¨uri Allik, +</td><td>('38370357', 'Kaustubh Kulkarni', 'kaustubh kulkarni')<br/>('22197083', 'Ciprian Adrian Corneanu', 'ciprian adrian corneanu')<br/>('22211769', 'Ikechukwu Ofodile', 'ikechukwu ofodile')<br/>('47608164', 'Gholamreza Anbarjafari', 'gholamreza anbarjafari')</td><td></td></tr><tr><td>b235b4ccd01a204b95f7408bed7a10e080623d2e</td><td>Regularizing Flat Latent Variables with Hierarchical Structures </td><td>('7246002', 'Rongcheng Lin', 'rongcheng lin')<br/>('2703486', 'Huayu Li', 'huayu li')<br/>('38472218', 'Xiaojun Quan', 'xiaojun quan')<br/>('2248826', 'Richang Hong', 'richang hong')<br/>('2737890', 'Zhiang Wu', 'zhiang wu')<br/>('1874059', 'Yong Ge', 'yong ge')</td><td>(cid:117)UNC Charlotte. Email: {rlin4, hli38, yong.ge}@uncc.edu, <br/>(cid:63) Hefei University of Technology. Email: hongrc@hfut.edu.cn <br/>† Institute for Infocomm Research. Email: quanx@i2r.a-star.edu.sg @@ -8346,6 +9771,28 @@ <br/>Department of Signal Processing <br/><b>Tampere University of Technology</b><br/>Tampere 33720, Finland </td><td>('40394658', 'Ke Chen', 'ke chen')</td><td>firstname.lastname@tut.fi +</td></tr><tr><td>d904f945c1506e7b51b19c99c632ef13f340ef4c</td><td>A scalable 3D HOG model for fast object detection and viewpoint estimation +<br/>KU Leuven, ESAT/PSI - iMinds +<br/>Kasteelpark Arenberg 10 B-3001 Leuven, Belgium +</td><td>('3048367', 'Marco Pedersoli', 'marco pedersoli')<br/>('1704728', 'Tinne Tuytelaars', 'tinne tuytelaars')</td><td>firstname.lastname@esat.kuleuven.be +</td></tr><tr><td>d949fadc9b6c5c8b067fa42265ad30945f9caa99</td><td>Rethinking Feature Discrimination and +<br/>Polymerization for Large-scale Recognition +<br/><b>The Chinese University of Hong Kong</b></td><td>('1715752', 'Yu Liu', 'yu liu')<br/>('46382329', 'Hongyang Li', 'hongyang li')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')</td><td>{yuliu, yangli, xgwang}@ee.cuhk.edu.hk +</td></tr><tr><td>d93baa5ecf3e1196b34494a79df0a1933fd2b4ec</td><td>Precise Temporal Action Localization by +<br/>Evolving Temporal Proposals +<br/><b>East China Normal University</b><br/>Shanghai, China +<br/><b>University of Washington</b><br/>Seattle, WA, USA +<br/>Shanghai Advanced Research +<br/><b>Institute, CAS, China</b><br/><b>East China Normal University</b><br/>Shanghai, China +<br/>Shanghai Advanced Research +<br/><b>Institute, CAS, China</b><br/>Liang He +<br/><b>East China Normal University</b><br/>Shanghai, China +</td><td>('31567595', 'Haonan Qiu', 'haonan qiu')<br/>('1803391', 'Yao Lu', 'yao lu')<br/>('3015119', 'Yingbin Zheng', 'yingbin zheng')<br/>('47939010', 'Feng Wang', 'feng wang')<br/>('1743864', 'Hao Ye', 'hao ye')</td><td>hnqiu@ica.stc.sh.cn +<br/>luyao@cs.washington.edu +<br/>zhengyb@sari.ac.cn +<br/>fwang@cs.ecnu.edu.cn +<br/>yeh@sari.ac.cn +<br/>lhe@cs.ecnu.edu.cn </td></tr><tr><td>d961617db4e95382ba869a7603006edc4d66ac3b</td><td>Experimenting Motion Relativity for Action Recognition <br/>with a Large Number of Classes <br/><b>East China Normal University</b><br/>500 Dongchuan Rd., Shanghai, China @@ -8402,7 +9849,21 @@ <br/> Available online at: www.ijarcsse.com <br/>A Research - Face Recognition by Using Near Set Theory <br/>Department of Computer Science and Engineering -<br/><b>Abha Gaikwad -Patil College of Engineering, Nagpur, Maharashtra, India</b></td><td>('9231464', 'Bhakti Kurhade', 'bhakti kurhade')</td><td></td></tr><tr><td>d9327b9621a97244d351b5b93e057f159f24a21e</td><td>SCIENCE CHINA +<br/><b>Abha Gaikwad -Patil College of Engineering, Nagpur, Maharashtra, India</b></td><td>('9231464', 'Bhakti Kurhade', 'bhakti kurhade')</td><td></td></tr><tr><td>d9c4b1ca997583047a8721b7dfd9f0ea2efdc42c</td><td>Learning Inference Models for Computer Vision +</td><td></td><td></td></tr><tr><td>d9bad7c3c874169e3e0b66a031c8199ec0bc2c1f</td><td>It All Matters: +<br/>Reporting Accuracy, Inference Time and Power Consumption +<br/>for Face Emotion Recognition on Embedded Systems +<br/><b>Institute of Telecommunications, TU Wien</b><br/>Movidius an Intel Company +<br/>Dexmont Pe˜na +<br/>Movidius an Intel Company +<br/>Movidius an Intel Company +<br/>ALaRI, Faculty of Informatics, USI +</td><td>('48802034', 'Jelena Milosevic', 'jelena milosevic')<br/>('51129064', 'Andrew Forembsky', 'andrew forembsky')<br/>('9151916', 'David Moloney', 'david moloney')<br/>('1697550', 'Miroslaw Malek', 'miroslaw malek')</td><td>jelena.milosevic@tuwien.ac.at +<br/>andrew.forembsky2@mail.dcu.ie +<br/>dexmont.pena@intel.com +<br/>david.moloney@intel.com +<br/>miroslaw.malek@usi.ch +</td></tr><tr><td>d9327b9621a97244d351b5b93e057f159f24a21e</td><td>SCIENCE CHINA <br/>Information Sciences <br/>. RESEARCH PAPERS . <br/>December 2010 Vol. 53 No. 12: 2415–2428 @@ -8415,7 +9876,12 @@ </td><td></td><td></td></tr><tr><td>d915e634aec40d7ee00cbea96d735d3e69602f1a</td><td>Two-Stream convolutional nets for action recognition in untrimmed video <br/><b>Stanford University</b><br/><b>Stanford University</b></td><td>('3308619', 'Kenneth Jung', 'kenneth jung')<br/>('5590869', 'Song Han', 'song han')</td><td>kjung@stanford.edu <br/>songhan@stanford.edu -</td></tr><tr><td>ac1d97a465b7cc56204af5f2df0d54f819eef8a6</td><td>A Look at Eye Detection for Unconstrained +</td></tr><tr><td>aca232de87c4c61537c730ee59a8f7ebf5ecb14f</td><td>EBGM VS SUBSPACE PROJECTION FOR FACE RECOGNITION +<br/>19.5 Km Markopoulou Avenue, P.O. Box 68, Peania, Athens, Greece +<br/>Athens Information Technology +<br/>Keywords: +<br/>Human-Machine Interfaces, Computer Vision, Face Recognition. +</td><td>('40089976', 'Andreas Stergiou', 'andreas stergiou')<br/>('1702943', 'Aristodemos Pnevmatikakis', 'aristodemos pnevmatikakis')<br/>('1725498', 'Lazaros Polymenakos', 'lazaros polymenakos')</td><td></td></tr><tr><td>ac1d97a465b7cc56204af5f2df0d54f819eef8a6</td><td>A Look at Eye Detection for Unconstrained <br/>Environments <br/>Key words: Unconstrained Face Recognition, Eye Detection, Machine Learning, <br/>Correlation Filters, Photo-head Testing Protocol @@ -8444,7 +9910,9 @@ <br/><b>Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Finland</b></td><td>('1848903', 'James Booth', 'james booth')<br/>('2931390', 'Anastasios Roussos', 'anastasios roussos')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('5137183', 'Allan Ponniah', 'allan ponniah')<br/>('2421231', 'David Dunaway', 'david dunaway')</td><td>⋆{james.booth,troussos,s.zafeiriou}@imperial.ac.uk, †{allan.ponniah,david.dunaway}@gosh.nhs.uk </td></tr><tr><td>ac6c3b3e92ff5fbcd8f7967696c7aae134bea209</td><td>Deep Cascaded Bi-Network for <br/>Face Hallucination(cid:63) -<br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b><br/><b>University of California, Merced</b></td><td>('2226254', 'Shizhan Zhu', 'shizhan zhu')<br/>('2391885', 'Sifei Liu', 'sifei liu')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>ac21c8aceea6b9495574f8f9d916e571e2fc497f</td><td>Pose-Independent Identity-based Facial Image +<br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b><br/><b>University of California, Merced</b></td><td>('2226254', 'Shizhan Zhu', 'shizhan zhu')<br/>('2391885', 'Sifei Liu', 'sifei liu')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>ac855f0de9086e9e170072cb37400637f0c9b735</td><td>Fast Geometrically-Perturbed Adversarial Faces +<br/><b>West Virginia University</b></td><td>('35477977', 'Ali Dabouei', 'ali dabouei')<br/>('30319988', 'Sobhan Soleymani', 'sobhan soleymani')<br/>('8147588', 'Nasser M. Nasrabadi', 'nasser m. nasrabadi')</td><td>{ad0046, ssoleyma}@mix.wvu.edu, {jeremy.dawson, nasser.nasrabadi}@mail.wvu.edu +</td></tr><tr><td>ac21c8aceea6b9495574f8f9d916e571e2fc497f</td><td>Pose-Independent Identity-based Facial Image <br/>Retrieval using Contextual Similarity <br/><b>King Abdullah University of Science and Technology 4700, Thuwal, Saudi Arabia</b></td><td>('3036634', 'Islam Almasri', 'islam almasri')</td><td></td></tr><tr><td>ac6a9f80d850b544a2cbfdde7002ad5e25c05ac6</td><td>779 <br/>Privacy-Protected Facial Biometric Verification @@ -8452,6 +9920,89 @@ </td><td>('1690116', 'Ahmed Bouridane', 'ahmed bouridane')<br/>('1691478', 'Danny Crookes', 'danny crookes')<br/>('1739563', 'M. Emre Celebi', 'm. emre celebi')<br/>('39486168', 'Hua-Liang Wei', 'hua-liang wei')</td><td></td></tr><tr><td>aca273a9350b10b6e2ef84f0e3a327255207d0f5</td><td></td><td></td><td></td></tr><tr><td>aca75c032cfb0b2eb4c0ae56f3d060d8875e43f9</td><td>Co-Regularized Ensemble for Feature Selection <br/><b>School of Computer Science and Technology, Tianjin University, China</b><br/><b>School of Information Technology and Electrical Engineering, The University of Queensland</b><br/>3Tianjin Key Laboratory of Cognitive Computing and Application </td><td>('2302512', 'Yahong Han', 'yahong han')<br/>('1698559', 'Yi Yang', 'yi yang')<br/>('1720932', 'Xiaofang Zhou', 'xiaofang zhou')</td><td>yahong@tju.edu.cn, yee.i.yang@gmail.com, zxf@itee.uq.edu.au +</td></tr><tr><td>accbd6cd5dd649137a7c57ad6ef99232759f7544</td><td>FACIAL EXPRESSION RECOGNITION WITH LOCAL BINARY PATTERNS +<br/>AND LINEAR PROGRAMMING +<br/>1 Machine Vision Group, Infotech Oulu and Dept. of Electrical and Information Engineering +<br/><b>P. O. Box 4500 Fin-90014 University of Oulu, Finland</b><br/><b>College of Electronics and Information, Northwestern Polytechnic University</b><br/>710072 Xi’an, China +<br/>In this work, we propose a novel approach to recognize facial expressions from static +<br/>images. First, the Local Binary Patterns (LBP) are used to efficiently represent the facial +<br/>images and then the Linear Programming (LP) technique is adopted to classify the seven +<br/>facial expressions anger, disgust, fear, happiness, sadness, surprise and neutral. +<br/>Experimental results demonstrate an average recognition accuracy of 93.8% on the JAFFE +<br/>database, which outperforms the rates of all other reported methods on the same database. +<br/>Introduction +<br/>Facial expression recognition from static +<br/>images is a more challenging problem +<br/>than from image sequences because less +<br/>information for expression actions +<br/>is +<br/>available. However, information in a +<br/>single image is sometimes enough for +<br/>expression recognition, and +<br/>in many +<br/>applications it is also useful to recognize +<br/>single image’s facial expression. +<br/>In the recent years, numerous approaches +<br/>to facial expression analysis from static +<br/>images have been proposed [1] [2]. These +<br/>methods +<br/>face +<br/>representation and similarity measure. +<br/>For instance, Zhang [3] used two types of +<br/>features: the geometric position of 34 +<br/>manually selected fiducial points and a +<br/>set of Gabor wavelet coefficients at these +<br/>points. These two types of features were +<br/>used both independently and jointly with +<br/>a multi-layer perceptron for classification. +<br/>Guo and Dyer [4] also adopted a similar +<br/>face representation, combined with linear +<br/>to carry out +<br/>programming +<br/>selection +<br/>simultaneous +<br/>and +<br/>classifier +<br/>they reported +<br/>technique +<br/>feature +<br/>training, and +<br/>differ +<br/>generally +<br/>in +<br/>a +<br/>simple +<br/>imperative question +<br/>better result. Lyons et al. used a similar face +<br/>representation with +<br/>LDA-based +<br/>classification scheme [5]. All the above methods +<br/>required the manual selection of fiducial points. +<br/>Buciu et al. used ICA and Gabor representation for +<br/>facial expression recognition and reported good result +<br/>on the same database [6]. However, a suitable +<br/>combination of feature extraction and classification is +<br/>still one +<br/>for expression +<br/>recognition. +<br/>In this paper, we propose a novel method for facial +<br/>expression recognition. In the feature extraction step, +<br/>the Local Binary Pattern (LBP) operator is used to +<br/>describe facial expressions. In the classification step, +<br/>seven expressions (anger, disgust, fear, happiness, +<br/>sadness, surprise and neutral) are decomposed into 21 +<br/>expression pairs such as anger-fear, happiness- +<br/>sadness etc. 21 classifiers are produced by the Linear +<br/>Programming (LP) technique, each corresponding to +<br/>one of the 21 expression pairs. A simple binary tree +<br/>tournament scheme with pairwise comparisons is +<br/>Face Representation with Local Binary Patterns +<br/> +<br/>Fig.1 shows the basic LBP operator [7], in which the +<br/>original 3×3 neighbourhood at the left is thresholded +<br/>by the value of the centre pixel, and a binary pattern +</td><td>('4729239', 'Xiaoyi Feng', 'xiaoyi feng')<br/>('1714724', 'Matti Pietikäinen', 'matti pietikäinen')<br/>('1751372', 'Abdenour Hadid', 'abdenour hadid')</td><td>{xiaoyi,mkp,hadid}@ee.oulu.fi +<br/>fengxiao@nwpu.edu.cn </td></tr><tr><td>ac51d9ddbd462d023ec60818bac6cdae83b66992</td><td>Hindawi Publishing Corporation <br/>Computational Intelligence and Neuroscience <br/>Volume 2015, Article ID 709072, 10 pages @@ -8566,11 +10117,26 @@ <br/>anger, disgust, and surprise). In their approach, the amount of <br/>facial movements change and timing have been quantified by </td><td>('40432410', 'Peng Wu', 'peng wu')<br/>('34068333', 'Isabel Gonzalez', 'isabel gonzalez')<br/>('3348420', 'Dongmei Jiang', 'dongmei jiang')<br/>('1970907', 'Hichem Sahli', 'hichem sahli')<br/>('3041213', 'Eric Kerckhofs', 'eric kerckhofs')<br/>('2540163', 'Marie Vandekerckhove', 'marie vandekerckhove')<br/>('40432410', 'Peng Wu', 'peng wu')</td><td>Correspondence should be addressed to Peng Wu; pwu@etro.vub.ac.be -</td></tr><tr><td>ac820d67b313c38b9add05abef8891426edd5afb</td><td></td><td></td><td></td></tr><tr><td>ac9a331327cceda4e23f9873f387c9fd161fad76</td><td>Deep Convolutional Neural Network for Age Estimation based on +</td></tr><tr><td>acee2201f8a15990551804dd382b86973eb7c0a8</td><td>To Boost or Not to Boost? On the Limits of +<br/>Boosted Trees for Object Detection +<br/><b>Computer Vision and Robotics Research Laboratory</b><br/><b>University of California San Diego</b></td><td>('1802326', 'Eshed Ohn-Bar', 'eshed ohn-bar')</td><td>{eohnbar, mtrivedi}@ucsd.edu +</td></tr><tr><td>ac0d3f6ed5c42b7fc6d7c9e1a9bb80392742ad5e</td><td></td><td></td><td></td></tr><tr><td>ac820d67b313c38b9add05abef8891426edd5afb</td><td></td><td></td><td></td></tr><tr><td>ac9a331327cceda4e23f9873f387c9fd161fad76</td><td>Deep Convolutional Neural Network for Age Estimation based on <br/>VGG-Face Model <br/><b>University of Bridgeport</b><br/><b>University of Bridgeport</b><br/>Technology Building, Bridgeport CT 06604 USA </td><td>('7404315', 'Zakariya Qawaqneh', 'zakariya qawaqneh')<br/>('34792425', 'Arafat Abu Mallouh', 'arafat abu mallouh')<br/>('2791535', 'Buket D. Barkana', 'buket d. barkana')</td><td>Emails: {zqawaqneh; aabumall@my.bridgeport.edu}, bbarkana@bridgeport.edu -</td></tr><tr><td>ac12ba5bf81de83991210b4cd95b4ad048317681</td><td>Combining Deep Facial and Ambient Features +</td></tr><tr><td>ac26166857e55fd5c64ae7194a169ff4e473eb8b</td><td>Personalized Age Progression with Bi-level +<br/>Aging Dictionary Learning +</td><td>('2287686', 'Xiangbo Shu', 'xiangbo shu')<br/>('8053308', 'Jinhui Tang', 'jinhui tang')<br/>('3233021', 'Zechao Li', 'zechao li')<br/>('2356867', 'Hanjiang Lai', 'hanjiang lai')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>ac559873b288f3ac28ee8a38c0f3710ea3f986d9</td><td>Team DEEP-HRI Moments in Time Challenge 2018 Technical Report +<br/><b>Hikvision Research Institute</b></td><td>('39816387', 'Chao Li', 'chao li')<br/>('48375401', 'Zhi Hou', 'zhi hou')<br/>('35843399', 'Jiaxu Chen', 'jiaxu chen')<br/>('9162532', 'Jiqiang Zhou', 'jiqiang zhou')<br/>('50322310', 'Di Xie', 'di xie')<br/>('3290437', 'Shiliang Pu', 'shiliang pu')</td><td></td></tr><tr><td>ac8e09128e1e48a2eae5fa90f252ada689f6eae7</td><td>Leolani: a reference machine with a theory of +<br/>mind for social communication +<br/><b>VU University Amsterdam, Computational Lexicology and Terminology Lab, De</b><br/>Boelelaan 1105, 1081HV Amsterdam, The Netherlands +<br/>www.cltl.nl +</td><td>('50998926', 'Bram Kraaijeveld', 'bram kraaijeveld')</td><td>{p.t.j.m.vossen,s.baezsantamaria,l.bajcetic,b.kraaijeveld}@vu.nl +</td></tr><tr><td>ac8441e30833a8e2a96a57c5e6fede5df81794af</td><td>IEEE TRANSACTIONS ON IMAGE PROCESSING +<br/>Hierarchical Representation Learning for Kinship +<br/>Verification +</td><td>('1952698', 'Naman Kohli', 'naman kohli')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2487227', 'Afzel Noore', 'afzel noore')<br/>('2641605', 'Angshul Majumdar', 'angshul majumdar')</td><td></td></tr><tr><td>ac86ccc16d555484a91741e4cb578b75599147b2</td><td>Morphable Face Models - An Open Framework +<br/><b>Gravis Research Group, University of Basel</b></td><td>('3277377', 'Thomas Gerig', 'thomas gerig')<br/>('39550224', 'Clemens Blumer', 'clemens blumer')<br/>('34460642', 'Bernhard Egger', 'bernhard egger')<br/>('1687079', 'Thomas Vetter', 'thomas vetter')</td><td></td></tr><tr><td>ac12ba5bf81de83991210b4cd95b4ad048317681</td><td>Combining Deep Facial and Ambient Features <br/>for First Impression Estimation <br/><b>Program of Computational Science and Engineering, Bo gazi ci University</b><br/>Bebek, Istanbul, Turkey <br/><b>Nam k Kemal University</b><br/>C¸ orlu, Tekirda˘g, Turkey @@ -8728,7 +10294,15 @@ <br/>Dr. Antonio Criminisi <br/>Florian Schroff <br/><b>St. Anne s College</b><br/>Trinity, 2009 -</td><td></td><td></td></tr><tr><td>adfaf01773c8af859faa5a9f40fb3aa9770a8aa7</td><td>LARGE SCALE VISUAL RECOGNITION +</td><td></td><td></td></tr><tr><td>ad0d4d5c61b55a3ab29764237cd97be0ebb0ddff</td><td>Weakly Supervised Action Localization by Sparse Temporal Pooling Network +<br/><b>University of California</b><br/>Irvine, CA, USA +<br/>Google +<br/>Venice, CA, USA +<br/><b>Seoul National University</b><br/>Seoul, Korea +</td><td>('1998374', 'Phuc Nguyen', 'phuc nguyen')<br/>('40282288', 'Ting Liu', 'ting liu')<br/>('2775959', 'Gautam Prasad', 'gautam prasad')<br/>('40030651', 'Bohyung Han', 'bohyung han')</td><td>nguyenpx@uci.edu +<br/>{liuti, gautamprasad}@google.com +<br/>bhhan@snu.ac.kr +</td></tr><tr><td>adfaf01773c8af859faa5a9f40fb3aa9770a8aa7</td><td>LARGE SCALE VISUAL RECOGNITION <br/>A DISSERTATION <br/>PRESENTED TO THE FACULTY <br/><b>OF PRINCETON UNIVERSITY</b><br/>IN CANDIDACY FOR THE DEGREE @@ -8842,6 +10416,8 @@ <br/>l.ball@abertay.ac.uk <br/>j.archibald @abertay.ac.uk <br/>l.carson@abertay.ac.uk +</td></tr><tr><td>ad2339c48ad4ffdd6100310dcbb1fb78e72fac98</td><td>Video Fill In the Blank using LR/RL LSTMs with Spatial-Temporal Attentions +<br/><b>Center for Research in Computer Vision, University of Central Florida, Orlando, FL</b></td><td>('33209161', 'Amir Mazaheri', 'amir mazaheri')<br/>('46335319', 'Dong Zhang', 'dong zhang')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>amirmazaheri@cs.ucf.edu, dzhang@cs.ucf.edu, shah@crcv.ucf.edu </td></tr><tr><td>ad247138e751cefa3bb891c2fe69805da9c293d7</td><td>American Journal of Networks and Communications <br/>2015; 4(4): 90-94 <br/>Published online July 7, 2015 (http://www.sciencepublishinggroup.com/j/ajnc) @@ -8853,6 +10429,74 @@ <br/>To cite this article: <br/>Decomposition. American Journal of Networks and Communications. Vol. 4, No. 4, 2015, pp. 90-94. doi: 10.11648/j.ajnc.20150404.12 </td><td>('2653670', 'Vahid Haji Hashemi', 'vahid haji hashemi')<br/>('2153844', 'Abdorreza Alavi Gharahbagh', 'abdorreza alavi gharahbagh')<br/>('2653670', 'Vahid Haji Hashemi', 'vahid haji hashemi')<br/>('2153844', 'Abdorreza Alavi Gharahbagh', 'abdorreza alavi gharahbagh')</td><td>hajihashemi.vahid@yahoo.com (V. H. Hashemi), R_alavi@iau-shahrood.ac.ir (A. A. Gharahbagh) +</td></tr><tr><td>adf62dfa00748381ac21634ae97710bb80fc2922</td><td>ViFaI: A trained video face indexing scheme +<br/>1. Introduction +<br/>With the increasing prominence of inexpensive +<br/>video recording devices (e.g., digital camcorders and +<br/>video recording smartphones), +<br/>the average user’s +<br/>video collection today is increasing rapidly. With this +<br/>development, there arises a natural desire to rapidly +<br/>access a subset of one’s collection of videos. The solu- +<br/>tion to this problem requires an effective video index- +<br/>ing scheme. In particular, we must be able to easily +<br/>process a video to extract such indexes. +<br/>Today, there also exist large sets of labeled (tagged) +<br/>face images. One important example is an individual’s +<br/>Facebook profile. Such a set of of tagged images of +<br/>one’s self, family, friends, and colleagues represents +<br/>an extremely valuable potential training set. +<br/>In this work, we explore how to leverage the afore- +<br/>mentioned training set to solve the video indexing +<br/>problem. +<br/>2. Problem Statement +<br/>Use a labeled (tagged) training set of face images +<br/>to extract relevant indexes from a collection of videos, +<br/>and use these indexes to answer boolean queries of the +<br/>form: “videos with ‘Person 1’ OP1 ‘Person 2’ OP2 ... +<br/>OP(N-1) ‘Person N’ ”, where ‘Person N’ corresponds +<br/>to a training label (tag) and OPN is a boolean operand +<br/>such as AND, OR, NOT, XOR, and so on. +<br/>3. Proposed Scheme +<br/>In this section, we outline our proposed scheme to +<br/>address the problem we postulate in the previous sec- +<br/>tion. We provide further details about the system im- +<br/>plementation in Section 4. +<br/>At a high level, we subdivide the problem into two +<br/>key phases: the first ”off-line” executed once, and the +<br/>second ”on-line” phase instantiated upon each query. +<br/>For the purposes of this work, we define an index as +<br/>follows: <video id, tag, frame #>. +<br/>3.1. The training phase +<br/>We first outline Phase 1 (the training or “off-line” +<br/>phase): +<br/>1. Use the labeled training set plus an additional set +<br/>of ‘other’ faces to compute the Fisher Linear Dis- +<br/>criminant (FLD) [1]. +<br/>2. Project the training data onto the space defined by +<br/>the eigenvectors returned by the FLD, and train +<br/>a classifier (first nearest neighbour, then SVM if +<br/>required) using the training features. +<br/>3. Iterate through each frame of each video, detect- +<br/>ing faces [2], classifying detected results, and add +<br/>an index if the detected face corresponds to one of +<br/>the labeled classes from the previous step. +<br/>3.2. The query phase +<br/>Now, we outline Phase 2 (the query or “on-line” +<br/>phase): +<br/>1. Key the indexes on their video id. +<br/>2. For each video, evaluate the boolean query for the +<br/>set of corresponding indexes. +<br/>3. Keep videos for which the boolean query evalu- +<br/>ates true, and discard those for which it evaluates +<br/>false. +<br/>4. Implementation Details +<br/>We are implementing the project in C++, leverag- +<br/>ing the OpenCV v2.2 framework [4]. In this section, +<br/>we will highlight some of the critical implementation +<br/>details of our proposed system. +</td><td>('30006340', 'Nayyar', 'nayyar')<br/>('47384529', 'Audrey Wei', 'audrey wei')</td><td>hnayyar@stanford.edu +<br/>awei1001@stanford.edu </td></tr><tr><td>bbc4b376ebd296fb9848b857527a72c82828fc52</td><td>Attributes for Improved Attributes <br/><b>University of Maryland</b><br/><b>College Park, MD</b></td><td>('3351637', 'Emily Hand', 'emily hand')</td><td>emhand@cs.umd.edu </td></tr><tr><td>bb489e4de6f9b835d70ab46217f11e32887931a2</td><td>Everything you wanted to know about Deep Learning for Computer Vision but were @@ -8919,6 +10563,9 @@ <br/>1 =@@EJE J BA=JKHA HAFHAIAJ=JE MA =I EJH@K?A = AJD@ BH ?=IIE?=JE <br/>AJMHI @EC = IJHC ?=IIEAH EI JDA ?HA E JDA ANEIJEC B=?E= ANFHAIIE ==O <br/>IEI IJK@EAI 1 JDA =FFH=?DAI JD=J =@FJ ?= B=?E= EBH=JE MAECDJEC JDAIA ?= +</td></tr><tr><td>bbf28f39e5038813afd74cf1bc78d55fcbe630f1</td><td>Style Aggregated Network for Facial Landmark Detection +<br/><b>University of Technology Sydney, 2 The University of Sydney</b></td><td>('9929684', 'Xuanyi Dong', 'xuanyi dong')<br/>('1685212', 'Yan Yan', 'yan yan')<br/>('3001348', 'Wanli Ouyang', 'wanli ouyang')<br/>('1698559', 'Yi Yang', 'yi yang')</td><td>{xuanyi.dong,yan.yan-3}@student.uts.edu.au; +<br/>wanli.ouyang@sydney.edu.au; yi.yang@uts.edu.au </td></tr><tr><td>bbe1332b4d83986542f5db359aee1fd9b9ba9967</td><td></td><td></td><td></td></tr><tr><td>bbe949c06dc4872c7976950b655788555fe513b8</td><td>Automatic Frequency Band Selection for <br/>Illumination Robust Face Recognition <br/><b>Institute of Anthropomatics, Karlsruhe Institute of Technology, Germany</b></td><td>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')</td><td>{ekenel,rainer.stiefelhagen}@kit.edu @@ -8945,7 +10592,13 @@ <br/>Figure 1. Verb prediction accuracy on the development set. Some verbs such as taxiing typically have a similar image (a plane on the <br/>tarmac), while verbs such as rubbing or twisting can have very different corresponding images. <br/>taxiinglappingretrievingflickingminingwaxingjugglingcurtsyingcommutingdancingcrushingreadingexaminingdousingdecomposingchoppingdrawingcryingcalmingsniffingmourningsubmergingtwistingcarvingrubbingaskingVerbs0102030405060708090100Accuracy (%) </td><td>('8139953', 'Ruiyu Li', 'ruiyu li')<br/>('2103464', 'Makarand Tapaswi', 'makarand tapaswi')<br/>('2246396', 'Renjie Liao', 'renjie liao')<br/>('1729056', 'Jiaya Jia', 'jiaya jia')<br/>('2422559', 'Raquel Urtasun', 'raquel urtasun')<br/>('37895334', 'Sanja Fidler', 'sanja fidler')<br/>('2043324', 'Hong Kong', 'hong kong')</td><td>ryli@cse.cuhk.edu.hk, {makarand,rjliao,urtasun,fidler}@cs.toronto.edu, leojia9@gmail.com -</td></tr><tr><td>bbf01aa347982592b3e4c9e4f433e05d30e71305</td><td></td><td></td><td></td></tr><tr><td>bbfe0527e277e0213aafe068113d719b2e62b09c</td><td>Dog Breed Classification Using Part Localization +</td></tr><tr><td>bb7f2c5d84797742f1d819ea34d1f4b4f8d7c197</td><td>TO APPEAR IN TPAMI +<br/>From Images to 3D Shape Attributes +</td><td>('1786435', 'David F. Fouhey', 'david f. fouhey')<br/>('1737809', 'Abhinav Gupta', 'abhinav gupta')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td></td></tr><tr><td>bbf01aa347982592b3e4c9e4f433e05d30e71305</td><td></td><td></td><td></td></tr><tr><td>bbc5f4052674278c96abe7ff9dc2d75071b6e3f3</td><td>Nonlinear Hierarchical Part-based Regression for Unconstrained Face Alignment +<br/>†NEC Laboratories America, Media Analytics +<br/>‡Adobe Research +<br/><b>cid:93)University of North Carolina at Charlotte</b><br/><b>Rutgers, The State University of New Jersey</b></td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1753384', 'Shaoting Zhang', 'shaoting zhang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>xiangyu@nec-labs.com, zlin@adobe.com, szhang16@uncc.edu, dnm@cs.rutgers.edu +</td></tr><tr><td>bbfe0527e277e0213aafe068113d719b2e62b09c</td><td>Dog Breed Classification Using Part Localization <br/><b>Columbia University</b><br/><b>University of Maryland</b></td><td>('2454675', 'Jiongxin Liu', 'jiongxin liu')<br/>('20615377', 'Angjoo Kanazawa', 'angjoo kanazawa')</td><td></td></tr><tr><td>bbf1396eb826b3826c5a800975047beabde2f0de</td><td></td><td></td><td></td></tr><tr><td>bb451dc2420e1a090c4796c19716f93a9ef867c9</td><td>International Journal of Computer Applications (0975 – 8887) <br/>Volume 104 – No.5, October 2014 <br/>A Review on: Automatic Movie Character Annotation @@ -8962,7 +10615,7 @@ <br/>HOD, Department of <br/>Information Technology, <br/><b>College of Engineering (Poly</b><br/>Pandharpur, Solapur, INDIA -</td><td></td><td></td></tr><tr><td>d73d2c9a6cef79052f9236e825058d5d9cdc1321</td><td>2014-ENST-0040 +</td><td></td><td></td></tr><tr><td>bbd1eb87c0686fddb838421050007e934b2d74ab</td><td></td><td></td><td></td></tr><tr><td>d73d2c9a6cef79052f9236e825058d5d9cdc1321</td><td>2014-ENST-0040 <br/>EDITE - ED 130 <br/>Doctorat ParisTech <br/>T H È S E @@ -8992,7 +10645,24 @@ </td><td>('2135932', 'Usman Farrokh Niaz', 'usman farrokh niaz')</td><td></td></tr><tr><td>d794ffece3533567d838f1bd7f442afee13148fd</td><td>Hand Detection and Tracking in Videos <br/>for Fine-grained Action Recognition <br/><b>The University of Electro-Communications, Tokyo</b><br/>1-5-1 Chofugaoka, Chofu, Tokyo, 182-8585 Japan -</td><td>('1681659', 'Keiji Yanai', 'keiji yanai')</td><td></td></tr><tr><td>d78077a7aa8a302d4a6a09fb9737ab489ae169a6</td><td></td><td></td><td></td></tr><tr><td>d7312149a6b773d1d97c0c2b847609c07b5255ec</td><td></td><td></td><td></td></tr><tr><td>d7d9c1fa77f3a3b3c2eedbeb02e8e7e49c955a2f</td><td>Automating Image Analysis by Annotating Landmarks with Deep +</td><td>('1681659', 'Keiji Yanai', 'keiji yanai')</td><td></td></tr><tr><td>d78077a7aa8a302d4a6a09fb9737ab489ae169a6</td><td></td><td></td><td></td></tr><tr><td>d7593148e4319df7a288180d920f2822eeecea0b</td><td>LIU, YU, FUNES-MORA, ODOBEZ: DIFFERENTIAL APPROACH FOR GAZE ESTIMATION 1 +<br/>A Differential Approach for Gaze +<br/>Estimation with Calibration +<br/><b>Idiap Research Institute</b><br/>2 Eyeware Tech SA +<br/>Kenneth A. Funes-Mora 2 +</td><td>('1697913', 'Gang Liu', 'gang liu')<br/>('50133842', 'Yu Yu', 'yu yu')<br/>('1719610', 'Jean-Marc Odobez', 'jean-marc odobez')</td><td>gang.liu@idiap.ch +<br/>yu.yu@idiap.ch +<br/>kenneth@eyeware.tech +<br/>odobez@idiap.ch +</td></tr><tr><td>d7312149a6b773d1d97c0c2b847609c07b5255ec</td><td></td><td></td><td></td></tr><tr><td>d7fe2a52d0ad915b78330340a8111e0b5a66513a</td><td>Unpaired Photo-to-Caricature Translation on Faces in +<br/>the Wild +<br/><b>aNo. 238 Songling Road, Ocean University of</b><br/>China, Qingdao, China +</td><td>('4670300', 'Ziqiang Zheng', 'ziqiang zheng')<br/>('50077564', 'Zhibin Yu', 'zhibin yu')<br/>('2336297', 'Haiyong Zheng', 'haiyong zheng')<br/>('49297407', 'Bing Zheng', 'bing zheng')</td><td></td></tr><tr><td>d7cbedbee06293e78661335c7dd9059c70143a28</td><td>MobileFaceNets: Efficient CNNs for Accurate Real- +<br/>Time Face Verification on Mobile Devices +<br/><b>School of Computer and Information Technology, Beijing Jiaotong University, Beijing</b><br/><b>Research Institute, Watchdata Inc., Beijing, China</b><br/>China +</td><td>('39326372', 'Sheng Chen', 'sheng chen')<br/>('1681842', 'Yang Liu', 'yang liu')<br/>('46757550', 'Xiang Gao', 'xiang gao')<br/>('2765914', 'Zhen Han', 'zhen han')</td><td>{sheng.chen, yang.liu.yj, xiang.gao}@watchdata.com, +<br/>zhan@bjtu.edu.cn +</td></tr><tr><td>d7d9c1fa77f3a3b3c2eedbeb02e8e7e49c955a2f</td><td>Automating Image Analysis by Annotating Landmarks with Deep <br/>Neural Networks <br/>February 3, 2017 <br/>Running head: Automatic Annotation of Landmarks @@ -9088,9 +10758,34 @@ <br/>Hollywood Human Action: The Hollywood <br/>dataset [3] contains 8 action classes collected from <br/>32 Hollywood movies with a total of 430 videos. -</td><td>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('3099139', 'Zuxuan Wu', 'zuxuan wu')<br/>('39811558', 'Jun Wang', 'jun wang')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td></td></tr><tr><td>d785fcf71cb22f9c33473cba35f075c1f0f06ffc</td><td>Learning Active Facial Patches for Expression Analysis +</td><td>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('3099139', 'Zuxuan Wu', 'zuxuan wu')<br/>('39811558', 'Jun Wang', 'jun wang')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td></td></tr><tr><td>d78734c54f29e4474b4d47334278cfde6efe963a</td><td>Exploring Disentangled Feature Representation Beyond Face Identification +<br/><b>CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong</b><br/><b>SenseTime Group Limited, 3Peking University</b></td><td>('1715752', 'Yu Liu', 'yu liu')<br/>('22181490', 'Fangyin Wei', 'fangyin wei')<br/>('49895575', 'Jing Shao', 'jing shao')<br/>('37145669', 'Lu Sheng', 'lu sheng')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')</td><td>{yuliu,lsheng,xgwang}@ee.cuhk.edu.hk, weifangyin@pku.edu.cn, +<br/>{shaojing,yanjunjie}@sensetime.com +</td></tr><tr><td>d785fcf71cb22f9c33473cba35f075c1f0f06ffc</td><td>Learning Active Facial Patches for Expression Analysis <br/><b>Rutgers University, Piscataway, NJ</b><br/><b>Nanjing University of Information Science and Technology, Nanjing, 210044, China</b><br/><b>University of Texas at Arlington, Arlington, TX</b></td><td>('29803023', 'Lin Zhong', 'lin zhong')<br/>('1734954', 'Qingshan Liu', 'qingshan liu')<br/>('39606160', 'Peng Yang', 'peng yang')<br/>('40107085', 'Bo Liu', 'bo liu')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>{linzhong,qsliu,peyang,lb507,dnm}@cs.rutgers.edu, Jzhuang@uta.edu -</td></tr><tr><td>d78373de773c2271a10b89466fe1858c3cab677f</td><td></td><td></td><td></td></tr><tr><td>d78fbd11f12cbc194e8ede761d292dc2c02d38a2</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, +</td></tr><tr><td>d79365336115661b0e8dbbcd4b2aa1f504b91af6</td><td>Variational methods for Conditional Multimodal +<br/>Deep Learning +<br/>Department of Computer Science and Automation +<br/><b>Indian Institute of Science</b></td><td>('2686270', 'Gaurav Pandey', 'gaurav pandey')<br/>('2440174', 'Ambedkar Dukkipati', 'ambedkar dukkipati')</td><td>Email{gp88, ad@csa.iisc.ernet.in +</td></tr><tr><td>d7b6bbb94ac20f5e75893f140ef7e207db7cd483</td><td>Griffith Research Online +<br/>https://research-repository.griffith.edu.au +<br/>Face Recognition across Pose: A +<br/>Review +<br/>Author +<br/>Zhang, Paul, Gao, Yongsheng +<br/>Published +<br/>2009 +<br/>Journal Title +<br/>Pattern Recognition +<br/>DOI +<br/>https://doi.org/10.1016/j.patcog.2009.04.017 +<br/>Copyright Statement +<br/>Copyright 2009 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance +<br/>with the copyright policy of the publisher. Please refer to the journal's website for access to the +<br/>definitive, published version. +<br/>Downloaded from +<br/>http://hdl.handle.net/10072/30193 +</td><td></td><td></td></tr><tr><td>d78373de773c2271a10b89466fe1858c3cab677f</td><td></td><td></td><td></td></tr><tr><td>d78fbd11f12cbc194e8ede761d292dc2c02d38a2</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, <br/>Vol. 8, No. 10, 2017 <br/>Enhancing Gray Scale Images for Face Detection <br/>under Unstable Lighting Condition @@ -9108,7 +10803,10 @@ <br/><b>South China University of Technology</b><br/>Guangzhou, Guangdong, China </td><td>('2588058', 'DI ZHANG', 'di zhang')<br/>('20374749', 'YUN ZHAO', 'yun zhao')<br/>('31866339', 'MINGHUI DU', 'minghui du')</td><td> haihaiwenqi@163.com, zyun@gdmc.edu.cn <br/>ecmhdu@scut.edu.cn -</td></tr><tr><td>d7d166aee5369b79ea2d71a6edd73b7599597aaa</td><td>Fast Subspace Clustering Based on the +</td></tr><tr><td>d700aedcb22a4be374c40d8bee50aef9f85d98ef</td><td>Rethinking Spatiotemporal Feature Learning: +<br/>Speed-Accuracy Trade-offs in Video Classification +<br/>1 Google Research +<br/><b>University of California San Diego</b></td><td>('1817030', 'Saining Xie', 'saining xie')<br/>('40559421', 'Chen Sun', 'chen sun')<br/>('1808244', 'Jonathan Huang', 'jonathan huang')<br/>('1736745', 'Zhuowen Tu', 'zhuowen tu')<br/>('1702318', 'Kevin Murphy', 'kevin murphy')</td><td></td></tr><tr><td>d7d166aee5369b79ea2d71a6edd73b7599597aaa</td><td>Fast Subspace Clustering Based on the <br/>Kronecker Product <br/><b>Beihang University 2Gri th University 3University of York, UK</b></td><td>('38840844', 'Lei Zhou', 'lei zhou')<br/>('3042223', 'Xiao Bai', 'xiao bai')<br/>('6820648', 'Xianglong Liu', 'xianglong liu')<br/>('40582215', 'Jun Zhou', 'jun zhou')<br/>('38987678', 'Hancock Edwin', 'hancock edwin')</td><td></td></tr><tr><td>d79f9ada35e4410cd255db39d7cc557017f8111a</td><td>Journal of Eye Movement Research <br/>7(3):3, 1-8 @@ -9215,6 +10913,12 @@ <br/>Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 05/28/2015 Terms of Use: http://spiedl.org/terms </td><td>('7671296', 'Shaohua Zhang', 'shaohua zhang')<br/>('39584289', 'Hua Yang', 'hua yang')</td><td></td></tr><tr><td>d0ac9913a3b1784f94446db2f1fb4cf3afda151f</td><td>Exploiting Multi-modal Curriculum in Noisy Web Data for <br/>Large-scale Concept Learning <br/><b>School of Computer Science, Carnegie Mellon University, PA, USA</b><br/><b>School of Mathematics and Statistics, Xi an Jiaotong University, P. R. China</b></td><td>('1915796', 'Junwei Liang', 'junwei liang')<br/>('38782499', 'Lu Jiang', 'lu jiang')<br/>('1803714', 'Deyu Meng', 'deyu meng')</td><td>{junweil, lujiang, alex}@cs.cmu.edu, dymeng@mail.xjtu.edu.cn. +</td></tr><tr><td>d0471d5907d6557cf081edf4c7c2296c3c221a38</td><td>A Constrained Deep Neural Network for Ordinal Regression +<br/><b>Nanyang Technological University</b><br/>Rolls-Royce Advanced Technology Centre +<br/>50 Nanyang Avenue, Singapore, 639798 +<br/>6 Seletar Aerospace Rise, Singapore, 797575 +</td><td>('47908585', 'Yanzhu Liu', 'yanzhu liu')<br/>('1799918', 'Chi Keong Goh', 'chi keong goh')</td><td>liuy0109@e.ntu.edu.sg, adamskong@ntu.edu.sg +<br/>ChiKeong.Goh@Rolls-Royce.com </td></tr><tr><td>d0eb3fd1b1750242f3bb39ce9ac27fc8cc7c5af0</td><td></td><td></td><td></td></tr><tr><td>d00c335fbb542bc628642c1db36791eae24e02b7</td><td>Article <br/>Deep Learning-Based Gaze Detection System for <br/>Automobile Drivers Using a NIR Camera Sensor @@ -9349,7 +11053,32 @@ <br/>Object Bank <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences <br/><b>CAS), Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>School of Computer Science, Carnegie Mellon University, PA 15213, USA</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b></td><td>('1731144', 'Xin Liu', 'xin liu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1688086', 'Shaoxin Li', 'shaoxin li')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')</td><td>{xin.liu, shiguang.shan, shaoxin.li}@vipl.ict.ac.cn, alex@cs.cmu.edu; -</td></tr><tr><td>d03baf17dff5177d07d94f05f5791779adf3cd5f</td><td></td><td></td><td></td></tr><tr><td>d0a21f94de312a0ff31657fd103d6b29db823caa</td><td>Facial Expression Analysis +</td></tr><tr><td>d0509afe9c2c26fe021889f8efae1d85b519452a</td><td>Visual Psychophysics for Making Face +<br/>Recognition Algorithms More Explainable +<br/><b>University of Notre Dame, Notre Dame, IN, 46556, USA</b><br/><b>Perceptive Automata, Inc</b><br/><b>Harvard University, Cambridge, MA 02138, USA</b></td><td>('3849184', 'Brandon RichardWebster', 'brandon richardwebster')<br/>('40901458', 'So Yon Kwon', 'so yon kwon')<br/>('40896426', 'Christopher Clarizio', 'christopher clarizio')<br/>('2503235', 'Samuel E. Anthony', 'samuel e. anthony')<br/>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')</td><td></td></tr><tr><td>d03baf17dff5177d07d94f05f5791779adf3cd5f</td><td></td><td></td><td></td></tr><tr><td>d0144d76b8b926d22411d388e7a26506519372eb</td><td>Improving Regression Performance with Distributional Losses +</td><td>('29905816', 'Ehsan Imani', 'ehsan imani')</td><td></td></tr><tr><td>d02e27e724f9b9592901ac1f45830341d37140fe</td><td>DA-GAN: Instance-level Image Translation by Deep Attention Generative +<br/>Adversarial Networks +<br/>The State Universtiy of New York at Buffalo +<br/>The State Universtiy of New York at Buffalo +<br/>Microsoft Research +<br/>Microsoft Research +</td><td>('2327045', 'Shuang Ma', 'shuang ma')<br/>('1735257', 'Chang Wen Chen', 'chang wen chen')<br/>('3247966', 'Jianlong Fu', 'jianlong fu')<br/>('1724211', 'Tao Mei', 'tao mei')</td><td>shuangma@buffalo.edu +<br/>chencw@buffalo.edu +<br/>jianf@microsoft.com +<br/>tmei@microsoft.com +</td></tr><tr><td>d02b32b012ffba2baeb80dca78e7857aaeececb0</td><td>Human Pose Estimation: Extension and Application +<br/>Thesis submitted in partial fulfillment +<br/>of the requirements for the degree of +<br/>Master of Science (By Research) +<br/>in +<br/>Computer Science and Engineering +<br/>by +<br/>201002052 +<br/>Center for Visual Information Technology +<br/><b>International Institute of Information Technology</b><br/>Hyderabad - 500 032, INDIA +<br/>September 2016 +</td><td>('50226534', 'Digvijay Singh', 'digvijay singh')</td><td>digvijay.singh@research.iiit.ac.in +</td></tr><tr><td>d0a21f94de312a0ff31657fd103d6b29db823caa</td><td>Facial Expression Analysis </td><td>('1707876', 'Fernando De la Torre', 'fernando de la torre')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>d03e4e938bcbc25aa0feb83d8a0830f9cd3eb3ea</td><td>Face Recognition with Patterns of Oriented <br/>Edge Magnitudes <br/>1 Vesalis Sarl, Clermont Ferrand, France @@ -9358,10 +11087,17 @@ <br/>for Zero-Shot Action Recognition <br/><b>Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China</b><br/><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, Australia</b><br/><b>School of Computer Science, Carnegie Mellon University, Pittsburgh, USA</b><br/><b>College of Computer Science, Zhejiang University, Zhejiang, China</b></td><td>('2551285', 'Chuang Gan', 'chuang gan')<br/>('2735055', 'Ming Lin', 'ming lin')<br/>('39033919', 'Yi Yang', 'yi yang')<br/>('1755711', 'Yueting Zhuang', 'yueting zhuang')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')</td><td>ganchuang1990@gmail.com, linming04@gmail.com, <br/>yiyang@cs.cmu.edu, yzhuang@zju.edu.cn, alex@cs.cmu.edu +</td></tr><tr><td>d01303062b21cd9ff46d5e3ff78897b8499480de</td><td>Multi-task Learning by Maximizing Statistical Dependence +<br/><b>University of Bath</b><br/><b>University of Bath</b><br/><b>University of Bath</b></td><td>('51013428', 'Youssef A. Mejjati', 'youssef a. mejjati')<br/>('1792288', 'Darren Cosker', 'darren cosker')<br/>('1808255', 'Kwang In Kim', 'kwang in kim')</td><td></td></tr><tr><td>d02c54192dbd0798b43231efe1159d6b4375ad36</td><td>3D Reconstruction and Face Recognition Using Kernel-Based +<br/> ICA and Neural Networks +<br/>Dept. of Electrical Dept. of CSIE Dept. of CSIE +<br/><b>Engineering Chaoyang University Nankai Institute of</b><br/><b>National University of Technology Technology</b></td><td>('1734467', 'Cheng-Jian Lin', 'cheng-jian lin')<br/>('1759040', 'Chi-Yung Lee', 'chi-yung lee')</td><td> of Kaohsiung s9527618@cyut.edu.tw cylee@nkc.edu.tw +<br/>cjlin@nuk.edu.tw </td></tr><tr><td>d00787e215bd74d32d80a6c115c4789214da5edb</td><td>Faster and Lighter Online <br/>Sparse Dictionary Learning <br/>Project report -</td><td>('2714145', 'Jeremias Sulam', 'jeremias sulam')</td><td></td></tr><tr><td>be8c517406528edc47c4ec0222e2a603950c2762</td><td>Harrigan / The new handbook of methods in nonverbal behaviour research 02-harrigan-chap02 Page Proof page 7 +</td><td>('2714145', 'Jeremias Sulam', 'jeremias sulam')</td><td></td></tr><tr><td>d0f54b72e3a3fe7c0e65d7d5a3b30affb275f4c5</td><td>Towards Universal Representation for Unseen Action Recognition +<br/><b>University of California, Merced</b><br/><b>Open Lab, School of Computing, Newcastle University, UK</b><br/><b>Inception Institute of Arti cial Intelligence (IIAI), Abu Dhabi, UAE</b></td><td>('1749901', 'Yi Zhu', 'yi zhu')<br/>('50363618', 'Yang Long', 'yang long')<br/>('1735787', 'Yu Guan', 'yu guan')<br/>('40799321', 'Ling Shao', 'ling shao')</td><td></td></tr><tr><td>be8c517406528edc47c4ec0222e2a603950c2762</td><td>Harrigan / The new handbook of methods in nonverbal behaviour research 02-harrigan-chap02 Page Proof page 7 <br/>17.6.2005 <br/>5:45pm <br/>B A S I C R E S E A RC H @@ -9382,7 +11118,10 @@ <br/><b>Stony Brook University, Stony Brook NY 11794, USA</b><br/><b>Columbia University, New York NY 10027, USA</b><br/><b>University of California, Berkeley, Berkeley CA 94720, USA</b></td><td>('1685538', 'Tamara L. Berg', 'tamara l. berg')<br/>('39668247', 'Alexander C. Berg', 'alexander c. berg')<br/>('9676096', 'Jonathan Shih', 'jonathan shih')</td><td>tlberg@cs.sunysb.edu, <br/>aberg@cs.columbia.edu, <br/>jmshih@berkeley.edu. -</td></tr><tr><td>beb49072f5ba79ed24750108c593e8982715498e</td><td>STUDENT, PROF, COLLABORATOR: BMVC AUTHOR GUIDELINES +</td></tr><tr><td>be48b5dcd10ab834cd68d5b2a24187180e2b408f</td><td>FOR PERSONAL USE ONLY +<br/>Constrained Low-rank Learning Using Least +<br/>Squares Based Regularization +</td><td>('2420746', 'Ping Li', 'ping li')<br/>('1720236', 'Jun Yu', 'jun yu')<br/>('48958393', 'Meng Wang', 'meng wang')<br/>('1763785', 'Luming Zhang', 'luming zhang')<br/>('1724421', 'Deng Cai', 'deng cai')<br/>('50080046', 'Xuelong Li', 'xuelong li')</td><td></td></tr><tr><td>beb49072f5ba79ed24750108c593e8982715498e</td><td>STUDENT, PROF, COLLABORATOR: BMVC AUTHOR GUIDELINES <br/>GeneGAN: Learning Object Transfiguration <br/>and Attribute Subspace from Unpaired Data <br/>1 Megvii Inc. @@ -9396,11 +11135,87 @@ <br/>fdq@megvii.com <br/>hqy@megvii.com <br/>hwr@megvii.com +</td></tr><tr><td>be4a20113bc204019ea79c6557a0bece23da1121</td><td>DeepCache: Principled Cache for Mobile Deep Vision +<br/>We present DeepCache, a principled cache design for deep learning +<br/>inference in continuous mobile vision. DeepCache benefits model +<br/>execution efficiency by exploiting temporal locality in input video +<br/>streams. It addresses a key challenge raised by mobile vision: the +<br/>cache must operate under video scene variation, while trading off +<br/>among cacheability, overhead, and loss in model accuracy. At the +<br/>input of a model, DeepCache discovers video temporal locality by ex- +<br/>ploiting the video’s internal structure, for which it borrows proven +<br/>heuristics from video compression; into the model, DeepCache prop- +<br/>agates regions of reusable results by exploiting the model’s internal +<br/>structure. Notably, DeepCache eschews applying video heuristics to +<br/>model internals which are not pixels but high-dimensional, difficult- +<br/>to-interpret data. +<br/>Our implementation of DeepCache works with unmodified deep +<br/>learning models, requires zero developer’s manual effort, and is +<br/>therefore immediately deployable on off-the-shelf mobile devices. +<br/>Our experiments show that DeepCache saves inference execution +<br/>time by 18% on average and up to 47%. DeepCache reduces system +<br/>energy consumption by 20% on average. +<br/>CCS Concepts: • Human-centered computing → Ubiquitous +<br/>and mobile computing; • Computing methodologies → Com- +<br/>puter vision tasks; +<br/>Additional Key Words and Phrases: Deep Learning; Mobile Vision; +<br/>Cache +<br/>INTRODUCTION +<br/>With ubiquitous cameras on mobile and wearable devices, +<br/>continuous mobile vision emerges to enable a variety of com- +<br/><b>pelling applications, including cognitive assistance [29], life</b><br/>style monitoring [61], and street navigation [27]. To support +<br/>continuous mobile vision, Convolutional Neural Network +<br/>2018. XXXX-XXXX/2018/9-ART $15.00 +<br/>https://doi.org/10.1145/3241539.3241563 +<br/>Fig. 1. The overview of DeepCache. +<br/>(CNN) is recognized as the state-of-the-art algorithm: a soft- +<br/>ware runtime, called deep learning engine, ingests a continu- +<br/>ous stream of video images1; for each input frame the engine +<br/>executes a CNN model as a cascade of layers, produces in- +<br/>termediate results called feature maps, and outputs inference +<br/>results. Such CNN executions are known for their high time +<br/>and space complexity, stressing resource-constrained mobile +<br/>devices. Although CNN execution can be offloaded to the +<br/>cloud [2, 34], it becomes increasingly compelling to execute +<br/>CNNs on device [27, 44, 52], which ensures fast inference, pre- +<br/>serves user privacy, and remains unaffected by poor Internet +<br/>connectivity. +<br/>To afford costly CNN on resource-constrained mobile/wear- +<br/>able devices, we set to exploit a mobile video stream’s tempo- +<br/>ral locality, i.e., rich information redundancy among consec- +<br/>utive video frames [27, 51, 52]. Accordingly, a deep learning +<br/>engine can cache results when it executes CNN over a mo- +<br/>bile video, by using input frame contents as cache keys and +<br/>inference results as cache values. Such caching is expected +<br/>to reduce the engine’s resource demand significantly. +<br/>Towards effective caching and result reusing, we face two +<br/>major challenges. 1) Reusable results lookup: Classic caches, +<br/>e.g., the web browser cache, look up cached values (e.g., web +<br/>pages) based on key equivalence (e.g., identical URLs). This +<br/>does not apply to a CNN cache: its keys, i.e., mobile video +<br/>contents, often undergo moderate scene variation over time. +<br/>The variation is caused by environmental changes such as +<br/>1We refer to them as a mobile video stream in the remainder of the paper. +<br/>, Vol. 1, No. 1, Article . Publication date: September 2018. +</td><td>('2529558', 'Mengwei Xu', 'mengwei xu')<br/>('46694806', 'Mengze Zhu', 'mengze zhu')<br/>('3180228', 'Yunxin Liu', 'yunxin liu')<br/>('1774176', 'Felix Xiaozhu Lin', 'felix xiaozhu lin')<br/>('8016688', 'Xuanzhe Liu', 'xuanzhe liu')<br/>('8016688', 'Xuanzhe Liu', 'xuanzhe liu')<br/>('2529558', 'Mengwei Xu', 'mengwei xu')</td><td>xumengwei@pku.edu.cn; Mengze Zhu, Peking University, MoE, Beijing, +<br/>China, zhumz@pku.edu.cn; Yunxin Liu, Microsoft Research, Beijing, China, +<br/>yunxin.liu@microsoft.com; Felix Xiaozhu Lin, Purdue ECE, West Lafayette, +<br/>Indiana, USA, xzl@purdue.edu; Xuanzhe Liu, Peking University, MoE, Bei- +<br/>jing, China, xzl@pku.edu.cn. </td></tr><tr><td>becd5fd62f6301226b8e150e1a5ec3180f748ff8</td><td>Robust and Practical Face Recognition via <br/>Structured Sparsity <br/>1Advanced Digital Sciences Center, Singapore <br/>2 Microsoft Research Asia, Beijing, China -<br/><b>University of Illinois at Urbana-Champaign</b></td><td>('2370507', 'Kui Jia', 'kui jia')<br/>('1926757', 'Tsung-Han Chan', 'tsung-han chan')<br/>('1700297', 'Yi Ma', 'yi ma')</td><td></td></tr><tr><td>bebb8a97b2940a4e5f6e9d3caf6d71af21585eda</td><td>Mapping Emotional Status to Facial Expressions +<br/><b>University of Illinois at Urbana-Champaign</b></td><td>('2370507', 'Kui Jia', 'kui jia')<br/>('1926757', 'Tsung-Han Chan', 'tsung-han chan')<br/>('1700297', 'Yi Ma', 'yi ma')</td><td></td></tr><tr><td>be437b53a376085b01ebd0f4c7c6c9e40a4b1a75</td><td>ISSN (Online) 2321 – 2004 +<br/>ISSN (Print) 2321 – 5526 +<br/> INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN ELECTRICAL, ELECTRONICS, INSTRUMENTATION AND CONTROL ENGINEERING +<br/> Vol. 4, Issue 5, May 2016 +<br/>IJIREEICE +<br/>Face Recognition and Retrieval Using Cross +<br/>Age Reference Coding +<br/> BE, DSCE, Bangalore1 +<br/>Assistant Professor, DSCE, Bangalore2 +</td><td>('4427719', 'Chandrakala', 'chandrakala')</td><td></td></tr><tr><td>bebb8a97b2940a4e5f6e9d3caf6d71af21585eda</td><td>Mapping Emotional Status to Facial Expressions <br/><b>Tsinghua University</b><br/>Beijing 100084, P. R. China </td><td>('3165307', 'Yangzhou Du', 'yangzhou du')<br/>('2693354', 'Xueyin Lin', 'xueyin lin')</td><td>dyz99@mails.tsinghua.edu.cn; lxy-dcs@tsinghua.edu.cn </td></tr><tr><td>be07f2950771d318a78d2b64de340394f7d6b717</td><td>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/290192867 @@ -9421,13 +11236,39 @@ <br/>letting you access and read them immediately. <br/>Available from: Djamel Bouchaffra <br/>Retrieved on: 11 February 2016 -</td><td></td><td></td></tr><tr><td>beb4546ae95f79235c5f3c0e9cc301b5d6fc9374</td><td>A Modular Approach to Facial Expression Recognition +</td><td></td><td></td></tr><tr><td>be4f7679797777f2bc1fd6aad8af67cce5e5ce87</td><td>Interestingness Prediction +<br/>by Robust Learning to Rank(cid:2) +<br/><b>School of EECS, Queen Mary University of London, UK</b><br/><b>School of Mathematical Sciences, Peking University, China</b></td><td>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('1746280', 'Yuan Yao', 'yuan yao')</td><td>{y.fu,t.hospedales,t.xiang,s.gong}@qmul.ac.uk, yuany@math.pku.edu.cn +</td></tr><tr><td>beb4546ae95f79235c5f3c0e9cc301b5d6fc9374</td><td>A Modular Approach to Facial Expression Recognition <br/><b>Cognitive Arti cial Intelligence, Utrecht University, Heidelberglaan 6, 3584 CD, Utrecht</b><br/><b>Intelligent Systems Group, Utrecht University, Padualaan 14, 3508 TB, Utrecht</b></td><td>('31822812', 'Michal Sindlar', 'michal sindlar')<br/>('1727399', 'Marco Wiering', 'marco wiering')</td><td>sindlar@phil.uu.nl <br/>marco@cs.uu.nl -</td></tr><tr><td>bec31269632c17206deb90cd74367d1e6586f75f</td><td>Large-scale Datasets: Faces with Partial +</td></tr><tr><td>be28ed1be084385f5d389db25fd7f56cd2d7f7bf</td><td>Exploring Computation-Communication Tradeoffs +<br/>in Camera Systems +<br/><b>Paul G. Allen School of Computer Science and Engineering, University of Washington</b><br/><b>University of Washington</b></td><td>('19170117', 'Amrita Mazumdar', 'amrita mazumdar')<br/>('47108160', 'Thierry Moreau', 'thierry moreau')<br/>('37270394', 'Meghan Cowan', 'meghan cowan')<br/>('1698528', 'Armin Alaghi', 'armin alaghi')<br/>('1717411', 'Luis Ceze', 'luis ceze')<br/>('1723213', 'Mark Oskin', 'mark oskin')<br/>('46829693', 'Visvesh Sathe', 'visvesh sathe')</td><td>{amrita,moreau,cowanmeg}@cs.washington.edu, sungk9@uw.edu, {armin,luisceze,oskin}@cs.washington.edu, sathe@uw.edu +</td></tr><tr><td>bebea83479a8e1988a7da32584e37bfc463d32d4</td><td>Discovery of Latent 3D Keypoints via +<br/>End-to-end Geometric Reasoning +<br/>Google AI +</td><td>('37016781', 'Supasorn Suwajanakorn', 'supasorn suwajanakorn')<br/>('2704494', 'Jonathan Tompson', 'jonathan tompson')</td><td>{supasorn, snavely, tompson, mnorouzi}@google.com +</td></tr><tr><td>bed06e7ff0b510b4a1762283640b4233de4c18e0</td><td>Bachelor Project +<br/>Czech +<br/>Technical +<br/><b>University</b><br/>in Prague +<br/>F3 +<br/>Faculty of Electrical Engineering +<br/>Department of Cybernetics +<br/>Face Interpretation Problems on Low +<br/>Quality Images +<br/>Supervisor: Ing. Jan Čech, Ph.D +<br/>May 2018 +</td><td></td><td></td></tr><tr><td>bec31269632c17206deb90cd74367d1e6586f75f</td><td>Large-scale Datasets: Faces with Partial <br/>Occlusions and Pose Variations in the Wild <br/><b>Wayne State University</b><br/>Detroit, MI, USA 48120 </td><td>('2489629', 'Zeyad Hailat', 'zeyad hailat')<br/>('35265528', 'Xuewen Chen', 'xuewen chen')</td><td>Email: ∗tarik alafif@wayne.edu, †zmhailat@wayne.edu, ‡melih.aslan@wayne.edu, §xuewen.chen@wayne.edu +</td></tr><tr><td>be5276e9744c4445fe5b12b785650e8f173f56ff</td><td>Spatio-temporal VLAD Encoding for +<br/>Human Action Recognition in Videos +<br/><b>University of Trento, Italy</b><br/><b>University Politehnica of Bucharest, Romania</b><br/><b>University of Tokyo, Japan</b></td><td>('3429470', 'Ionut C. Duta', 'ionut c. duta')<br/>('1796198', 'Bogdan Ionescu', 'bogdan ionescu')<br/>('1712839', 'Kiyoharu Aizawa', 'kiyoharu aizawa')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td>{ionutcosmin.duta, niculae.sebe}@unitn.it +<br/>bionescu@imag.pub.ro +<br/>aizawa@hal.t.u-tokyo.ac.jp </td></tr><tr><td>be57d2aaab615ec8bc1dd2dba8bee41a4d038b85</td><td>Automatic Analysis of Naturalistic Hand-Over-Face Gestures <br/><b>University of Cambridge</b><br/>One of the main factors that limit the accuracy of facial analysis systems is hand occlusion. As the face <br/>becomes occluded, facial features are lost, corrupted, or erroneously detected. Hand-over-face occlusions are @@ -9466,10 +11307,26 @@ <br/>without fee provided that copies are not made or distributed for profit or commercial advantage and that <br/>copies show this notice on the first page or initial screen of a display along with the full citation. Copyrights for </td><td>('2022940', 'Marwa Mahmoud', 'marwa mahmoud')<br/>('39626495', 'Peter Robinson', 'peter robinson')<br/>('2022940', 'Marwa Mahmoud', 'marwa mahmoud')<br/>('39626495', 'Peter Robinson', 'peter robinson')</td><td>emails: {Marwa.Mahmoud, Tadas.Baltrusaitis, Peter.Robinson}@cl.cam.ac.uk. +</td></tr><tr><td>be4f18e25b06f430e2de0cc8fddcac8585b00beb</td><td>STUDENT, PROF, COLLABORATOR: BMVC AUTHOR GUIDELINES +<br/>A New Face Recognition Algorithm based on +<br/>Dictionary Learning for a Single Training +<br/>Sample per Person +<br/>Ian Wassell +<br/>Computer Laboratory, +<br/><b>University of Cambridge</b></td><td>('1681842', 'Yang Liu', 'yang liu')</td><td>yl504@cam.ac.uk +<br/>ijw24@cam.ac.uk </td></tr><tr><td>bef503cdfe38e7940141f70524ee8df4afd4f954</td><td></td><td></td><td></td></tr><tr><td>beab10d1bdb0c95b2f880a81a747f6dd17caa9c2</td><td>DeepDeblur: Fast one-step blurry face images restoration <br/>Tsinghua Unversity </td><td>('2766905', 'Lingxiao Wang', 'lingxiao wang')<br/>('2112160', 'Yali Li', 'yali li')<br/>('1678689', 'Shengjin Wang', 'shengjin wang')</td><td>wlx16@mails.tsinghua.edu.cn, liyali@ocrserv.ee.tsinghua.edu.cn, wgsgj@tsinghua.edu.cn -</td></tr><tr><td>b3b532e8ea6304446b1623e83b0b9a96968f926c</td><td>Joint Network based Attention for Action Recognition +</td></tr><tr><td>b331ca23aed90394c05f06701f90afd550131fe3</td><td>Zhou et al. EURASIP Journal on Image and Video Processing (2018) 2018:49 +<br/>https://doi.org/10.1186/s13640-018-0287-5 +<br/>EURASIP Journal on Image +<br/>and Video Processing +<br/>R ES EAR CH +<br/>Double regularized matrix factorization for +<br/>image classification and clustering +<br/>Open Access +</td><td>('39147685', 'Wei Zhou', 'wei zhou')<br/>('7513726', 'Chengdong Wu', 'chengdong wu')<br/>('46583983', 'Jianzhong Wang', 'jianzhong wang')<br/>('9305845', 'Xiaosheng Yu', 'xiaosheng yu')<br/>('50130800', 'Yugen Yi', 'yugen yi')</td><td></td></tr><tr><td>b3b532e8ea6304446b1623e83b0b9a96968f926c</td><td>Joint Network based Attention for Action Recognition <br/>1 National Engineering Laboratory for Video Technology, School of EE&CS, <br/><b>Peking University, Beijing, China</b><br/>2 Cooperative Medianet Innovation Center, China <br/>3 School of Information and Electronics, @@ -9550,7 +11407,11 @@ <br/><b>School of Electrical and Computer Engineering, Cornell University</b><br/>116 Ward Hall, Ithaca, NY 14853, USA <br/>3 JSPS Postdoctoral Fellow for Research Abroad </td><td>('2759239', 'Toshihiko Yamasaki', 'toshihiko yamasaki')<br/>('21152852', 'Tomoaki Matsunami', 'tomoaki matsunami')</td><td>{yamasaki,matsunami}@hal.t.u-tokyo.ac.jp -</td></tr><tr><td>b340f275518aa5dd2c3663eed951045a5b8b0ab1</td><td>Visual Inference of Human Emotion and Behaviour +</td></tr><tr><td>b3cb91a08be4117d6efe57251061b62417867de9</td><td>T. Swearingen and A. Ross. "A label propagation approach for predicting missing biographic labels in +<br/>A Label Propagation Approach for +<br/>Predicting Missing Biographic Labels +<br/>in Face-Based Biometric Records +</td><td>('3153117', 'Thomas Swearingen', 'thomas swearingen')<br/>('1698707', 'Arun Ross', 'arun ross')</td><td></td></tr><tr><td>b340f275518aa5dd2c3663eed951045a5b8b0ab1</td><td>Visual Inference of Human Emotion and Behaviour <br/>Dept of Computer Science <br/><b>Queen Mary College, London</b><br/>Dept of Computer Science <br/><b>Queen Mary College, London</b><br/>Dept of Computer Science @@ -9560,6 +11421,18 @@ </td><td>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('10795229', 'Caifeng Shan', 'caifeng shan')<br/>('1700927', 'Tao Xiang', 'tao xiang')</td><td>sgg@dcs.qmul.ac.uk <br/>cfshan@dcs.qmul.ac.uk <br/>txiang@dcs.qmul.ac.uk +</td></tr><tr><td>b3200539538eca54a85223bf0ec4f3ed132d0493</td><td>Action Anticipation with RBF Kernelized +<br/>Feature Mapping RNN +<br/>Hartley[0000−0002−5005−0191] +<br/><b>The Australian National University, Australia</b></td><td>('11519650', 'Yuge Shi', 'yuge shi')</td><td></td></tr><tr><td>b3b467961ba66264bb73ffe00b1830d7874ae8ce</td><td>Finding Tiny Faces +<br/><b>Robotics Institute</b><br/><b>Carnegie Mellon University</b><br/>Figure 1: We describe a detector that can find around 800 faces out of the reportedly 1000 present, by making use of novel +<br/>characterizations of scale, resolution, and context to find small objects. Detector confidence is given by the colorbar on the +<br/>right: can you confidently identify errors? +</td><td>('2894848', 'Peiyun Hu', 'peiyun hu')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td>{peiyunh,deva}@cs.cmu.edu +</td></tr><tr><td>b3ba7ab6de023a0d58c741d6abfa3eae67227caf</td><td>Zero-Shot Activity Recognition with Verb Attribute Induction +<br/>Paul G. Allen School of Computer Science & Engineering +<br/><b>University of Washington</b><br/>Seattle, WA 98195, USA +</td><td>('2545335', 'Rowan Zellers', 'rowan zellers')<br/>('1699545', 'Yejin Choi', 'yejin choi')</td><td>{rowanz,yejin}@cs.washington.edu </td></tr><tr><td>b375db63742f8a67c2a7d663f23774aedccc84e5</td><td>Brain-inspired Classroom Occupancy <br/>Monitoring on a Low-Power Mobile Platform <br/><b>Electronic and Information Engineering, University of Bologna, Italy</b><br/>†Integrated Systems Laboratory, ETH Zurich, Switzerland @@ -9586,7 +11459,27 @@ <br/>Image <br/><b>Institute of Automation, Chinese Academy of</b><br/>Sciences, Beijing, 100080, China, </td><td>('29948255', 'Haitao Wang', 'haitao wang')<br/>('1744302', 'Yangsheng Wang', 'yangsheng wang')</td><td>Email: {htwang,wys}@nlpr.ia.ac.cn -</td></tr><tr><td>b3658514a0729694d86a8b89c875a66cde20480c</td><td>Improving the Robustness of Subspace Learning +</td></tr><tr><td>b32cf547a764a4efa475e9c99a72a5db36eeced6</td><td>UvA-DARE (Digital Academic Repository) +<br/>Mimicry of ingroup and outgroup emotional expressions +<br/>Sachisthal, M.S.M.; Sauter, D.A.; Fischer, A.H. +<br/>Published in: +<br/>Comprehensive Results in Social Psychology +<br/>DOI: +<br/>10.1080/23743603.2017.1298355 +<br/>Link to publication +<br/>Citation for published version (APA): +<br/>Sachisthal, M. S. M., Sauter, D. A., & Fischer, A. H. (2016). Mimicry of ingroup and outgroup emotional +<br/>expressions. Comprehensive Results in Social Psychology, 1(1-3), 86-105. DOI: +<br/>10.1080/23743603.2017.1298355 +<br/>General rights +<br/>It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +<br/>other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +<br/>Disclaimer/Complaints regulations +<br/>If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +<br/>your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +<br/><b>the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam</b><br/>The Netherlands. You will be contacted as soon as possible. +<br/>Download date: 08 Aug 2018 +<br/><b>UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl</b></td><td></td><td></td></tr><tr><td>b3658514a0729694d86a8b89c875a66cde20480c</td><td>Improving the Robustness of Subspace Learning <br/>Techniques for Facial Expression Recognition <br/><b>Aristotle University of Thessaloniki</b><br/>Box 451, 54124 Thessaloniki, Greece </td><td>('2342345', 'Dimitris Bolis', 'dimitris bolis')<br/>('2447585', 'Anastasios Maronidis', 'anastasios maronidis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td>email: {mpolis, amaronidis, tefas, pitas}@aiia.csd.auth.gr (cid:63) @@ -9600,7 +11493,16 @@ <br/>1 <br/>The State of the Art <br/><b>College of Computing, Georgia Institute of Technology</b></td><td>('3115428', 'Vinay Bettadapura', 'vinay bettadapura')</td><td>vinay@gatech.edu -</td></tr><tr><td>df8da144a695269e159fb0120bf5355a558f4b02</td><td>International Journal of Computer Applications (0975 – 8887) +</td></tr><tr><td>b3afa234996f44852317af382b98f5f557cab25a</td><td></td><td></td><td></td></tr><tr><td>df90850f1c153bfab691b985bfe536a5544e438b</td><td>FACE TRACKING ALGORITHM ROBUST TO POSE, +<br/>ILLUMINATION AND FACE EXPRESSION CHANGES: A 3D +<br/>PARAMETRIC MODEL APPROACH +<br/><b></b><br/>via Bramante 65 - 26013, Crema (CR), Italy +<br/>Luigi Arnone, Fabrizio Beverina +<br/>STMicroelectronics - Advanced System Technology Group +<br/>via Olivetti 5 - 20041, Agrate Brianza, Italy +<br/>Keywords: +<br/>Face tracking, expression changes, FACS, illumination changes. +</td><td>('3330245', 'Marco Anisetti', 'marco anisetti')<br/>('2061298', 'Valerio Bellandi', 'valerio bellandi')</td><td></td></tr><tr><td>df8da144a695269e159fb0120bf5355a558f4b02</td><td>International Journal of Computer Applications (0975 – 8887) <br/>International Conference on Recent Trends in engineering & Technology - 2013(ICRTET'2013) <br/>Face Recognition using PCA and Eigen Face <br/>Approach @@ -9623,6 +11525,9 @@ <br/>Tel: +44 (0)1752 584890 <br/>Fax: +44 (0)1752 584808 </td><td>('39557512', 'Chang Hong Liu', 'chang hong liu')</td><td>Email: chris.longmore@plymouth.ac.uk +</td></tr><tr><td>df577a89830be69c1bfb196e925df3055cafc0ed</td><td>Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions +<br/>UC Berkeley +</td><td>('3130257', 'Bichen Wu', 'bichen wu')<br/>('40417702', 'Alvin Wan', 'alvin wan')<br/>('27577617', 'Xiangyu Yue', 'xiangyu yue')<br/>('1755487', 'Sicheng Zhao', 'sicheng zhao')<br/>('30096597', 'Noah Golmant', 'noah golmant')<br/>('3647010', 'Amir Gholaminejad', 'amir gholaminejad')<br/>('30503077', 'Joseph Gonzalez', 'joseph gonzalez')<br/>('1732330', 'Kurt Keutzer', 'kurt keutzer')</td><td>{bichen,alvinwan,xyyue,phj,schzhao,noah.golmant,amirgh,jegonzal,keutzer}@berkeley.edu </td></tr><tr><td>df0e280cae018cebd5b16ad701ad101265c369fa</td><td>Deep Attributes from Context-Aware Regional Neural Codes <br/><b>Image Processing Center, Beihang University</b><br/>2 Intel Labs China <br/><b>Columbia University</b></td><td>('2780589', 'Jianwei Luo', 'jianwei luo')<br/>('35423937', 'Jianguo Li', 'jianguo li')<br/>('1715001', 'Jun Wang', 'jun wang')<br/>('1791565', 'Zhiguo Jiang', 'zhiguo jiang')<br/>('6060281', 'Yurong Chen', 'yurong chen')</td><td></td></tr><tr><td>dfabe7ef245ca68185f4fcc96a08602ee1afb3f7</td><td></td><td></td><td></td></tr><tr><td>df51dfe55912d30fc2f792561e9e0c2b43179089</td><td>Face Hallucination using Linear Models of Coupled @@ -9635,7 +11540,10 @@ <br/>The research community has lately focused on the latter <br/>category of super-resolution methods, since they can provide <br/>higher quality images and larger magnification factors. -</td><td>('1805605', 'Reuben A. Farrugia', 'reuben a. farrugia')<br/>('1780587', 'Christine Guillemot', 'christine guillemot')</td><td></td></tr><tr><td>df054fa8ee6bb7d2a50909939d90ef417c73604c</td><td>Image Quality-Aware Deep Networks Ensemble for Efficient +</td><td>('1805605', 'Reuben A. Farrugia', 'reuben a. farrugia')<br/>('1780587', 'Christine Guillemot', 'christine guillemot')</td><td></td></tr><tr><td>df2c685aa9c234783ab51c1aa1bf1cb5d71a3dbb</td><td>SREFI: Synthesis of Realistic Example Face Images +<br/><b>University of Notre Dame, USA</b><br/><b>FaceTec, Inc</b></td><td>('40061203', 'Sandipan Banerjee', 'sandipan banerjee')<br/>('3365839', 'John S. Bernhard', 'john s. bernhard')<br/>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')<br/>('1799014', 'Kevin W. Bowyer', 'kevin w. bowyer')<br/>('1704876', 'Patrick J. Flynn', 'patrick j. flynn')</td><td>{sbanerj1, wscheire, kwb, flynn}@nd.edu +<br/>jsbernhardjr@gmail.com +</td></tr><tr><td>df054fa8ee6bb7d2a50909939d90ef417c73604c</td><td>Image Quality-Aware Deep Networks Ensemble for Efficient <br/>Gender Recognition in the Wild <br/><b>Augmented Vision Lab, Technical University Kaiserslautern, Kaiserslautern, Germany</b><br/><b>German Research Center for Arti cial Intelligence (DFKI), Kaiserslautern, Germany</b><br/>Keywords: <br/>Gender, Face, Deep Neural Networks, Quality, In the Wild @@ -9643,7 +11551,11 @@ </td></tr><tr><td>df80fed59ffdf751a20af317f265848fe6bfb9c9</td><td>1666 <br/>Learning Deep Sharable and Structural <br/>Detectors for Face Alignment -</td><td>('40387982', 'Hao Liu', 'hao liu')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('2632601', 'Jianjiang Feng', 'jianjiang feng')<br/>('25060740', 'Jie Zhou', 'jie zhou')</td><td></td></tr><tr><td>dff838ba0567ef0a6c8fbfff9837ea484314efc6</td><td>Progress Report, MSc. Dissertation: On-line +</td><td>('40387982', 'Hao Liu', 'hao liu')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('2632601', 'Jianjiang Feng', 'jianjiang feng')<br/>('25060740', 'Jie Zhou', 'jie zhou')</td><td></td></tr><tr><td>dfd8602820c0e94b624d02f2e10ce6c798193a25</td><td>STRUCTURED ANALYSIS DICTIONARY LEARNING FOR IMAGE CLASSIFICATION +<br/>Department of Electrical and Computer Engineering +<br/><b>North Carolina State University, Raleigh, NC, USA</b><br/>†Army Research Office, RTP, Raleigh, NC, USA +</td><td>('49501811', 'Wen Tang', 'wen tang')<br/>('1733181', 'Ashkan Panahi', 'ashkan panahi')<br/>('1769928', 'Hamid Krim', 'hamid krim')<br/>('2622498', 'Liyi Dai', 'liyi dai')</td><td>{wtang6, apanahi, ahk}@ncsu.edu, liyi.dai@us.army.mil +</td></tr><tr><td>dff838ba0567ef0a6c8fbfff9837ea484314efc6</td><td>Progress Report, MSc. Dissertation: On-line <br/>Random Forest for Face Detection <br/>School of Computer Science <br/><b>The University of Manchester</b><br/>May 9, 2014 @@ -9690,6 +11602,10 @@ </td><td>('1698066', 'Rui Wang', 'rui wang')<br/>('1690035', 'Andrew T. Campbell', 'andrew t. campbell')<br/>('2253140', 'Xia Zhou', 'xia zhou')</td><td>rui.wang@cs.dartmouth.edu <br/>campbell@cs.dartmouth.edu <br/>xia@cs.dartmouth.edu +</td></tr><tr><td>df9269657505fcdc1e10cf45bbb8e325678a40f5</td><td>INTERSPEECH 2016 +<br/>September 8–12, 2016, San Francisco, USA +<br/>Open-Domain Audio-Visual Speech Recognition: A Deep Learning Approach +<br/><b>Carnegie Mellon University</b></td><td>('37467623', 'Yajie Miao', 'yajie miao')<br/>('1740721', 'Florian Metze', 'florian metze')</td><td>{ymiao,fmetze}@cs.cmu.edu </td></tr><tr><td>dfb6aa168177d4685420fcb184def0aa7db7cddb</td><td>The Effect of Lighting Direction/Condition on the Performance <br/>of Face Recognition Algorithms <br/><b>West Virginia University, Morgantown, WV</b><br/><b>University of Miami, Coral Gables, FL</b></td><td>('1722978', 'Gamal Fahmy', 'gamal fahmy')<br/>('4562956', 'Ahmed El-Sherbeeny', 'ahmed el-sherbeeny')<br/>('9449390', 'Mohamed Abdel-Mottaleb', 'mohamed abdel-mottaleb')<br/>('16279046', 'Hany Ammar', 'hany ammar')</td><td></td></tr><tr><td>df2841a1d2a21a0fc6f14fe53b6124519f3812f9</td><td>Learning Image Attributes @@ -9700,7 +11616,12 @@ <br/><b>Brown University</b><br/>Providence, RI 02912 </td><td>('2059199', 'Soravit Changpinyo', 'soravit changpinyo')<br/>('1799035', 'Erik B. Sudderth', 'erik b. sudderth')</td><td>schangpi@cs.brown.edu <br/>sudderth@cs.brown.edu -</td></tr><tr><td>df5fe0c195eea34ddc8d80efedb25f1b9034d07d</td><td>Robust Modified Active Shape Model for Automatic Facial Landmark +</td></tr><tr><td>dfecaedeaf618041a5498cd3f0942c15302e75c3</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>A Recursive Framework for Expression Recognition: From +<br/>Web Images to Deep Models to Game Dataset +<br/>Received: date / Accepted: date +</td><td>('48625314', 'Wei Li', 'wei li')</td><td></td></tr><tr><td>df5fe0c195eea34ddc8d80efedb25f1b9034d07d</td><td>Robust Modified Active Shape Model for Automatic Facial Landmark <br/>Annotation of Frontal Faces </td><td>('2363348', 'Keshav Seshadri', 'keshav seshadri')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td></td></tr><tr><td>df2494da8efa44d70c27abf23f73387318cf1ca8</td><td>RESEARCH ARTICLE <br/>Supervised Filter Learning for Representation @@ -9723,7 +11644,8 @@ </td><td>('2272441', 'Ambra Demontis', 'ambra demontis')<br/>('1684175', 'Battista Biggio', 'battista biggio')<br/>('1716261', 'Giorgio Fumera', 'giorgio fumera')<br/>('1710171', 'Fabio Roli', 'fabio roli')</td><td>{ambra.demontis,battista.biggio,fumera,roli}@diee.unica.it </td></tr><tr><td>daf05febbe8406a480306683e46eb5676843c424</td><td>Robust Subspace Segmentation with Block-diagonal Prior <br/><b>National University of Singapore, Singapore</b><br/><b>Key Lab. of Machine Perception, School of EECS, Peking University, China</b><br/><b>National University of Singapore, Singapore</b></td><td>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('33383055', 'Zhouchen Lin', 'zhouchen lin')<br/>('1678675', 'Huan Xu', 'huan xu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td>1{a0066331,eleyans}@nus.edu.sg, 2zlin@pku.edu.cn, 3mpexuh@nus.edu.sg -</td></tr><tr><td>da15344a4c10b91d6ee2e9356a48cb3a0eac6a97</td><td></td><td></td><td></td></tr><tr><td>da5bfddcfe703ca60c930e79d6df302920ab9465</td><td></td><td></td><td></td></tr><tr><td>dac2103843adc40191e48ee7f35b6d86a02ef019</td><td>854 +</td></tr><tr><td>da4170c862d8ae39861aa193667bfdbdf0ecb363</td><td>Multi-task CNN Model for Attribute Prediction +</td><td>('3282196', 'Abrar H. Abdulnabi', 'abrar h. abdulnabi')<br/>('22804340', 'Gang Wang', 'gang wang')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('2370507', 'Kui Jia', 'kui jia')</td><td></td></tr><tr><td>da15344a4c10b91d6ee2e9356a48cb3a0eac6a97</td><td></td><td></td><td></td></tr><tr><td>da5bfddcfe703ca60c930e79d6df302920ab9465</td><td></td><td></td><td></td></tr><tr><td>dac2103843adc40191e48ee7f35b6d86a02ef019</td><td>854 <br/>Unsupervised Celebrity Face Naming in Web Videos </td><td>('2172810', 'Lei Pang', 'lei pang')<br/>('1751681', 'Chong-Wah Ngo', 'chong-wah ngo')</td><td></td></tr><tr><td>dae420b776957e6b8cf5fbbacd7bc0ec226b3e2e</td><td>RECOGNIZING EMOTIONS IN SPONTANEOUS FACIAL EXPRESSIONS <br/>Institut f¨ur Nachrichtentechnik @@ -9738,7 +11660,12 @@ </td><td>('1899753', 'Ryo Yonetani', 'ryo yonetani')<br/>('37991449', 'Kris M. Kitani', 'kris m. kitani')<br/>('9467266', 'Yoichi Sato', 'yoichi sato')</td><td>yonetani@iis.u-tokyo.ac.jp <br/>kkitani@cs.cmu.edu <br/>ysato@iis.u-tokyo.ac.jp -</td></tr><tr><td>daba8f0717f3f47c272f018d0a466a205eba6395</td><td></td><td></td><td></td></tr><tr><td>b4d694961d3cde43ccef7d8fcf1061fe0d8f97f3</td><td>Rapid Face Recognition Using Hashing +</td></tr><tr><td>daba8f0717f3f47c272f018d0a466a205eba6395</td><td></td><td></td><td></td></tr><tr><td>daefac0610fdeff415c2a3f49b47968d84692e87</td><td>New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics +<br/>Proceedings of NAACL-HLT 2018, pages 1481–1491 +<br/>1481 +</td><td></td><td></td></tr><tr><td>b49affdff167f5d170da18de3efa6fd6a50262a2</td><td>Author manuscript, published in "Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France +<br/>(2008)" +</td><td></td><td></td></tr><tr><td>b4d694961d3cde43ccef7d8fcf1061fe0d8f97f3</td><td>Rapid Face Recognition Using Hashing <br/><b>Australian National University, and NICTA</b><br/><b>Australian National University, and NICTA</b><br/>Canberra, Australia <br/>Canberra, Australia <br/><b>NICTA, and Australian National University</b><br/>Canberra, Australia @@ -9773,7 +11700,23 @@ </td></tr><tr><td>b41374f4f31906cf1a73c7adda6c50a78b4eb498</td><td>This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. <br/>Iterative Gaussianization: From ICA to <br/>Random Rotations -</td><td>('2732577', 'Valero Laparra', 'valero laparra')<br/>('1684246', 'Gustavo Camps-Valls', 'gustavo camps-valls')<br/>('2186866', 'Jesús Malo', 'jesús malo')</td><td></td></tr><tr><td>b4d7ca26deb83cec1922a6964c1193e8dd7270e7</td><td></td><td></td><td></td></tr><tr><td>b40290a694075868e0daef77303f2c4ca1c43269</td><td>第 40 卷 第 4 期 +</td><td>('2732577', 'Valero Laparra', 'valero laparra')<br/>('1684246', 'Gustavo Camps-Valls', 'gustavo camps-valls')<br/>('2186866', 'Jesús Malo', 'jesús malo')</td><td></td></tr><tr><td>b42a97fb47bcd6bfa72e130c08960a77ee96f9ab</td><td>FACIAL EXPRESSION RECOGNITION BASED ON GRAPH-PRESERVING SPARSE +<br/>NON-NEGATIVE MATRIX FACTORIZATION +<br/><b>Institute of Information Science</b><br/><b>Beijing Jiaotong University</b><br/>Beijing 100044, P.R. China +<br/>Qiuqi Ruan +<br/>ACCESS Linnaeus Center +<br/><b>KTH Royal Institute of Technology, Stockholm</b><br/>School of Electrical Engineering +</td><td>('3247912', 'Ruicong Zhi', 'ruicong zhi')<br/>('1749334', 'Markus Flierl', 'markus flierl')</td><td>{05120370, qqruan}@bjtu.edu.cn +<br/>{ruicong, mflierl, bastiaan}@kth.se +</td></tr><tr><td>b4d209845e1c67870ef50a7c37abaf3770563f3e</td><td>GHODRATI, GAVVES, SNOEK: VIDEO TIME +<br/>Video Time: Properties, Encoders and +<br/>Evaluation +<br/>Cees G. M. Snoek +<br/>QUVA Lab +<br/><b>University of Amsterdam</b><br/>Netherlands +</td><td>('3060081', 'Amir Ghodrati', 'amir ghodrati')<br/>('2304222', 'Efstratios Gavves', 'efstratios gavves')</td><td>{a.ghodrati,egavves,cgmsnoek}@uva.nl +</td></tr><tr><td>b4d7ca26deb83cec1922a6964c1193e8dd7270e7</td><td></td><td></td><td></td></tr><tr><td>b4ee64022cc3ccd14c7f9d4935c59b16456067d3</td><td>Unsupervised Cross-Domain Image Generation +</td><td>('40084473', 'Davis Rempe', 'davis rempe')<br/>('9184695', 'Haotian Zhang', 'haotian zhang')</td><td></td></tr><tr><td>b40290a694075868e0daef77303f2c4ca1c43269</td><td>第 40 卷 第 4 期 <br/>2014 年 4 月 <br/>自 动 化 学 报 <br/>ACTA AUTOMATICA SINICA @@ -9813,7 +11756,10 @@ <br/><b>University of Illinois at Urbana-Champaign</b><br/>2 Computer Vision Group, School of Mathematics <br/><b>Institute for studies in theoretical Physics and Mathematics(IPM</b></td><td>('2270286', 'Ali Farhadi', 'ali farhadi')<br/>('1888731', 'Mohsen Hejrati', 'mohsen hejrati')<br/>('21160985', 'Mohammad Amin Sadeghi', 'mohammad amin sadeghi')<br/>('35527128', 'Peter Young', 'peter young')<br/>('3125805', 'Cyrus Rashtchian', 'cyrus rashtchian')<br/>('3118681', 'Julia Hockenmaier', 'julia hockenmaier')</td><td>{afarhad2,pyoung2,crashtc2,juliahmr,daf}@illinois.edu <br/>{m.a.sadeghi,mhejrati}@gmail.com -</td></tr><tr><td>b43b6551ecc556557b63edb8b0dc39901ed0343b</td><td>ICA AND GABOR REPRESENTATION FOR FACIAL EXPRESSION RECOGNITION +</td></tr><tr><td>b4b0bf0cbe1a2c114adde9fac64900b2f8f6fee4</td><td>Autonomous Learning Framework Based on Online Hybrid +<br/>Classifier for Multi-view Object Detection in Video +<br/><b>aSchool of Electronic Information and Mechanics, China University of Geosciences, Wuhan, Hubei 430074, China</b><br/><b>bSchool of Automation, China University of Geosciences, Wuhan, Hubei 430074, China</b><br/><b>cHuizhou School Affiliated to Beijing Normal University, Huizhou 516002, China</b><br/>dNational Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong +<br/><b>University of Science and Technology, Wuhan, 430074, China</b></td><td>('2588731', 'Dapeng Luo', 'dapeng luo')</td><td></td></tr><tr><td>b43b6551ecc556557b63edb8b0dc39901ed0343b</td><td>ICA AND GABOR REPRESENTATION FOR FACIAL EXPRESSION RECOGNITION <br/>I. Buciu C. Kotropoulos <br/>and I. Pitas <br/><b>Aristotle University of Thessaloniki</b></td><td></td><td>GR-54124, Thessaloniki, Box 451, Greece, {nelu,costas,pitas}@zeus.csd.auth.gr @@ -9827,11 +11773,28 @@ <br/>Department of Computer Science <br/><b>University of Texas at Austin</b><br/>May 6, 2011 </td><td>('39573884', 'Andy Luong', 'andy luong')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>aluong@cs.utexas.edu +</td></tr><tr><td>a285b6edd47f9b8966935878ad4539d270b406d1</td><td>Sensors 2011, 11, 9573-9588; doi:10.3390/s111009573 +<br/>OPEN ACCESS +<br/>sensors +<br/>ISSN 1424-8220 +<br/>www.mdpi.com/journal/sensors +<br/>Article +<br/>Facial Expression Recognition Based on Local Binary Patterns +<br/>and Kernel Discriminant Isomap +<br/><b>Taizhou University, Taizhou 317000, China</b><br/><b>School of Physics and Electronic Engineering, Taizhou University, Taizhou 318000, China</b><br/>Tel.: +86-576-8513-7178; Fax: ++86-576-8513-7178. +<br/>Received: 31 August 2011; in revised form: 27 September 2011 / Accepted: 9 October 2011 / +<br/>Published: 11 October 2011 +</td><td>('48551029', 'Xiaoming Zhao', 'xiaoming zhao')<br/>('1695589', 'Shiqing Zhang', 'shiqing zhang')</td><td>E-Mail: tzczsq@163.com +<br/>* Author to whom correspondence should be addressed; E-Mail: tzxyzxm@163.com; </td></tr><tr><td>a2bd81be79edfa8dcfde79173b0a895682d62329</td><td>Multi-Objective Vehicle Routing Problem Applied to <br/>Large Scale Post Office Deliveries <br/>Zenia <br/><b>aSchool of Technology, University of Campinas</b><br/>Paschoal Marmo, 1888, Limeira, SP, Brazil -</td><td>('1788152', 'Luis A. A. Meira', 'luis a. a. meira')<br/>('37279198', 'Paulo S. Martins', 'paulo s. martins')<br/>('7809605', 'Mauro Menzori', 'mauro menzori')</td><td></td></tr><tr><td>a2eb90e334575d9b435c01de4f4bf42d2464effc</td><td>A NEW SPARSE IMAGE REPRESENTATION +</td><td>('1788152', 'Luis A. A. Meira', 'luis a. a. meira')<br/>('37279198', 'Paulo S. Martins', 'paulo s. martins')<br/>('7809605', 'Mauro Menzori', 'mauro menzori')</td><td></td></tr><tr><td>a2359c0f81a7eb032cff1fe45e3b80007facaa2a</td><td>Towards Structured Analysis of Broadcast Badminton Videos +<br/>C.V.Jawahar +<br/>CVIT, KCIS, IIIT Hyderabad +</td><td>('2964097', 'Anurag Ghosh', 'anurag ghosh')<br/>('48039353', 'Suriya Singh', 'suriya singh')</td><td>{anurag.ghosh, suriya.singh}@research.iiit.ac.in, jawahar@iiit.ac.in +</td></tr><tr><td>a2eb90e334575d9b435c01de4f4bf42d2464effc</td><td>A NEW SPARSE IMAGE REPRESENTATION <br/>ALGORITHM APPLIED TO FACIAL <br/>EXPRESSION RECOGNITION <br/>Ioan Buciu and Ioannis Pitas @@ -9992,6 +11955,12 @@ <br/>from Videos <br/><b>University of Science, VNU-HCMC, Ho Chi Minh city, Vietnam</b></td><td>('2187730', 'Dinh-Luan Nguyen', 'dinh-luan nguyen')<br/>('1780348', 'Minh-Triet Tran', 'minh-triet tran')</td><td>1212223@student.hcmus.edu.vn <br/>tmtriet@fit.hcmus.edu.vn +</td></tr><tr><td>a5f11c132eaab258a7cea2d681875af09cddba65</td><td>A spatiotemporal model with visual attention for +<br/>video classification +<br/>Department of Electrical and Computer Engineering +<br/><b>University of California San Diego, La Jolla, California, USA</b><br/>paper proposes a spatiotemporal model in which CNN and +<br/>RNN are concatenated, as shown in Fig. 1. +</td><td>('2493180', 'Mo Shan', 'mo shan')<br/>('50365495', 'Nikolay Atanasov', 'nikolay atanasov')</td><td>Email: {moshan, natanasov}@eng.ucsd.edu </td></tr><tr><td>a546fd229f99d7fe3cf634234e04bae920a2ec33</td><td>RESEARCH ARTICLE <br/>Fast Fight Detection <br/>1 Department of Systems Engineering and Automation, E.T.S.I. Industriales, Ciudad Real, Castilla-La @@ -10108,7 +12077,9 @@ </td><td>('34703740', 'Jonathan Long', 'jonathan long')</td><td></td></tr><tr><td>a51882cfd0706512bf50e12c0a7dd0775285030d</td><td>Cross-Modal Face Matching: Beyond Viewed <br/>Sketches <br/><b>Beijing University of Posts and Telecommunications, Beijing, China. 2School of</b><br/><b>Electronic Engineering and Computer Science Queen Mary University of London</b><br/>London E1 4NS, United Kingdom -</td><td>('2961830', 'Shuxin Ouyang', 'shuxin ouyang')<br/>('1705408', 'Yi-Zhe Song', 'yi-zhe song')<br/>('7823169', 'Xueming Li', 'xueming li')</td><td></td></tr><tr><td>a5c04f2ad6a1f7c50b6aa5b1b71c36af76af06be</td><td></td><td></td><td></td></tr><tr><td>a503eb91c0bce3a83bf6f524545888524b29b166</td><td></td><td></td><td></td></tr><tr><td>a52581a7b48138d7124afc7ccfcf8ec3b48359d0</td><td>http://www.jos.org.cn +</td><td>('2961830', 'Shuxin Ouyang', 'shuxin ouyang')<br/>('1705408', 'Yi-Zhe Song', 'yi-zhe song')<br/>('7823169', 'Xueming Li', 'xueming li')</td><td></td></tr><tr><td>a5c04f2ad6a1f7c50b6aa5b1b71c36af76af06be</td><td></td><td></td><td></td></tr><tr><td>a503eb91c0bce3a83bf6f524545888524b29b166</td><td></td><td></td><td></td></tr><tr><td>a5a44a32a91474f00a3cda671a802e87c899fbb4</td><td>Moments in Time Dataset: one million +<br/>videos for event understanding +</td><td>('2526653', 'Mathew Monfort', 'mathew monfort')<br/>('1804424', 'Bolei Zhou', 'bolei zhou')<br/>('3298267', 'Sarah Adel Bargal', 'sarah adel bargal')<br/>('50112310', 'Alex Andonian', 'alex andonian')<br/>('12082007', 'Tom Yan', 'tom yan')<br/>('40544169', 'Kandan Ramakrishnan', 'kandan ramakrishnan')<br/>('33421444', 'Quanfu Fan', 'quanfu fan')<br/>('1856025', 'Carl Vondrick', 'carl vondrick')<br/>('31735139', 'Aude Oliva', 'aude oliva')</td><td></td></tr><tr><td>a52581a7b48138d7124afc7ccfcf8ec3b48359d0</td><td>http://www.jos.org.cn <br/>Tel/Fax: +86-10-62562563 <br/>ISSN 1000-9825, CODEN RUXUEW <br/>Journal of Software, Vol.17, No.3, March 2006, pp.525−534 @@ -10124,7 +12095,8 @@ <br/>face reconstruction. Journal of Software, 2006,17(3):525−534. http://www.jos.org.cn/1000-9825/17/525.htm </td><td>('2100752', 'GAO Wen', 'gao wen')</td><td>E-mail: jos@iscas.ac.cn <br/>+ Corresponding author: Phn: +86-10-58858300 ext 314, Fax: +86-10-58858301, E-mail: xjchai@jdl.ac.cn, http://www.jdl.ac.cn/ -</td></tr><tr><td>bd572e9cbec095bcf5700cb7cd73d1cdc2fe02f4</td><td>Hindawi +</td></tr><tr><td>bd0265ba7f391dc3df9059da3f487f7ef17144df</td><td>Data-Driven Sparse Sensor Placement +<br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>University of Washington, Seattle, WA 98195, United States</b></td><td>('37119658', 'Krithika Manohar', 'krithika manohar')<br/>('1824880', 'Bingni W. Brunton', 'bingni w. brunton')<br/>('1937069', 'J. Nathan Kutz', 'j. nathan kutz')<br/>('3083169', 'Steven L. Brunton', 'steven l. brunton')</td><td></td></tr><tr><td>bd572e9cbec095bcf5700cb7cd73d1cdc2fe02f4</td><td>Hindawi <br/>Computational Intelligence and Neuroscience <br/>Volume 2018, Article ID 7068349, 13 pages <br/>https://doi.org/10.1155/2018/7068349 @@ -10155,6 +12127,10 @@ <br/>GUANG.GDAI@GMAIL.COM <br/>XUCONGFU@ZJU.EDU.CN <br/>JORDAN@CS.BERKELEY.EDU +</td></tr><tr><td>bd0e100a91ff179ee5c1d3383c75c85eddc81723</td><td>Okutama-Action: An Aerial View Video Dataset for Concurrent Human Action +<br/>Detection∗ +<br/><b>Technical University of Munich, Munich, 2KTH Royal Institute of Technology, Stockholm</b><br/><b>Polytechnic University of Catalonia, Barcelona, 4National Taiwan University, Taipei, 5University of</b><br/><b>Tokyo, Tokyo, 6National Institute of Informatics, Tokyo</b></td><td>('39393520', 'Mohammadamin Barekatain', 'mohammadamin barekatain')<br/>('19185012', 'Hsueh-Fu Shih', 'hsueh-fu shih')<br/>('47427148', 'Samuel Murray', 'samuel murray')<br/>('1943224', 'Kotaro Nakayama', 'kotaro nakayama')<br/>('47972365', 'Yutaka Matsuo', 'yutaka matsuo')<br/>('2356111', 'Helmut Prendinger', 'helmut prendinger')</td><td>m.barekatain@tum.de, miquelmr@kth.se, r03945026@ntu.edu.tw, samuelmu@kth.se, +<br/>nakayama@weblab.t.u-tokyo.ac.jp, matsuo@weblab.t.u-tokyo.ac.jp, helmut@nii.ac.jp </td></tr><tr><td>bd8f3fef958ebed5576792078f84c43999b1b207</td><td>BUAA-iCC at ImageCLEF 2015 Scalable <br/>Concept Image Annotation Challenge <br/><b>Intelligent Recognition and Image Processing Lab, Beihang University, Beijing</b><br/>100191, P.R.China @@ -10179,19 +12155,39 @@ <br/>---------------------------------------------------------------------***--------------------------------------------------------------------- </td><td>('3124644', 'Florica Moldoveanu', 'florica moldoveanu')</td><td></td></tr><tr><td>bd8e2d27987be9e13af2aef378754f89ab20ce10</td><td></td><td></td><td></td></tr><tr><td>bd236913cfe07896e171ece9bda62c18b8c8197e</td><td>Deep Learning with Energy-efficient Binary Gradient Cameras <br/>∗NVIDIA, -<br/><b>Carnegie Mellon University</b></td><td>('39131476', 'Suren Jayasuriya', 'suren jayasuriya')<br/>('39775678', 'Orazio Gallo', 'orazio gallo')<br/>('2931118', 'Jinwei Gu', 'jinwei gu')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td></td></tr><tr><td>bd13f50b8997d0733169ceba39b6eb1bda3eb1aa</td><td>Occlusion Coherence: Detecting and Localizing Occluded Faces -<br/><b>University of California at Irvine, Irvine, CA</b></td><td>('1898210', 'Golnaz Ghiasi', 'golnaz ghiasi')<br/>('3157443', 'Charless C. Fowlkes', 'charless c. fowlkes')</td><td></td></tr><tr><td>bd8b7599acf53e3053aa27cfd522764e28474e57</td><td>Learning Long Term Face Aging Patterns +<br/><b>Carnegie Mellon University</b></td><td>('39131476', 'Suren Jayasuriya', 'suren jayasuriya')<br/>('39775678', 'Orazio Gallo', 'orazio gallo')<br/>('2931118', 'Jinwei Gu', 'jinwei gu')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td></td></tr><tr><td>bd379f8e08f88729a9214260e05967f4ca66cd65</td><td>Learning Compositional Visual Concepts with Mutual Consistency +<br/><b>School of Electrical and Computer Engineering, Cornell University, Ithaca NY</b><br/><b>Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca NY</b><br/>3Siemens Corporate Technology, Princeton NJ +<br/>Figure 1: We propose ConceptGAN, a framework that can jointly learn, transfer and compose concepts to generate semantically meaningful +<br/>images, even in subdomains with no training data (highlighted) while the state-of-the-art methods such as CycleGAN [49] fail to do so. +</td><td>('3303727', 'Yunye Gong', 'yunye gong')<br/>('1976152', 'Srikrishna Karanam', 'srikrishna karanam')<br/>('3311781', 'Ziyan Wu', 'ziyan wu')<br/>('2692770', 'Kuan-Chuan Peng', 'kuan-chuan peng')<br/>('39497207', 'Jan Ernst', 'jan ernst')<br/>('1767099', 'Peter C. Doerschuk', 'peter c. doerschuk')</td><td>{yg326,pd83}@cornell.edu,{first.last}@siemens.com +</td></tr><tr><td>bd13f50b8997d0733169ceba39b6eb1bda3eb1aa</td><td>Occlusion Coherence: Detecting and Localizing Occluded Faces +<br/><b>University of California at Irvine, Irvine, CA</b></td><td>('1898210', 'Golnaz Ghiasi', 'golnaz ghiasi')<br/>('3157443', 'Charless C. Fowlkes', 'charless c. fowlkes')</td><td></td></tr><tr><td>bd21109e40c26af83c353a3271d0cd0b5c4b4ade</td><td>Attentive Sequence to Sequence Translation for Localizing Clips of Interest +<br/>by Natural Language Descriptions +<br/><b>Zhejiang University</b><br/><b>University of Technology Sydney</b><br/><b>Zhejiang University</b><br/><b>University of Technology Sydney</b><br/><b>Hikvision Research Institute</b></td><td>('1819984', 'Ke Ning', 'ke ning')<br/>('2948393', 'Linchao Zhu', 'linchao zhu')<br/>('50140409', 'Ming Cai', 'ming cai')<br/>('1698559', 'Yi Yang', 'yi yang')<br/>('2603725', 'Di Xie', 'di xie')</td><td>ningke@zju.edu.cn +<br/>zhulinchao7@gmail.com +<br/>Yi.Yang@uts.edu.au +<br/>xiedi@hikvision.com +</td></tr><tr><td>bd8b7599acf53e3053aa27cfd522764e28474e57</td><td>Learning Long Term Face Aging Patterns <br/>from Partially Dense Aging Databases <br/>Jinli Suo1,2,3 <br/><b>Graduate University of Chinese Academy of Sciences(CAS), 100190, China</b><br/>2Key Lab of Intelligent Information Processing of CAS, <br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>Lotus Hill Institute for Computer Vision and Information Science, 436000, China</b><br/><b>School of Electronic Engineering and Computer Science, Peking University, 100871, China</b></td><td>('1698902', 'Wen Gao', 'wen gao')<br/>('1710220', 'Xilin Chen', 'xilin chen')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')</td><td>wgao@pku.edu.cn <br/>jlsuo@jdl.ac.cn <br/>{xlchen,sgshan}@ict.ac.cn +</td></tr><tr><td>bd8f77b7d3b9d272f7a68defc1412f73e5ac3135</td><td>SphereFace: Deep Hypersphere Embedding for Face Recognition +<br/><b>Georgia Institute of Technology</b><br/><b>Carnegie Mellon University</b><br/><b>Sun Yat-Sen University</b></td><td>('36326884', 'Weiyang Liu', 'weiyang liu')<br/>('1751019', 'Zhiding Yu', 'zhiding yu')<br/>('1779453', 'Le Song', 'le song')</td><td>wyliu@gatech.edu, {yandongw,yzhiding}@andrew.cmu.edu, lsong@cc.gatech.edu +</td></tr><tr><td>bd26dabab576adb6af30484183c9c9c8379bf2e0</td><td>SCUT-FBP: A Benchmark Dataset for +<br/>Facial Beauty Perception +<br/>School of Electronic and Information Engineering +<br/><b>South China University of Technology, Guangzhou 510640, China</b></td><td>('2361818', 'Duorui Xie', 'duorui xie')<br/>('2521432', 'Lingyu Liang', 'lingyu liang')<br/>('1703322', 'Lianwen Jin', 'lianwen jin')<br/>('1720015', 'Jie Xu', 'jie xu')<br/>('4997446', 'Mengru Li', 'mengru li')</td><td>*Email: lianwen.jin@gmail.com </td></tr><tr><td>bd78a853df61d03b7133aea58e45cd27d464c3cf</td><td>A Sparse Representation Approach to Facial <br/>Expression Recognition Based on LBP plus LFDA <br/>Computer science and Engineering Department, <br/><b>Government College of Engineering, Aurangabad [Autonomous</b><br/>Station Road, Aurangabad, Maharashtra, India. -</td><td></td><td></td></tr><tr><td>bd2d7c7f0145028e85c102fe52655c2b6c26aeb5</td><td>Attribute-based People Search: Lessons Learnt from a +</td><td></td><td></td></tr><tr><td>bd9c9729475ba7e3b255e24e7478a5acb393c8e9</td><td>Interpretable Partitioned Embedding for Customized Fashion Outfit +<br/>Composition +<br/><b>Zhejiang University, Hangzhou, China</b><br/><b>Arizona State University, Phoenix, Arizona</b><br/>♭Alibaba Group, Hangzhou, China +</td><td>('7357719', 'Zunlei Feng', 'zunlei feng')<br/>('46218293', 'Zhenyun Yu', 'zhenyun yu')<br/>('7607499', 'Yezhou Yang', 'yezhou yang')<br/>('9633703', 'Yongcheng Jing', 'yongcheng jing')<br/>('46179768', 'Junxiao Jiang', 'junxiao jiang')<br/>('1727111', 'Mingli Song', 'mingli song')</td><td></td></tr><tr><td>bd2d7c7f0145028e85c102fe52655c2b6c26aeb5</td><td>Attribute-based People Search: Lessons Learnt from a <br/>Practical Surveillance System <br/>Rogerio Feris <br/>IBM Watson @@ -10206,6 +12202,56 @@ <br/>sharat@us.ibm.com </td></tr><tr><td>bd9157331104a0708aa4f8ae79b7651a5be797c6</td><td>SLAC: A Sparsely Labeled Dataset for Action Classification and Localization <br/><b>Massachusetts Institute of Technology, 2Facebook Applied Machine Learning, 3Dartmouth College</b></td><td>('1683002', 'Hang Zhao', 'hang zhao')<br/>('3305169', 'Zhicheng Yan', 'zhicheng yan')<br/>('1804138', 'Heng Wang', 'heng wang')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')<br/>('1690178', 'Antonio Torralba', 'antonio torralba')</td><td>{hangzhao, torralba}@mit.edu, {zyan3, hengwang, torresani}@fb.com +</td></tr><tr><td>bdbba95e5abc543981fb557f21e3e6551a563b45</td><td>International Journal of Computational Intelligence and Applications +<br/>Vol. 17, No. 2 (2018) 1850008 (15 pages) +<br/>#.c The Author(s) +<br/>DOI: 10.1142/S1469026818500086 +<br/>Speeding up the Hyperparameter Optimization of Deep +<br/>Convolutional Neural Networks +<br/>Knowledge Technology, Department of Informatics +<br/>Universit€at Hamburg +<br/>Vogt-K€olln-Str. 30, Hamburg 22527, Germany +<br/>Received 15 August 2017 +<br/>Accepted 23 March 2018 +<br/>Published 18 June 2018 +<br/>Most learning algorithms require the practitioner to manually set the values of many hyper- +<br/>parameters before the learning process can begin. However, with modern algorithms, the +<br/>evaluation of a given hyperparameter setting can take a considerable amount of time and the +<br/>search space is often very high-dimensional. We suggest using a lower-dimensional represen- +<br/>tation of the original data to quickly identify promising areas in the hyperparameter space. This +<br/>information can then be used to initialize the optimization algorithm for the original, higher- +<br/>dimensional data. We compare this approach with the standard procedure of optimizing the +<br/>hyperparameters only on the original input. +<br/>We perform experiments with various state-of-the-art hyperparameter optimization algo- +<br/>rithms such as random search, the tree of parzen estimators (TPEs), sequential model-based +<br/>algorithm con¯guration (SMAC), and a genetic algorithm (GA). Our experiments indicate that +<br/>it is possible to speed up the optimization process by using lower-dimensional data repre- +<br/>sentations at the beginning, while increasing the dimensionality of the input later in the opti- +<br/>mization process. This is independent of the underlying optimization procedure, making the +<br/>approach promising for many existing hyperparameter optimization algorithms. +<br/>Keywords: Hyperparameter optimization; hyperparameter importance; convolutional neural +<br/>networks; genetic algorithm; Bayesian optimization. +<br/>1. Introduction +<br/>The performance of many contemporary machine learning algorithms depends cru- +<br/>cially on the speci¯c initialization of hyperparameters such as the general architec- +<br/>ture, the learning rate, regularization parameters, and many others.1,2 Indeed, +<br/>This is an Open Access article published by World Scienti¯c Publishing Company. It is distributed under +<br/>the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is +<br/>permitted, provided the original work is properly cited. +<br/>1850008-1 +<br/>Int. J. Comp. Intel. Appl. 2018.17. Downloaded from www.worldscientific.comby WSPC on 07/18/18. Re-use and distribution is strictly not permitted, except for Open Access articles. </td><td>('11634287', 'Tobias Hinz', 'tobias hinz')<br/>('2632932', 'Sven Magg', 'sven magg')<br/>('1736513', 'Stefan Wermter', 'stefan wermter')</td><td>*hinz@informatik.uni-hamburg.de +<br/>†navarro@informatik.uni-hamburg.de +<br/>‡magg@informatik.uni-hamburg.de +<br/>wermter@informatik.uni-hamburg.de +</td></tr><tr><td>bd70f832e133fb87bae82dfaa0ae9d1599e52e4b</td><td>Combining Classifier for Face Identification +<br/><b>HCI Lab., Samsung Advanced Institute of Technology, Yongin, Korea</b><br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, UK</b></td><td>('1700968', 'Tae-Kyun Kim', 'tae-kyun kim')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>taekyun@sait.samsung.co.kr +<br/>J.Kittler@surrey.ac.uk +</td></tr><tr><td>d1dfdc107fa5f2c4820570e369cda10ab1661b87</td><td>Super SloMo: High Quality Estimation of Multiple Intermediate Frames +<br/>for Video Interpolation +<br/>Erik Learned-Miller1 +<br/>1UMass Amherst +<br/>2NVIDIA 3UC Merced +</td><td>('40175280', 'Huaizu Jiang', 'huaizu jiang')<br/>('3232265', 'Deqing Sun', 'deqing sun')<br/>('2745026', 'Varun Jampani', 'varun jampani')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td>{hzjiang,elm}@cs.umass.edu,{deqings,vjampani,jkautz}@nvidia.com, mhyang@ucmerced.edu </td></tr><tr><td>d185f4f05c587e23c0119f2cdfac8ea335197ac0</td><td> 33 <br/>Chapter III <br/>Facial Expression Analysis, @@ -10235,7 +12281,9 @@ <br/><b>Swansea University</b><br/>Singleton Park, Swansea SA2 8PP, United Kingdom <br/>http://csvision.swan.ac.uk </td><td>('6248353', 'Jingjing Deng', 'jingjing deng')<br/>('2168049', 'Xianghua Xie', 'xianghua xie')<br/>('13154093', 'Michael Edwards', 'michael edwards')</td><td>*x.xie@swansea.ac.uk -</td></tr><tr><td>d122d66c51606a8157a461b9d7eb8b6af3d819b0</td><td>Vol-3 Issue-4 2017 +</td></tr><tr><td>d1a43737ca8be02d65684cf64ab2331f66947207</td><td>IJB–S: IARPA Janus Surveillance Video Benchmark (cid:3) +<br/>Kevin O’Connor z +</td><td>('1718102', 'Nathan D. Kalka', 'nathan d. kalka')<br/>('48889427', 'Stephen Elliott', 'stephen elliott')<br/>('8033275', 'Brianna Maze', 'brianna maze')<br/>('40205896', 'James A. Duncan', 'james a. duncan')<br/>('40577714', 'Julia Bryan', 'julia bryan')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>d122d66c51606a8157a461b9d7eb8b6af3d819b0</td><td>Vol-3 Issue-4 2017 <br/>IJARIIE-ISSN(O)-2395-4396 <br/>AUTOMATED RECOGNITION OF FACIAL <br/>EXPRESSIONS @@ -10267,7 +12315,10 @@ </td></tr><tr><td>d1881993c446ea693bbf7f7d6e750798bf958900</td><td>Large-Scale YouTube-8M Video Understanding with Deep Neural Networks <br/><b>Institute for System Programming</b><br/><b>Institute for System Programming</b><br/>ispras.ru </td><td>('34125461', 'Manuk Akopyan', 'manuk akopyan')<br/>('19228325', 'Eshsou Khashba', 'eshsou khashba')</td><td>manuk@ispras.ru -</td></tr><tr><td>d61578468d267c2d50672077918c1cda9b91429b</td><td>Available Online at www.ijcsmc.com +</td></tr><tr><td>d1d6f1d64a04af9c2e1bdd74e72bd3ffac329576</td><td>Neural Face Editing with Intrinsic Image Disentangling +<br/><b>Stony Brook University 2Adobe Research 3 CentraleSup elec, Universit e Paris-Saclay</b></td><td>('2496409', 'Zhixin Shu', 'zhixin shu')</td><td>1{zhshu,samaras}@cs.stonybrook.edu +<br/>2{yumer,hadap,sunkaval,elishe}@adobe.com +</td></tr><tr><td>d69df51cff3d6b9b0625acdcbea27cd2bbf4b9c0</td><td></td><td></td><td></td></tr><tr><td>d61578468d267c2d50672077918c1cda9b91429b</td><td>Available Online at www.ijcsmc.com <br/>International Journal of Computer Science and Mobile Computing <br/> A Monthly Journal of Computer Science and Information Technology <br/>ISSN 2320–088X @@ -10285,9 +12336,14 @@ <br/>tributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any me- <br/>dium, provided the original work is properly cited. </td><td></td><td>Email: *kathirvalavakumar@yahoo.com, jebaarul07@yahoo.com -</td></tr><tr><td>d647099e571f9af3a1762f895fd8c99760a3916e</td><td>Exploring Facial Expressions with Compositional Features +</td></tr><tr><td>d69719b42ee53b666e56ed476629a883c59ddf66</td><td>Learning Facial Action Units from Web Images with +<br/>Scalable Weakly Supervised Clustering +<br/>Aleix M. Martinez3 +<br/><b>School of Comm. and Info. Engineering, Beijing University of Posts and Telecom</b><br/><b>Robotics Institute, Carnegie Mellon University</b><br/><b>The Ohio State University</b></td><td>('2393320', 'Kaili Zhao', 'kaili zhao')</td><td></td></tr><tr><td>d647099e571f9af3a1762f895fd8c99760a3916e</td><td>Exploring Facial Expressions with Compositional Features <br/><b>Rutgers University</b><br/>110 Frelinghuysen Road, Piscataway, NJ 08854, USA </td><td>('39606160', 'Peng Yang', 'peng yang')<br/>('1734954', 'Qingshan Liu', 'qingshan liu')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>peyang@cs.rutgers.edu, qsliu@cs.rutgers.edu, dnm@cs.rutgers.edu +</td></tr><tr><td>d69271c7b77bc3a06882884c21aa1b609b3f76cc</td><td>FaceBoxes: A CPU Real-time Face Detector with High Accuracy +<br/><b>CBSR and NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('3220556', 'Shifeng Zhang', 'shifeng zhang')</td><td>{shifeng.zhang,xiangyu.zhu,zlei,hailin.shi,xiaobo.wang,szli}@nlpr.ia.ac.cn </td></tr><tr><td>d6a9ea9b40a7377c91c705f4c7f206a669a9eea2</td><td>Visual Representations for Fine-grained <br/>Categorization <br/>Electrical Engineering and Computer Sciences @@ -10419,15 +12475,150 @@ <br/>naturalistic driving data largely due to concerns over indi- <br/>vidual privacy. Camera sensors looking at a driver, which </td><td>('1841835', 'Sujitha Martin', 'sujitha martin')<br/>('1713989', 'Mohan M. Trivedi', 'mohan m. trivedi')</td><td>scmartin@ucsd.edu, mtrivedi@ucsd.edu -</td></tr><tr><td>d6fb606e538763282e3942a5fb45c696ba38aee6</td><td></td><td></td><td></td></tr><tr><td>bcee40c25e8819955263b89a433c735f82755a03</td><td>Biologically inspired vision for human-robot +</td></tr><tr><td>d666ce9d783a2d31550a8aa47da45128a67304a7</td><td>On Relating Visual Elements to City Statistics +<br/><b>University of California, Berkeley</b><br/>Maneesh Agrawala† +<br/><b>University of California, Berkeley</b><br/><b>University of California, Berkeley</b><br/>(c) Visual Elements for Thefts in San Francisco +<br/>(a) Predicted High Theft Location in Oakland +<br/>(b) Predicted Low Theft Location in Oakland +<br/>(d) Predicted Theft Rate in Oakland +<br/>Figure 1: Our system automatically computes a predictor from a set of Google StreetView images of areas where a statistic was observed. In this example +<br/>we use a predictor generated from reports of theft in San Francisco to predict the probability of thefts occurring in Oakland. Our system can predict high +<br/>theft rate areas (a) and low theft rates area (b) based solely on street-level images from the areas. Visually, the high theft area exhibits a marked quality of +<br/>disrepair (bars on the windows, unkempt facades, etc), a visual cue that the probability of theft is likely higher. Our method automatically computes machine +<br/>learning models that detect visual elements similar to these cues (c) from San Francisco. To compute predictions, we use the models to detect the presence of +<br/>these visual elements in an image and combine all of the detections according to an automatically learned set of weights. Our resulting predictions are 63% +<br/>accurate in this case and can be computed everywhere in Oakland (d) as they only rely on images as input. +</td><td>('2288243', 'Sean M. Arietta', 'sean m. arietta')<br/>('1752236', 'Ravi Ramamoorthi', 'ravi ramamoorthi')</td><td></td></tr><tr><td>d6fb606e538763282e3942a5fb45c696ba38aee6</td><td></td><td></td><td></td></tr><tr><td>bcee40c25e8819955263b89a433c735f82755a03</td><td>Biologically inspired vision for human-robot <br/>interaction <br/>M. Saleiro, M. Farrajota, K. Terzi´c, S. Krishna, J.M.F. Rodrigues, and J.M.H. <br/>du Buf <br/><b>Vision Laboratory, LARSyS, University of the Algarve, 8005-139 Faro, Portugal</b></td><td></td><td>{masaleiro, mafarrajota, kterzic, jrodrig, dubuf}@ualg.pt, <br/>saikrishnap2003@gmail.com, -</td></tr><tr><td>bc15a2fd09df7046e7e8c7c5b054d7f06c3cefe9</td><td>Using Deep Autoencoders for Facial Expression +</td></tr><tr><td>bc6de183cd8b2baeebafeefcf40be88468b04b74</td><td>Age Group Recognition using Human Facial Images +<br/>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 126 – No.13, September 2015 +<br/>Dept. of Electronics and Telecommunication +<br/><b>Government College of Engineering</b><br/>Aurangabad, Maharashtra, India +</td><td>('31765215', 'Shailesh S. Kulkarni', 'shailesh s. kulkarni')</td><td></td></tr><tr><td>bcf19b964e7d1134d00332cf1acf1ee6184aff00</td><td>1922 +<br/>IEICE TRANS. INF. & SYST., VOL.E100–D, NO.8 AUGUST 2017 +<br/>LETTER +<br/>Trajectory-Set Feature for Action Recognition +<br/>SUMMARY We propose a feature for action recognition called +<br/>Trajectory-Set (TS), on top of the improved Dense Trajectory (iDT). +<br/>The TS feature encodes only trajectories around densely sampled inter- +<br/>est points, without any appearance features. Experimental results on the +<br/>UCF50 action dataset demonstrates that TS is comparable to state-of-the- +<br/>arts, and outperforms iDT; the accuracy of 95.0%, compared to 91.7% by +<br/>iDT. +<br/>key words: action recognition, trajectory, improved Dense Trajectory +<br/>the two-stream CNN [2] that uses a single frame and a opti- +<br/>cal flow stack. In their paper stacking trajectories was also +<br/>reported but did not perform well, probably the sparseness +<br/>of trajectories does not fit to CNN architectures. In contrast, +<br/>we take a hand-crafted approach that can be fused later with +<br/>CNN outputs. +<br/>1. +<br/>Introduction +<br/>Action recognition has been well studied in the computer +<br/>vision literature [1] because it is an important and challeng- +<br/>ing task. Deep learning approaches have been proposed +<br/>recently [2]–[4], however still a hand-crafted feature, im- +<br/>proved Dense Trajectory (iDT) [5], [6], is comparable in +<br/>performance. Moreover, top performances of deep learn- +<br/>ing approaches are obtained by combining the iDT fea- +<br/>ture [3], [7], [8]. +<br/>In this paper, we propose a novel hand-crafted feature +<br/>for action recognition, called Trajectory-Set (TS), that en- +<br/>codes trajectories in a local region of a video. The con- +<br/>tribution of this paper is summarized as follows. We pro- +<br/>pose another hand-crafted feature that can be combined with +<br/>deep learning approaches. Hand-crafted features are com- +<br/>plement to deep learning approaches, however a little effort +<br/>has been done in this direction after iDT. Second, the pro- +<br/>posed TS feature focuses on the better handling of motions +<br/>in the scene. The iDT feature uses trajectories of densely +<br/>samples interest points in a simple way, while we explore +<br/>here the way to extract a rich information from trajectories. +<br/>The proposed TS feature is complement to appearance in- +<br/>formation such as HOG and objects in the scene, which can +<br/>be computed separately and combined afterward in a late +<br/>fusion fashion. +<br/>There are two relate works relevant to our work. One +<br/>is trajectons [9] that uses a global dictionary of trajectories +<br/>in a video to cluster representative trajectories as snippets. +<br/>Our TS feature is computed locally, not globally, inspired +<br/>by the success of local image descriptors [10]. The other is +<br/>Manuscript received March 2, 2017. +<br/>Manuscript revised April 27, 2017. +<br/>Manuscript publicized May 10, 2017. +<br/><b>The authors are with Hiroshima University, Higashihiroshima</b><br/>shi, 739–8527 Japan. +<br/>DOI: 10.1587/transinf.2017EDL8049 +<br/>2. Dense Trajectory +<br/>Here we briefly summarize the improved dense trajectory +<br/>(iDT) [6] on which we base for the proposed method. First, +<br/>the image pyramid for a particular frame at time t in a video +<br/>is constructed, and interest points are densely sampled at +<br/>each level of the pyramid. Next, interest points are tracked +<br/>in the following L frames (L = 15 by default). Then, the +<br/>iDT is computed by using local features such as HOG (His- +<br/>togram of Oriented Gradient) [10], HOF (Histogram of Op- +<br/>tical Flow), and MBH (Motion Boundary Histograms) [11] +<br/>along the trajectory tube; a stack of patches centered at the +<br/>trajectory in the frames. +<br/>, pt1 +<br/>In fact, Tt0,tL +<br/>For example, between two points in time t0 and tL, a +<br/>, . . . , ptL in frames {t0, t1, +<br/>trajectory Tt0,tL has points pt0 +<br/>. . . , tL}. +<br/>is a vector of displacement be- +<br/>tween frames rather than point coordinates, that is, Tt0,tL +<br/>(v0, v1, . . . , vL−1) where vi = pi−1 − pi. Local features such as +<br/>HOGti are computed with a patch centered at pti in frame at +<br/>time ti. +<br/>To improve the performance, the global motion is re- +<br/>moved by computing homography, and background trajec- +<br/>tories are removed by using a people detector. The Fisher +<br/>vector encoding [12] is used to compute an iDT feature of a +<br/>video. +<br/>3. Proposed Trajectory-Set Feature +<br/>We think that extracted trajectories might have rich informa- +<br/>tion discriminative enough for classifying different actions, +<br/>even although trajectories have no appearance information. +<br/>As shown in Fig. 1, different actions are expected to have +<br/>different trajectories, regardless of appearance, texture, or +<br/>shape of the video frame contents. However a single trajec- +<br/>tory Tt0,tL may be severely affected by inaccurate tracking +<br/>results and an irregular motion in the frame. +<br/>We instead propose to aggregate nearby trajectories to +<br/>form a Trajectory-Set (TS) feature. First, a frame is divided +<br/>into non-overlapping cells of M × M pixels as shown in +<br/><b>Copyright c(cid:2) 2017 The Institute of Electronics, Information and Communication Engineers</b></td><td>('47916686', 'Kenji Matsui', 'kenji matsui')<br/>('1744862', 'Toru Tamaki', 'toru tamaki')<br/>('1688940', 'Bisser Raytchev', 'bisser raytchev')<br/>('1686272', 'Kazufumi Kaneda', 'kazufumi kaneda')</td><td>a) E-mail: tamaki@hiroshima-u.ac.jp +</td></tr><tr><td>bc9003ad368cb79d8a8ac2ad025718da5ea36bc4</td><td>Technische Universit¨at M¨unchen +<br/>Bildverstehen und Intelligente Autonome Systeme +<br/>Facial Expression Recognition With A +<br/>Three-Dimensional Face Model +<br/>Vollst¨andiger Abdruck der von der Fakult¨at f¨ur Informatik der Technischen Uni- +<br/>versit¨at M¨unchen zur Erlangung des akademischen Grades eines +<br/>Doktors der Naturwissenschaften +<br/>genehmigten Dissertation. +<br/>Vorsitzender: +<br/>Univ.-Prof. Dr. Johann Schlichter +<br/>Pr¨ufer der Dissertation: 1. Univ.-Prof. Dr. Bernd Radig (i.R.) +<br/>2. Univ.-Prof. Gudrun J. Klinker, Ph.D. +<br/>Die Dissertation wurde am 04.07.2011 bei der Technischen Universit¨at M¨unchen +<br/>eingereicht und durch die Fakult¨at f¨ur Informatik am 02.12.2011 angenommen. +</td><td>('50565622', 'Christoph Mayer', 'christoph mayer')</td><td></td></tr><tr><td>bc15a2fd09df7046e7e8c7c5b054d7f06c3cefe9</td><td>Using Deep Autoencoders for Facial Expression <br/>Recognition <br/><b>COMSATS Institute of Information Technology, Islamabad</b><br/><b>Information Technology University (ITU), Punjab, Lahore, Pakistan</b><br/><b>National University of Sciences and Technology (NUST), Islamabad, Pakistan</b></td><td>('24040678', 'Siddique Latif', 'siddique latif')<br/>('1734917', 'Junaid Qadir', 'junaid qadir')</td><td>engr.ussman@gmail.com, slatif.msee15seecs@seecs.edu.pk, junaid.qadir@itu.edu.pk +</td></tr><tr><td>bcc346f4a287d96d124e1163e4447bfc47073cd8</td><td></td><td></td><td></td></tr><tr><td>bc27434e376db89fe0e6ef2d2fabc100d2575ec6</td><td>Faceless Person Recognition; +<br/>Privacy Implications in Social Media +<br/><b>Max-Planck Institute for Informatics</b><br/>Person A training samples. +<br/>Is this person A ? +<br/>Fig. 1: An illustration of one of the scenarios considered: can a vision system +<br/>recognise that the person in the right image is the same as the tagged person in +<br/>the left images, even when the head is obfuscated? +</td><td>('2390510', 'Seong Joon Oh', 'seong joon oh')<br/>('1798000', 'Rodrigo Benenson', 'rodrigo benenson')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td>{joon, benenson, mfritz, schiele}@mpi-inf.mpg.de </td></tr><tr><td>bcc172a1051be261afacdd5313619881cbe0f676</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE <br/>2197 <br/>ICASSP 2017 @@ -10456,7 +12647,21 @@ </td><td>('3817476', 'Shouyi Yin', 'shouyi yin')<br/>('34585208', 'Xu Dai', 'xu dai')<br/>('12263637', 'Peng Ouyang', 'peng ouyang')<br/>('1743798', 'Leibo Liu', 'leibo liu')<br/>('1803672', 'Shaojun Wei', 'shaojun wei')</td><td>E-Mails: daixu@gmail.com (X.D.); oyangpeng12@163.com (P.O.); liulb@tsinghua.edu.cn (L.L.); <br/>wsj@tsinghua.edu.cn (S.W.) <br/>* Author to whom correspondence should be addressed; E-Mail: yinsy@tsinghua.edu.cn; -</td></tr><tr><td>bcb99d5150d792001a7d33031a3bd1b77bea706b</td><td></td><td></td><td></td></tr><tr><td>bc98027b331c090448492eb9e0b9721e812fac84</td><td>Journal of Intelligent Learning Systems and Applications, 2012, 4, 266-273 +</td></tr><tr><td>bc8e11b8cdf0cfbedde798a53a0318e8d6f67e17</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Deep Learning for Fixed Model Reuse∗ +<br/><b>National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, 210023, China</b><br/>Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing, 210023, China +</td><td>('1708973', 'Yang Yang', 'yang yang')<br/>('1721819', 'De-Chuan Zhan', 'de-chuan zhan')<br/>('3750883', 'Ying Fan', 'ying fan')<br/>('2192443', 'Yuan Jiang', 'yuan jiang')<br/>('1692625', 'Zhi-Hua Zhou', 'zhi-hua zhou')</td><td>{yangy, zhandc, fany, jiangy, zhouzh}@lamda.nju.edu.cn +</td></tr><tr><td>bcb99d5150d792001a7d33031a3bd1b77bea706b</td><td></td><td></td><td></td></tr><tr><td>bc811a66855aae130ca78cd0016fd820db1603ec</td><td>Towards three-dimensional face recognition in the real +<br/>To cite this version: +<br/>HAL Id: tel-00998798 +<br/>https://tel.archives-ouvertes.fr/tel-00998798 +<br/>Submitted on 2 Jun 2014 +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>teaching and research institutions in France or +<br/>destin´ee au d´epˆot et `a la diffusion de documents +<br/>recherche fran¸cais ou ´etrangers, des laboratoires +</td><td>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')<br/>('47144044', 'Li', 'li')</td><td></td></tr><tr><td>bc98027b331c090448492eb9e0b9721e812fac84</td><td>Journal of Intelligent Learning Systems and Applications, 2012, 4, 266-273 <br/>http://dx.doi.org/10.4236/jilsa.2012.44027 Published Online November 2012 (http://www.SciRP.org/journal/jilsa) <br/>Face Representation Using Combined Method of Gabor <br/>Filters, Wavelet Transformation and DCV and Recognition @@ -10464,6 +12669,11 @@ <br/><b>VHNSN College, Virudhunagar, ANJA College</b><br/>Sivakasi, India. <br/>Received April 27th, 2012; revised July 19th, 2012; accepted July 26th, 2012 </td><td>('39000426', 'Kathirvalavakumar Thangairulappan', 'kathirvalavakumar thangairulappan')<br/>('15392239', 'Jebakumari Beulah Vasanthi Jeyasingh', 'jebakumari beulah vasanthi jeyasingh')</td><td>Email: *kathirvalavakumar@yahoo.com, jebaarul07@yahoo.com +</td></tr><tr><td>bc9af4c2c22a82d2c84ef7c7fcc69073c19b30ab</td><td>MoCoGAN: Decomposing Motion and Content for Video Generation +<br/>Snap Research +<br/>NVIDIA +</td><td>('1715440', 'Sergey Tulyakov', 'sergey tulyakov')<br/>('9536217', 'Ming-Yu Liu', 'ming-yu liu')<br/>('50030951', 'Xiaodong Yang', 'xiaodong yang')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td>stulyakov@snap.com +<br/>{mingyul,xiaodongy,jkautz}@nvidia.com </td></tr><tr><td>bcac3a870501c5510df80c2a5631f371f2f6f74a</td><td>CVPR <br/>#1387 <br/>000 @@ -10526,15 +12736,38 @@ <br/>Structured Face Hallucination <br/>Anonymous CVPR submission <br/>Paper ID 1387 -</td><td></td><td></td></tr><tr><td>aed321909bb87c81121c841b21d31509d6c78f69</td><td></td><td></td><td></td></tr><tr><td>ae936628e78db4edb8e66853f59433b8cc83594f</td><td></td><td></td><td></td></tr><tr><td>ae0765ebdffffd6e6cc33c7705df33b7e8478627</td><td>Self-Reinforced Cascaded Regression for Face Alignment +</td><td></td><td></td></tr><tr><td>ae8d5be3caea59a21221f02ef04d49a86cb80191</td><td>Published as a conference paper at ICLR 2018 +<br/>SKIP RNN: LEARNING TO SKIP STATE UPDATES IN +<br/>RECURRENT NEURAL NETWORKS +<br/>†Barcelona Supercomputing Center, ‡Google Inc, +<br/><b>Universitat Polit`ecnica de Catalunya, Columbia University</b></td><td>('2447185', 'Brendan Jou', 'brendan jou')<br/>('1711068', 'Jordi Torres', 'jordi torres')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>{victor.campos, jordi.torres}@bsc.es, bjou@google.com, +<br/>xavier.giro@upc.edu, shih.fu.chang@columbia.edu +</td></tr><tr><td>aed321909bb87c81121c841b21d31509d6c78f69</td><td></td><td></td><td></td></tr><tr><td>ae936628e78db4edb8e66853f59433b8cc83594f</td><td></td><td></td><td></td></tr><tr><td>ae0765ebdffffd6e6cc33c7705df33b7e8478627</td><td>Self-Reinforced Cascaded Regression for Face Alignment <br/><b>DUT-RU International School of Information Science and Engineering, Dalian University of Technology, Dalian, China</b><br/>2Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, China <br/><b>School of Mathematical Science, Dalian University of Technology, Dalian, China</b></td><td>('1710408', 'Xin Fan', 'xin fan')<br/>('34469457', 'Risheng Liu', 'risheng liu')<br/>('3453975', 'Kang Huyan', 'kang huyan')<br/>('3013708', 'Yuyao Feng', 'yuyao feng')<br/>('7864960', 'Zhongxuan Luo', 'zhongxuan luo')</td><td>{xin.fan, rsliu, zxluo}@dlut.edu.cn, huyankang@hotmail.com yyaofeng@gmail.com </td></tr><tr><td>aefc7c708269b874182a5c877fb6dae06da210d4</td><td>Deep Learning of Invariant Features via Simulated <br/>Fixations in Video <br/><b>Stanford University, CA</b><br/><b>Stanford University, CA</b><br/><b>NEC Laboratories America, Inc., Cupertino, CA</b></td><td>('2860351', 'Will Y. Zou', 'will y. zou')<br/>('1682028', 'Shenghuo Zhu', 'shenghuo zhu')<br/>('1701538', 'Andrew Y. Ng', 'andrew y. ng')<br/>('38701713', 'Kai Yu', 'kai yu')</td><td>{wzou, ang}@cs.stanford.edu <br/>{zsh, kyu}@sv.nec-labs.com -</td></tr><tr><td>aebb9649bc38e878baef082b518fa68f5cda23a5</td><td> -</td><td></td><td></td></tr><tr><td>ae5bb02599244d6d88c4fe466a7fdd80aeb91af4</td><td>Analysis of Recognition Algorithms using Linear, Generalized Linear, and +</td></tr><tr><td>ae2cf545565c157813798910401e1da5dc8a6199</td><td>Mahkonen et al. EURASIP Journal on Image and Video +<br/>Processing (2018) 2018:61 +<br/>https://doi.org/10.1186/s13640-018-0303-9 +<br/>EURASIP Journal on Image +<br/>and Video Processing +<br/>RESEARCH +<br/>Open Access +<br/>Cascade of Boolean detector +<br/>combinations +</td><td>('3292563', 'Katariina Mahkonen', 'katariina mahkonen')</td><td></td></tr><tr><td>aebb9649bc38e878baef082b518fa68f5cda23a5</td><td> +</td><td></td><td></td></tr><tr><td>aeaf5dbb3608922246c7cd8a619541ea9e4a7028</td><td>Weakly Supervised Facial Action Unit Recognition through Adversarial Training +<br/><b>University of Science and Technology of China, Hefei, Anhui, China</b></td><td>('46217896', 'Guozhu Peng', 'guozhu peng')<br/>('1791319', 'Shangfei Wang', 'shangfei wang')</td><td>gzpeng@mail.ustc.edu.cn, sfwang@ustc.edu.cn +</td></tr><tr><td>ae836e2be4bb784760e43de88a68c97f4f9e44a1</td><td>Semi-Supervised Dimensionality Reduction∗ +<br/>1National Laboratory for Novel Software Technology +<br/><b>Nanjing University, Nanjing 210093, China</b><br/>2Department of Computer Science and Engineering +<br/><b>Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China</b></td><td>('51326748', 'Daoqiang Zhang', 'daoqiang zhang')<br/>('46228434', 'Zhi-Hua Zhou', 'zhi-hua zhou')<br/>('1680768', 'Songcan Chen', 'songcan chen')</td><td>dqzhang@nuaa.edu.cn +<br/>zhouzh@nju.edu.cn +<br/>s.chen@nuaa.edu.cn +</td></tr><tr><td>ae5bb02599244d6d88c4fe466a7fdd80aeb91af4</td><td>Analysis of Recognition Algorithms using Linear, Generalized Linear, and <br/>Generalized Linear Mixed Models <br/>Dept. of Computer Science <br/><b>Colorado State University</b><br/>Fort Colllins, CO 80523 @@ -10595,6 +12828,10 @@ </td><td>('39048426', 'Nan Sun', 'nan sun')<br/>('11832393', 'Zheng Chen', 'zheng chen')<br/>('1818364', 'Richard Day', 'richard day')</td><td>bruce.n.sun@gmail.com1 <br/>z.chen@glyndwr.ac.uk2 <br/>r.day@glyndwr.ac.uk3 +</td></tr><tr><td>aeff403079022683b233decda556a6aee3225065</td><td>DeepFace: Face Generation using Deep Learning +</td><td>('31560532', 'Hardie Cate', 'hardie cate')<br/>('6415321', 'Fahim Dalvi', 'fahim dalvi')<br/>('8815003', 'Zeshan Hussain', 'zeshan hussain')</td><td>ccate@stanford.edu +<br/>fdalvi@cs.stanford.edu +<br/>zeshanmh@stanford.edu </td></tr><tr><td>ae753fd46a744725424690d22d0d00fb05e53350</td><td>000 <br/>001 <br/>002 @@ -10646,11 +12883,71 @@ </td><td></td><td></td></tr><tr><td>aea4128ba18689ff1af27b90c111bbd34013f8d5</td><td>Efficient k-Support Matrix Pursuit <br/><b>National University of Singapore</b><br/><b>School of Software, Sun Yat-sen University, China</b><br/><b>School of Information Science and Technology, Sun Yat-sen University, China</b><br/><b>School of Computer Science, South China Normal University, China</b></td><td>('2356867', 'Hanjiang Lai', 'hanjiang lai')<br/>('2493641', 'Yan Pan', 'yan pan')<br/>('33224509', 'Canyi Lu', 'canyi lu')<br/>('1704995', 'Yong Tang', 'yong tang')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td>{laihanj,canyilu}@gmail.com, panyan5@mail.sysu.edu.cn, <br/>ytang@scnu.edu.cn, eleyans@nus.edu.sg +</td></tr><tr><td>ae2c71080b0e17dee4e5a019d87585f2987f0508</td><td>Research Paper: Emotional Face Recognition in Children +<br/>With Attention Deficit/Hyperactivity Disorder: Evidence +<br/>From Event Related Gamma Oscillation +<br/>CrossMark +<br/><b>School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran</b><br/><b>School of Medicine, Tehran University of Medical Sciences, Tehran, Iran</b><br/><b>Research Center for Cognitive and Behavioral Sciences, Tehran University of Medical Sciences, Tehran, Iran</b><br/><b>Amirkabir University of Technology, Tehran, Iran</b><br/>Use your device to scan +<br/>and read the article online +<br/>Citation: Sarraf Razavi, M., Tehranidoost, M., Ghassemi, F., Purabassi, P., & Taymourtash, A. (2017). Emotional Face Rec- +<br/>ognition in Children With Attention Deficit/Hyperactivity Disorder: Evidence From Event Related Gamma Oscillation. Basic +<br/>and Clinical Neuroscience, 8(5):419-426. https://doi.org/10.18869/NIRP.BCN.8.5.419 +<br/> : : https://doi.org/10.18869/NIRP.BCN.8.5.419 +<br/>Article info: +<br/>Received: 03 Feb. 2017 +<br/>First Revision: 29 Feb. 2017 +<br/>Accepted: 11 Jul. 2017 +<br/>Key Words: +<br/>Emotional face +<br/>recognition, Event- +<br/>Related Oscillation +<br/>(ERO), Gamma band +<br/>activity, Attention Deficit +<br/>Hyperactivity Disorder +<br/>(ADHD) +<br/>A B S T R A C T +<br/>Introduction: Children with attention-deficit/hyperactivity disorder (ADHD) have some +<br/>impairment in emotional relationship which can be due to problems in emotional processing. +<br/>The present study investigated neural correlates of early stages of emotional face processing in +<br/>this group compared with typically developing children using the Gamma Band Activity (GBA). +<br/>Methods: A total of 19 children diagnosed with ADHD (Combined type) based on DSM-IV +<br/>classification were compared with 19 typically developing children matched on age, gender, and +<br/>IQ. The participants performed an emotional face recognition while their brain activities were +<br/>recorded using an event-related oscillation procedure. +<br/>Results: The results indicated that ADHD children compared to normal group showed a significant +<br/>reduction in the gamma band activity, which is thought to reflect early perceptual emotion +<br/>discrimination for happy and angry emotions (P<0.05). +<br/>Conclusion: The present study supports the notion that individuals with ADHD have some +<br/>impairments in early stage of emotion processing which can cause their misinterpretation of +<br/>emotional faces. +<br/>1. Introduction +<br/>DHD is a common neurodevelopmental +<br/>disorder characterized by inattentiveness +<br/>and hyperactivity/impulsivity (American +<br/>Psychiatric Association, 2013). Individu- +<br/>als with ADHD also show problems in social and emo- +<br/><b>tional functions, including the effective assessment of</b><br/>the emotional state of others. It is important to set the +<br/>adaptive behavior of human facial expressions in social +<br/>interactions (Cadesky, Mota, & Schachar, 2000; Corbett +<br/>& Glidden, 2000). Based on the evidence, frontotem- +<br/>poral-posterior and fronto striatal cerebellar systems +<br/>are involved in emotional functions. These regions may +<br/>contribute to impairments of emotional recognition in +<br/>ADHD (Corbett & Glidden, 2000; Dickstein, Bannon, +<br/>Xavier Castellanos, & Milham, 2006; Durston, Van +<br/>Belle, & De Zeeuw, 2011). +<br/>* Corresponding Author: +<br/><b>Amirkabir University of Technology, Tehran, Iran</b><br/>Tel:+98 (912) 3260661 +<br/>419 +<br/>Basic and ClinicalSeptember, October 2017, Volume 8, Number 5 </td><td>('29928144', 'Mahdiyeh Sarraf Razavi', 'mahdiyeh sarraf razavi')<br/>('7171067', 'Mehdi Tehranidoost', 'mehdi tehranidoost')<br/>('34494047', 'Farnaz Ghassemi', 'farnaz ghassemi')<br/>('29839761', 'Parivash Purabassi', 'parivash purabassi')<br/>('29933673', 'Athena Taymourtash', 'athena taymourtash')<br/>('34494047', 'Farnaz Ghassemi', 'farnaz ghassemi')</td><td>E-mail: ghassemi@aut.ac.ir </td></tr><tr><td>ae4e2c81c8a8354c93c4b21442c26773352935dd</td><td></td><td></td><td></td></tr><tr><td>ae85c822c6aec8b0f67762c625a73a5d08f5060d</td><td>This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. <br/>The final version of record is available at http://dx.doi.org/10.1109/TPAMI.2014.2353624 <br/>IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. M, NO. N, MONTH YEAR <br/>Retrieving Similar Styles to Parse Clothing -</td><td>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')<br/>('1772294', 'M. Hadi Kiapour', 'm. hadi kiapour')<br/>('35258350', 'Luis E. Ortiz', 'luis e. ortiz')<br/>('1685538', 'Tamara L. Berg', 'tamara l. berg')</td><td></td></tr><tr><td>ae71f69f1db840e0aa17f8c814316f0bd0f6fbbf</td><td>Contents lists available at ScienceDirect +</td><td>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')<br/>('1772294', 'M. Hadi Kiapour', 'm. hadi kiapour')<br/>('35258350', 'Luis E. Ortiz', 'luis e. ortiz')<br/>('1685538', 'Tamara L. Berg', 'tamara l. berg')</td><td></td></tr><tr><td>ae5f32e489c4d52e7311b66060c7381d932f4193</td><td>Appearance-and-Relation Networks for Video Classification +<br/><b>State Key Laboratory for Novel Software Technology, Nanjing University, China</b><br/>2Computer Vision Laboratory, ETH Zurich, Switzerland +<br/>3Google Research +</td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('47113208', 'Wei Li', 'wei li')<br/>('50135099', 'Wen Li', 'wen li')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td></td></tr><tr><td>ae71f69f1db840e0aa17f8c814316f0bd0f6fbbf</td><td>Contents lists available at ScienceDirect <br/>j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h <br/>Full length article <br/>That personal profile image might jeopardize your rental opportunity! @@ -10788,7 +13085,12 @@ </td><td></td><td></td></tr><tr><td>d83ae5926b05894fcda0bc89bdc621e4f21272da</td><td>version of the following thesis: <br/>Frugal Forests: Learning a Dynamic and Cost Sensitive <br/>Feature Extraction Policy for Anytime Activity Classification -</td><td>('1794409', 'Kristen Grauman', 'kristen grauman')<br/>('1728389', 'Peter Stone', 'peter stone')</td><td></td></tr><tr><td>d8bf148899f09a0aad18a196ce729384a4464e2b</td><td>FACIAL EXPRESSION RECOGNITION AND EXPRESSION +</td><td>('1794409', 'Kristen Grauman', 'kristen grauman')<br/>('1728389', 'Peter Stone', 'peter stone')</td><td></td></tr><tr><td>d86fabd4498c8feaed80ec342d254fb877fb92f5</td><td>Y. GOUTSU: REGION-OBJECT RELEVANCE-GUIDED VRD +<br/>Region-Object Relevance-Guided +<br/>Visual Relationship Detection +<br/><b>National Institute of Informatics</b><br/>Tokyo, Japan +</td><td>('2897806', 'Yusuke Goutsu', 'yusuke goutsu')</td><td>goutsu@nii.ac.jp +</td></tr><tr><td>d8bf148899f09a0aad18a196ce729384a4464e2b</td><td>FACIAL EXPRESSION RECOGNITION AND EXPRESSION <br/>INTENSITY ESTIMATION <br/>A dissertation submitted to the <br/>Graduate School—New Brunswick @@ -10800,7 +13102,16 @@ <br/>and approved by <br/>New Brunswick, New Jersey <br/>May, 2011 -</td><td>('1683829', 'PENG YANG', 'peng yang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>d850aff9d10a01ad5f1d8a1b489fbb3998d0d80e</td><td><b>UNIVERSITY OF CALIFORNIA</b><br/>IRVINE +</td><td>('1683829', 'PENG YANG', 'peng yang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>d80a3d1f3a438e02a6685e66ee908446766fefa9</td><td>ZHANG ET AL.: QUANTIFYING FACIAL AGE BY POSTERIOR OF AGE COMPARISONS +<br/>Quantifying Facial Age by Posterior of +<br/>Age Comparisons +<br/>1 SenseTime Group Limited +<br/>2 Department of Information Engineering, +<br/><b>The Chinese University of Hong Kong</b></td><td>('6693591', 'Yunxuan Zhang', 'yunxuan zhang')<br/>('46457827', 'Li Liu', 'li liu')<br/>('46651787', 'Cheng Li', 'cheng li')<br/>('1717179', 'Chen Change Loy', 'chen change loy')</td><td>zhangyunxuan@sensetime.com +<br/>liuli@sensetime.com +<br/>chengli@sensetime.com +<br/>ccloy@ie.cuhk.edu.hk +</td></tr><tr><td>d850aff9d10a01ad5f1d8a1b489fbb3998d0d80e</td><td><b>UNIVERSITY OF CALIFORNIA</b><br/>IRVINE <br/>Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter <br/>DISSERTATION <br/>submitted in partial satisfaction of the requirements @@ -10813,9 +13124,21 @@ <br/>Professor Deva Ramanan <br/>Professor Alexander Ihler <br/>2016 -</td><td>('1898210', 'Golnaz Ghiasi', 'golnaz ghiasi')</td><td></td></tr><tr><td>ab8f9a6bd8f582501c6b41c0e7179546e21c5e91</td><td>Nonparametric Face Verification Using a Novel +</td><td>('1898210', 'Golnaz Ghiasi', 'golnaz ghiasi')</td><td></td></tr><tr><td>d89cfed36ce8ffdb2097c2ba2dac3e2b2501100d</td><td>Robust Face Recognition via Multimodal Deep +<br/>Face Representation +</td><td>('37990555', 'Changxing Ding', 'changxing ding')<br/>('1692693', 'Dacheng Tao', 'dacheng tao')</td><td></td></tr><tr><td>ab8f9a6bd8f582501c6b41c0e7179546e21c5e91</td><td>Nonparametric Face Verification Using a Novel <br/>Face Representation -</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>aba770a7c45e82b2f9de6ea2a12738722566a149</td><td>Face Recognition in the Scrambled Domain via Salience-Aware +</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>ab58a7db32683aea9281c188c756ddf969b4cdbd</td><td>Efficient Solvers for Sparse Subspace Clustering +</td><td>('50333204', 'Stephen Becker', 'stephen becker')</td><td></td></tr><tr><td>ab734bac3994b00bf97ce22b9abc881ee8c12918</td><td>Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold +<br/>with Application to Image Set Classification +<br/>†Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), +<br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, 100049, China</b><br/>§Cooperative Medianet Innovation Center, China +</td><td>('7945869', 'Zhiwu Huang', 'zhiwu huang')<br/>('3373117', 'Ruiping Wang', 'ruiping wang')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('3046528', 'Xianqiu Li', 'xianqiu li')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>ZHIWU.HUANG@VIPL.ICT.AC.CN +<br/>WANGRUIPING@ICT.AC.CN +<br/>SGSHAN@ICT.AC.CN +<br/>XIANQIU.LI@VIPL.ICT.AC.CN +<br/>XLCHEN@ICT.AC.CN +</td></tr><tr><td>aba770a7c45e82b2f9de6ea2a12738722566a149</td><td>Face Recognition in the Scrambled Domain via Salience-Aware <br/>Ensembles of Many Kernels <br/>Jiang, R., Al-Maadeed, S., Bouridane, A., Crookes, D., & Celebi, M. E. (2016). Face Recognition in the <br/>Scrambled Domain via Salience-Aware Ensembles of Many Kernels. IEEE Transactions on Information @@ -10841,7 +13164,9 @@ </td></tr><tr><td>abb396490ba8b112f10fbb20a0a8ce69737cd492</td><td>Robust Face Recognition Using Color <br/>Information <br/><b>New Jersey Institute of Technology</b></td><td>('2047820', 'Zhiming Liu', 'zhiming liu')<br/>('39664966', 'Chengjun Liu', 'chengjun liu')</td><td>Newark, New Jersey 07102, USA. femail:zl9@njit.edug -</td></tr><tr><td>abac0fa75281c9a0690bf67586280ed145682422</td><td>Describable Visual Attributes for Face Images +</td></tr><tr><td>ab989225a55a2ddcd3b60a99672e78e4373c0df1</td><td>Sample, Computation vs Storage Tradeoffs for +<br/>Classification Using Tensor Subspace Models +</td><td>('9039699', 'Mohammadhossein Chaghazardi', 'mohammadhossein chaghazardi')<br/>('1980683', 'Shuchin Aeron', 'shuchin aeron')</td><td></td></tr><tr><td>abac0fa75281c9a0690bf67586280ed145682422</td><td>Describable Visual Attributes for Face Images <br/>Submitted in partial fulfillment of the <br/>requirements for the degree <br/>of Doctor of Philosophy @@ -10851,7 +13176,53 @@ <br/>ISSN 2229-5518 <br/>A Survey on Various Facial Expression <br/>Techniques -</td><td>('2122870', 'Joy Bhattacharya', 'joy bhattacharya')</td><td></td></tr><tr><td>ab87dfccb1818bdf0b41d732da1f9335b43b74ae</td><td>SUBMITTED TO IEEE TRANSACTIONS ON SIGNAL PROCESSING +</td><td>('2122870', 'Joy Bhattacharya', 'joy bhattacharya')</td><td></td></tr><tr><td>ab1719f573a6c121d7d7da5053fe5f12de0182e7</td><td>Combining Visual Recognition +<br/>and Computational Linguistics +<br/>Linguistic Knowledge for Visual Recognition +<br/>and Natural Language Descriptions +<br/>of Visual Content +<br/>Thesis for obtaining the title of +<br/>Doctor of Engineering Science +<br/>(Dr.-Ing.) +<br/>of the Faculty of Natural Science and Technology I +<br/><b>of Saarland University</b><br/>by +<br/>Saarbrücken +<br/>March 2014 +</td><td>('34849128', 'Marcus Rohrbach', 'marcus rohrbach')</td><td></td></tr><tr><td>ab2b09b65fdc91a711e424524e666fc75aae7a51</td><td>Multi-modal Biomarkers to Discriminate Cognitive State* +<br/>1MIT Lincoln Laboratory, Lexington, Massachusetts, USA +<br/>2USARIEM, 3NSRDEC +<br/>1. Introduction +<br/>Multimodal biomarkers based on behavorial, neurophysiolgical, and cognitive measurements have +<br/>recently obtained increasing popularity in the detection of cognitive stress- and neurological-based +<br/>disorders. Such conditions are significantly and adversely affecting human performance and quality +<br/>of life for a large fraction of the world’s population. Example modalities used in detection of these +<br/>conditions include voice, facial expression, physiology, eye tracking, gait, and EEG analysis. +<br/>Toward the goal of finding simple, noninvasive means to detect, predict and monitor cognitive +<br/>stress and neurological conditions, MIT Lincoln Laboratory is developing biomarkers that satisfy +<br/>three criteria. First, we seek biomarkers that reflect core components of cognitive status such as +<br/>working memory capacity, processing speed, attention, and arousal. Second, and as importantly, we +<br/>seek biomarkers that reflect timing and coordination relations both within components of each +<br/>modality and across different modalities. This is based on the hypothesis that neural coordination +<br/>across different parts of the brain is essential in cognition (Figure 1). An example of timing and +<br/>coordination within a modality is the set of finely timed and synchronized physiological +<br/>components of speech production, while an example of coordination across modalities is the timing +<br/>and synchrony that occurs across speech and facial expression while speaking. Third, we seek +<br/>multimodal biomarkers that contribute in a complementary fashion under various channel and +<br/>background conditions. In this chapter, as an illustration of this biomarker approach we focus on +<br/>cognitive stress and the particular case of detecting different cognitive load levels. We also briefly +<br/>show how similar feature-extraction principles can be applied to a neurological condition through +<br/>the example of major depression disorder (MDD). MDD is one of several neurological disorders +<br/>where multi-modal biomarkers based on principles of timing and coordination are important for +<br/>detection [11]-[22]. In our cognitive load experiments, we use two easily obtained noninvasive +<br/>modalities, voice and face, and show how these two modalities can be fused to produce results on +<br/>par with more invasive, “gold-standard” EEG measurements. Vocal and facial biomarkers will also +<br/>be used in our MDD case study. In both application areas we focus on timing and coordination +<br/>relations within the components of each modality. +<br/>* Distribution A: public release.This work is sponsored by the Assistant Secretary of Defense for Research & Engineering under Air Force contract +<br/>#FA8721-05-C-0002. Opinions,interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States +<br/>Government. +</td><td>('1718470', 'Thomas F. Quatieri', 'thomas f. quatieri')<br/>('48628822', 'James R. Williamson', 'james r. williamson')<br/>('2794344', 'Christopher J. Smalt', 'christopher j. smalt')<br/>('38799981', 'Tejash Patel', 'tejash patel')<br/>('2894484', 'Brian S. Helfer', 'brian s. helfer')<br/>('3051832', 'Daryush D. Mehta', 'daryush d. mehta')<br/>('35718569', 'Kristin Heaton', 'kristin heaton')<br/>('47534051', 'Marianna Eddy', 'marianna eddy')<br/>('49739272', 'Joseph Moran', 'joseph moran')</td><td>[quatieri,jrw]@ll.mit.edu +</td></tr><tr><td>ab87dfccb1818bdf0b41d732da1f9335b43b74ae</td><td>SUBMITTED TO IEEE TRANSACTIONS ON SIGNAL PROCESSING <br/>Structured Dictionary Learning for Classification </td><td>('36657778', 'Yuanming Suo', 'yuanming suo')<br/>('31507586', 'Minh Dao', 'minh dao')<br/>('35210356', 'Umamahesh Srinivas', 'umamahesh srinivas')<br/>('3346079', 'Vishal Monga', 'vishal monga')<br/>('1709073', 'Trac D. Tran', 'trac d. tran')</td><td></td></tr><tr><td>abc1ef570bb2d7ea92cbe69e101eefa9a53e1d72</td><td>Raisonnement abductif en logique de <br/>description exploitant les domaines concrets @@ -10870,6 +13241,14 @@ <br/>concrets pour évaluer le degré de satisfaction des relations spatiales entre les objets. </td><td>('4156317', 'Yifan Yang', 'yifan yang')<br/>('1773774', 'Jamal Atif', 'jamal atif')<br/>('1695917', 'Isabelle Bloch', 'isabelle bloch')</td><td>{yifan.yang,isabelle.bloch}@telecom-paristech.fr <br/>jamal.atif@dauphine.fr +</td></tr><tr><td>abba1bf1348a6f1b70a26aac237338ee66764458</td><td>Facial Action Unit Detection Using Attention and Relation Learning +<br/><b>Shanghai Jiao Tong University, China</b><br/><b>School of Computer Science and Technology, Tianjin University, China</b><br/><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore</b><br/>4 Tencent YouTu, China +<br/><b>School of Computer Science and Software Engineering, East China Normal University, China</b></td><td>('3403352', 'Zhiwen Shao', 'zhiwen shao')<br/>('1771215', 'Zhilei Liu', 'zhilei liu')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')<br/>('10609538', 'Yunsheng Wu', 'yunsheng wu')<br/>('8452947', 'Lizhuang Ma', 'lizhuang ma')</td><td>shaozhiwen@sjtu.edu.cn, zhileiliu@tju.edu.cn, asjfcai@ntu.edu.sg +<br/>simonwu@tencent.com, ma-lz@cs.sjtu.edu.cn +</td></tr><tr><td>abdd17e411a7bfe043f280abd4e560a04ab6e992</td><td>Pose-Robust Face Recognition via Deep Residual Equivariant Mapping +<br/><b>The Chinese University of Hong Kong</b><br/>2SenseTime Research +</td><td>('9963152', 'Kaidi Cao', 'kaidi cao')<br/>('46651787', 'Cheng Li', 'cheng li')</td><td>{ry017, ccloy, xtang}@ie.cuhk.edu.hk +<br/>{caokaidi, chengli}@sensetime.com </td></tr><tr><td>ab1dfcd96654af0bf6e805ffa2de0f55a73c025d</td><td></td><td></td><td></td></tr><tr><td>abeda55a7be0bbe25a25139fb9a3d823215d7536</td><td>UNIVERSITATPOLITÈCNICADECATALUNYAProgramadeDoctorat:AUTOMÀTICA,ROBÒTICAIVISIÓTesiDoctoralUnderstandingHuman-CentricImages:FromGeometrytoFashionEdgarSimoSerraDirectors:FrancescMorenoNoguerCarmeTorrasMay2015 </td><td></td><td></td></tr><tr><td>ab427f0c7d4b0eb22c045392107509451165b2ba</td><td>LEARNING SCALE RANGES FOR THE EXTRACTION OF REGIONS OF <br/>INTEREST <br/><b>Western Kentucky University</b><br/>Department of Mathematics and Computer Science @@ -10888,7 +13267,27 @@ <br/>GENÈVE <br/>Repro-Mail - Université de Genève <br/>2011 -</td><td>('1809085', 'Thierry Pun', 'thierry pun')<br/>('2463695', 'Mohammad SOLEYMANI', 'mohammad soleymani')</td><td></td></tr><tr><td>e5737ffc4e74374b0c799b65afdbf0304ff344cb</td><td></td><td></td><td></td></tr><tr><td>e510f2412999399149d8635a83eca89c338a99a1</td><td>Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283 +</td><td>('1809085', 'Thierry Pun', 'thierry pun')<br/>('2463695', 'Mohammad SOLEYMANI', 'mohammad soleymani')</td><td></td></tr><tr><td>e5e5f31b81ed6526c26d277056b6ab4909a56c6c</td><td>Revisit Multinomial Logistic Regression in Deep Learning: +<br/>Data Dependent Model Initialization for Image Recognition +<br/><b>University of Illinois at Urbana-Champaign</b><br/>2Ping An Property&Casualty Insurance Company of China, +<br/>3Microsoft +</td><td>('50563570', 'Bowen Cheng', 'bowen cheng')<br/>('1972288', 'Rong Xiao', 'rong xiao')<br/>('3133575', 'Yandong Guo', 'yandong guo')<br/>('1689532', 'Yuxiao Hu', 'yuxiao hu')<br/>('38504661', 'Jianfeng Wang', 'jianfeng wang')<br/>('48571185', 'Lei Zhang', 'lei zhang')</td><td>1bcheng9@illinois.edu +<br/>2xiaorong283@pingan.com.cn +<br/>3yandong.guo@live.com, yuxiaohu@msn.com, {jianfw, leizhang}@microsoft.com +</td></tr><tr><td>e5737ffc4e74374b0c799b65afdbf0304ff344cb</td><td></td><td></td><td></td></tr><tr><td>e506cdb250eba5e70c5147eb477fbd069714765b</td><td>Heterogeneous Face Recognition +<br/>By +<br/>Brendan F. Klare +<br/>A Dissertation +<br/>Submitted to +<br/><b>Michigan State University</b><br/>in partial fulfillment of the requirements +<br/>for the degree of +<br/>Doctor of Philosophy +<br/>Computer Science and Engineering +<br/>2012 +</td><td></td><td></td></tr><tr><td>e572c42d8ef2e0fadedbaae77c8dfe05c4933fbf</td><td>A Visual Historical Record of American High School Yearbooks +<br/>A Century of Portraits: +<br/><b>University of California Berkeley</b><br/><b>Brown University</b><br/><b>University of California Berkeley</b></td><td>('2361255', 'Shiry Ginosar', 'shiry ginosar')<br/>('2660664', 'Kate Rakelly', 'kate rakelly')<br/>('33385802', 'Sarah Sachs', 'sarah sachs')<br/>('2130100', 'Brian Yin', 'brian yin')<br/>('1763086', 'Alexei A. Efros', 'alexei a. efros')</td><td></td></tr><tr><td>e5823a9d3e5e33e119576a34cb8aed497af20eea</td><td>DocFace+: ID Document to Selfie* Matching +</td><td>('9644181', 'Yichun Shi', 'yichun shi')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>e5dfd17dbfc9647ccc7323a5d62f65721b318ba9</td><td></td><td></td><td></td></tr><tr><td>e510f2412999399149d8635a83eca89c338a99a1</td><td>Journal of Advanced Computer Science and Technology, 1 (4) (2012) 266-283 <br/>c(cid:13)Science Publishing Corporation <br/>www.sciencepubco.com/index.php/JACST <br/>Face Recognition using Block-Based @@ -10899,6 +13298,12 @@ <br/>E-mail: vaish.india@gmail.com <br/>E-mail: sasikiran.f4@gmail.com <br/>E-mail: ramachandr@gmail.com +</td></tr><tr><td>e56c4c41bfa5ec2d86c7c9dd631a9a69cdc05e69</td><td>Human Activity Recognition Based on Wearable +<br/>Sensor Data: A Standardization of the +<br/>State-of-the-Art +<br/>Smart Surveillance Interest Group, Computer Science Department +<br/>Universidade Federal de Minas Gerais, Brazil +</td><td>('2954974', 'Antonio C. Nazare', 'antonio c. nazare')<br/>('1679142', 'William Robson Schwartz', 'william robson schwartz')</td><td>Email: {arturjordao, antonio.nazare, jessicasena, william}@dcc.ufmg.br </td></tr><tr><td>e59813940c5c83b1ce63f3f451d03d34d2f68082</td><td>Faculty of Informatics - Papers (Archive) <br/>Faculty of Engineering and Information Sciences <br/><b>University of Wollongong</b><br/>Research Online @@ -10916,7 +13321,26 @@ <br/>Library: research-pubs@uow.edu.au </td></tr><tr><td>e5b301ee349ba8e96ea6c71782295c4f06be6c31</td><td>The Case for Onloading Continuous High-Datarate Perception to the Phone <br/><b>University of Washington</b><br/>Microsoft Research -</td><td>('1871038', 'Seungyeop Han', 'seungyeop han')<br/>('3041721', 'Matthai Philipose', 'matthai philipose')</td><td></td></tr><tr><td>e5342233141a1d3858ed99ccd8ca0fead519f58b</td><td>ISSN: 2277 – 9043 +</td><td>('1871038', 'Seungyeop Han', 'seungyeop han')<br/>('3041721', 'Matthai Philipose', 'matthai philipose')</td><td></td></tr><tr><td>e569f4bd41895028c4c009e5b46b935056188e91</td><td>SIMONYAN et al.: FISHER VECTOR FACES IN THE WILD +<br/>Fisher Vector Faces in the Wild +<br/>Visual Geometry Group +<br/>Department of Engineering Science +<br/><b>University of Oxford</b><br/>Omkar M. Parkhi +<br/>Andrea Vedaldi +<br/>Andrew Zisserman +</td><td>('34838386', 'Karen Simonyan', 'karen simonyan')</td><td>karen@robots.ox.ac.uk +<br/>omkar@robots.ox.ac.uk +<br/>vedaldi@robots.ox.ac.uk +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>e5fbffd3449a2bfe0acb4ec339a19f5b88fff783</td><td>WILES, KOEPKE, ZISSERMAN: SELF-SUP. FACIAL ATTRIBUTE FROM VIDEO +<br/>Self-supervised learning of a facial attribute +<br/>embedding from video +<br/>Visual Geometry Group +<br/><b>University of Oxford</b><br/>Oxford, UK +</td><td>('8792285', 'Olivia Wiles', 'olivia wiles')<br/>('47104886', 'A. Sophia Koepke', 'a. sophia koepke')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>ow@robots.ox.ac.uk +<br/>koepke@robots.ox.ac.uk +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>e5342233141a1d3858ed99ccd8ca0fead519f58b</td><td>ISSN: 2277 – 9043 <br/>International Journal of Advanced Research in Computer Science and Electronics Engineering (IJARCSEE) <br/>Volume 2, Issue 2, February 2013 <br/>Finger print and Palm print based Multibiometric @@ -10939,22 +13363,77 @@ <br/>your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask <br/><b>the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam</b><br/>The Netherlands. You will be contacted as soon as possible. <br/>Download date: 12 Sep 2017 -<br/><b>UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl</b></td><td></td><td></td></tr><tr><td>e5799fd239531644ad9270f49a3961d7540ce358</td><td>KINSHIP CLASSIFICATION BY MODELING FACIAL FEATURE HEREDITY +<br/><b>UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl</b></td><td></td><td></td></tr><tr><td>e5d53a335515107452a30b330352cad216f88fc3</td><td>Generalized Loss-Sensitive Adversarial Learning +<br/>with Manifold Margins +<br/>Laboratory for MAchine Perception and LEarning (MAPLE) +<br/>http://maple.cs.ucf.edu/ +<br/><b>University of Central Florida, Orlando FL 32816, USA</b></td><td>('46232436', 'Marzieh Edraki', 'marzieh edraki')<br/>('2272096', 'Guo-Jun Qi', 'guo-jun qi')</td><td>m.edraki@knights.ucf.edu, guojun.qi@ucf.edu +</td></tr><tr><td>e5799fd239531644ad9270f49a3961d7540ce358</td><td>KINSHIP CLASSIFICATION BY MODELING FACIAL FEATURE HEREDITY <br/><b>Cornell University 2Eastman Kodak Company</b></td><td>('2666471', 'Ruogu Fang', 'ruogu fang')<br/>('39460815', 'Andrew C. Gallagher', 'andrew c. gallagher')<br/>('1746230', 'Tsuhan Chen', 'tsuhan chen')</td><td></td></tr><tr><td>e5eb7fa8c9a812d402facfe8e4672670541ed108</td><td>Performance of PCA Based Semi-supervised <br/>Learning in Face Recognition Using MPEG-7 <br/>Edge Histogram Descriptor <br/>Department of Computer Science and Engineering <br/><b>Bangladesh University of Engineering and Technology(BUET</b><br/>Dhaka-1000, Bangladesh </td><td>('3034202', 'Sheikh Motahar Naim', 'sheikh motahar naim')<br/>('9248625', 'Abdullah Al Farooq', 'abdullah al farooq')<br/>('1990532', 'Md. Monirul Islam', 'md. monirul islam')</td><td>Email: {shafin buet, naim sbh2007, saurav00001}@yahoo.com, mmislam@cse.buet.ac.bd +</td></tr><tr><td>e22adcd2a6a7544f017ec875ce8f89d5c59e09c8</td><td>Published in Proc. of IEEE 9th International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Los +<br/>Angeles, CA), October 2018. +<br/>Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding +<br/>Arbitrary Gender Classifiers +<br/><b>Computer Science and Engineering, Michigan State University, East Lansing, USA</b><br/><b>University of Wisconsin Madison, USA</b></td><td>('5456235', 'Vahid Mirjalili', 'vahid mirjalili')<br/>('2562040', 'Sebastian Raschka', 'sebastian raschka')<br/>('1698707', 'Arun Ross', 'arun ross')</td><td>mirjalil@cse.msu.edu +<br/>mail@sebastianraschka.com +<br/>rossarun@cse.msu.edu </td></tr><tr><td>e27c92255d7ccd1860b5fb71c5b1277c1648ed1e</td><td></td><td></td><td></td></tr><tr><td>e200c3f2849d56e08056484f3b6183aa43c0f13a</td><td></td><td></td><td></td></tr><tr><td>e2d265f606cd25f1fd72e5ee8b8f4c5127b764df</td><td>Real-Time End-to-End Action Detection <br/>with Two-Stream Networks <br/><b>School of Engineering, University of Guelph</b><br/><b>Vector Institute for Arti cial Intelligence</b><br/><b>Canadian Institute for Advanced Research</b></td><td>('35933395', 'Alaaeldin El-Nouby', 'alaaeldin el-nouby')<br/>('3861110', 'Graham W. Taylor', 'graham w. taylor')</td><td>{aelnouby,gwtaylor}@uoguelph.ca +</td></tr><tr><td>e293a31260cf20996d12d14b8f29a9d4d99c4642</td><td>Published as a conference paper at ICLR 2017 +<br/>LR-GAN: LAYERED RECURSIVE GENERATIVE AD- +<br/>VERSARIAL NETWORKS FOR IMAGE GENERATION +<br/>Virginia Tech +<br/>Blacksburg, VA +<br/>Facebook AI Research +<br/>Menlo Park, CA +<br/><b>Georgia Institute of Technology</b><br/>Atlanta, GA +</td><td>('2404941', 'Jianwei Yang', 'jianwei yang')<br/>('39248118', 'Anitha Kannan', 'anitha kannan')<br/>('1746610', 'Dhruv Batra', 'dhruv batra')</td><td>jw2yang@vt.edu +<br/>akannan@fb.com +<br/>{dbatra, parikh}@gatech.edu +</td></tr><tr><td>e20e2db743e8db1ff61279f4fda32bf8cf381f8e</td><td>Deep Cross Polarimetric Thermal-to-visible Face Recognition +<br/><b>West Virginia University</b></td><td>('6779960', 'Seyed Mehdi Iranmanesh', 'seyed mehdi iranmanesh')<br/>('35477977', 'Ali Dabouei', 'ali dabouei')<br/>('2700951', 'Hadi Kazemi', 'hadi kazemi')<br/>('8147588', 'Nasser M. Nasrabadi', 'nasser m. nasrabadi')</td><td>{seiranmanesh, ad0046, hakazemi}@mix.wvu.edu, {nasser.nasrabadi}@mail.wvu.edu </td></tr><tr><td>f437b3884a9e5fab66740ca2a6f1f3a5724385ea</td><td>Human Identification Technical Challenges <br/>DARPA <br/>3701 N. Fairfax Dr <br/>Arlington, VA 22203 </td><td>('32028519', 'P. Jonathon Phillips', 'p. jonathon phillips')</td><td>jphillips@darpa.mil -</td></tr><tr><td>f43eeb578e0ca48abfd43397bbd15825f94302e4</td><td>Optical Computer Recognition of Facial Expressions +</td></tr><tr><td>f412d9d7bc7534e7daafa43f8f5eab811e7e4148</td><td>Durham Research Online +<br/>Deposited in DRO: +<br/>16 December 2014 +<br/>Version of attached le: +<br/>Accepted Version +<br/>Peer-review status of attached le: +<br/>Peer-reviewed +<br/>Citation for published item: +<br/>Kirk, H. E. and Hocking, D. R. and Riby, D. M. and Cornish, K. M. (2013) 'Linking social behaviour and +<br/>anxiety to attention to emotional faces in Williams syndrome.', Research in developmental disabilities., 34 +<br/>(12). pp. 4608-4616. +<br/>Further information on publisher's website: +<br/>http://dx.doi.org/10.1016/j.ridd.2013.09.042 +<br/>Publisher's copyright statement: +<br/>NOTICE: this is the author's version of a work that was accepted for publication in Research in Developmental +<br/>Disabilities. Changes resulting from the publishing process, such as peer review, editing, corrections, structural +<br/>formatting, and other quality control mechanisms may not be re ected in this document. Changes may have been made +<br/>to this work since it was submitted for publication. A de nitive version was subsequently published in Research in +<br/>Developmental Disabilities, 34, 12, December 2013, 10.1016/j.ridd.2013.09.042. +<br/>Additional information: +<br/>Use policy +<br/>The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for +<br/>personal research or study, educational, or not-for-pro t purposes provided that: +<br/>• a full bibliographic reference is made to the original source +<br/>• a link is made to the metadata record in DRO +<br/>• the full-text is not changed in any way +<br/>The full-text must not be sold in any format or medium without the formal permission of the copyright holders. +<br/>Please consult the full DRO policy for further details. +<br/><b>Durham University Library, Stockton Road, Durham DH1 3LY, United Kingdom</b><br/>Tel : +44 (0)191 334 3042 | Fax : +44 (0)191 334 2971 +<br/>http://dro.dur.ac.uk +</td><td></td><td></td></tr><tr><td>f43eeb578e0ca48abfd43397bbd15825f94302e4</td><td>Optical Computer Recognition of Facial Expressions <br/>Associated with Stress Induced by Performance <br/>Demands <br/>DINGES DF, RIDER RL, DORRIAN J, MCGLINCHEY EL, ROGERS NL, @@ -11046,12 +13525,13 @@ <br/>dria, VA. <br/>B172 </td><td>('5515440', 'Jillian Dorrian', 'jillian dorrian')<br/>('4940404', 'Ziga Cizman', 'ziga cizman')<br/>('2467082', 'Christian Vogler', 'christian vogler')<br/>('2898034', 'Sundara Venkataraman', 'sundara venkataraman')</td><td>423 Guardian Drive, Philadelphia, PA 19104-6021; dinges@mail. -</td></tr><tr><td>f4f9697f2519f1fe725ee7e3788119ed217dca34</td><td>Selfie-Presentation in Everyday Life: A Large-scale +</td></tr><tr><td>f442a2f2749f921849e22f37e0480ac04a3c3fec</td><td></td><td></td><td> Critical Features for Face Recognition in Humans and Machines Naphtali Abudarham1, Lior Shkiller1, Galit Yovel1,2 1School of Psychological Sciences, 2Sagol School of Neuroscience Tel Aviv University, Tel Aviv, Israel Correspondence regarding this manuscript should be addressed to: Galit Yovel School of Psychological Sciences & Sagol School of Neuroscience Tel Aviv University Tel Aviv, 69978, Israel Email: gality@post.tau.ac.il, </td></tr><tr><td>f4f9697f2519f1fe725ee7e3788119ed217dca34</td><td>Selfie-Presentation in Everyday Life: A Large-scale <br/>Characterization of Selfie Contexts on Instagram <br/><b>Georgia Institute of Technology</b><br/>North Ave NW <br/>Atlanta, GA 30332 </td><td>('10799246', 'Julia Deeb-Swihart', 'julia deeb-swihart')<br/>('39723397', 'Christopher Polack', 'christopher polack')<br/>('1809407', 'Eric Gilbert', 'eric gilbert')</td><td>{jdeeb3, cfpolack,gilbert,irfan}@gatech.edu -</td></tr><tr><td>f4c01fc79c7ead67899f6fe7b79dd1ad249f71b0</td><td></td><td></td><td></td></tr><tr><td>f4373f5631329f77d85182ec2df6730cbd4686a9</td><td>Soft Computing manuscript No. +</td></tr><tr><td>f4f6fc473effb063b7a29aa221c65f64a791d7f4</td><td>Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 4/20/2018 Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +<br/>FacialexpressionrecognitioninthewildbasedonmultimodaltexturefeaturesBoSunLiandongLiGuoyanZhouJunHeBoSun,LiandongLi,GuoyanZhou,JunHe,“Facialexpressionrecognitioninthewildbasedonmultimodaltexturefeatures,”J.Electron.Imaging25(6),061407(2016),doi:10.1117/1.JEI.25.6.061407. </td><td></td><td></td></tr><tr><td>f4c01fc79c7ead67899f6fe7b79dd1ad249f71b0</td><td></td><td></td><td></td></tr><tr><td>f4373f5631329f77d85182ec2df6730cbd4686a9</td><td>Soft Computing manuscript No. <br/>(will be inserted by the editor) <br/>Recognizing Gender from Human Facial Regions using <br/>Genetic Algorithm @@ -11066,13 +13546,22 @@ <br/>Network </td><td>('7530203', 'Sneha Thakur', 'sneha thakur')</td><td> 1sne_thakur@yahoo.co.in <br/> 2ligendra@rediffmail.com -</td></tr><tr><td>f4ebbeb77249d1136c355f5bae30f02961b9a359</td><td>Human Computation for Attribute and Attribute Value Acquisition +</td></tr><tr><td>f4d30896c5f808a622824a2d740b3130be50258e</td><td>DS++: A Flexible, Scalable and Provably Tight Relaxation for Matching Problems +<br/><b>Weizmann Institute of Science</b></td><td>('3046344', 'Nadav Dym', 'nadav dym')<br/>('3416939', 'Haggai Maron', 'haggai maron')<br/>('3232072', 'Yaron Lipman', 'yaron lipman')</td><td></td></tr><tr><td>f4ebbeb77249d1136c355f5bae30f02961b9a359</td><td>Human Computation for Attribute and Attribute Value Acquisition <br/>School of Computer Science <br/><b>Carnegie Melon University</b></td><td>('2987829', 'Edith Law', 'edith law')<br/>('1717452', 'Burr Settles', 'burr settles')<br/>('2681926', 'Aaron Snook', 'aaron snook')<br/>('2762792', 'Harshit Surana', 'harshit surana')<br/>('3328108', 'Luis von Ahn', 'luis von ahn')<br/>('39182987', 'Tom Mitchell', 'tom mitchell')</td><td>edith@cmu.edu </td></tr><tr><td>f4aed1314b2d38fd8f1b9d2bc154295bbd45f523</td><td>Subspace Clustering using Ensembles of <br/>K-Subspaces <br/>Department of Electrical and Computer Engineering <br/><b>University of Michigan, Ann Arbor</b></td><td>('1782134', 'John Lipor', 'john lipor')<br/>('5250186', 'David Hong', 'david hong')<br/>('2358258', 'Dejiao Zhang', 'dejiao zhang')<br/>('1682385', 'Laura Balzano', 'laura balzano')</td><td>{lipor,dahong,dejiao,girasole}@umich.edu +</td></tr><tr><td>f42dca4a4426e5873a981712102aa961be34539a</td><td>Next-Flow: Hybrid Multi-Tasking with Next-Frame Prediction to Boost +<br/>Optical-Flow Estimation in the Wild +<br/><b>University of Freiburg</b><br/>Germany +</td><td>('31656404', 'Nima Sedaghat', 'nima sedaghat')</td><td>nima@cs.uni-freiburg.de +</td></tr><tr><td>f3ca2c43e8773b7062a8606286529c5bc9b3ce25</td><td>Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative +<br/>Entropy Minimization +<br/><b>Electrical and Computer Engineering, University of Pittsburgh, USA</b><br/><b>Computer Science and Engineering, University of Texas at Arlington, USA</b><br/><b>cid:93)School of Electronic Engineering, Xidian University, China</b><br/><b>cid:92)School of Information Technologies, University of Sydney, Australia</b></td><td>('2331771', 'Kamran Ghasedi Dizaji', 'kamran ghasedi dizaji')<br/>('10797930', 'Amirhossein Herandi', 'amirhossein herandi')<br/>('1748032', 'Heng Huang', 'heng huang')</td><td>kamran.ghasedi@gmail.com, amirhossein.herandi@uta.edu, chdeng@mail.xidian.edu.cn +<br/>tom.cai@sydney.edu.au, heng.huang@pitt.edu </td></tr><tr><td>f3fcaae2ea3e998395a1443c87544f203890ae15</td><td></td><td></td><td></td></tr><tr><td>f3015be0f9dbc1a55b6f3dc388d97bb566ff94fe</td><td>A Study on the Effective Approach <br/>to Illumination-Invariant Face Recognition <br/>Based on a Single Image @@ -11083,33 +13572,113 @@ <br/>methodology for head pose estimation in the wild <br/>IMAGO Research Group - Universidade Federal do Paran´a </td><td>('37435823', 'Antonio C. P. Nascimento', 'antonio c. p. nascimento')<br/>('1800955', 'Olga R. P. Bellon', 'olga r. p. bellon')</td><td>{flavio,antonio.paes,olga,luciano}@ufpr.br +</td></tr><tr><td>f3a59d85b7458394e3c043d8277aa1ffe3cdac91</td><td>Query-Free Attacks on Industry-Grade Face Recognition Systems under Resource +<br/>Constraints +<br/><b>Chinese University of Hong Kong</b><br/><b>Indiana University</b><br/><b>Chinese University of Hong Kong</b></td><td>('1807925', 'Di Tang', 'di tang')<br/>('47119002', 'XiaoFeng Wang', 'xiaofeng wang')<br/>('3297454', 'Kehuan Zhang', 'kehuan zhang')</td><td>td016@ie.cuhk.edu.hk +<br/>xw7@indiana.edu +<br/>khzhang@ie.cuhk.edu.hk </td></tr><tr><td>f3f77b803b375f0c63971b59d0906cb700ea24ed</td><td>Advances in Electrical and Computer Engineering Volume 9, Number 3, 2009 <br/>Feature Extraction for Facial Expression <br/>Recognition based on Hybrid Face Regions <br/>Seyed M. LAJEVARDI, Zahir M. HUSSAIN <br/><b>RMIT University, Australia</b></td><td></td><td>seyed.lajevardi @ rmit.edu.au -</td></tr><tr><td>f355e54ca94a2d8bbc598e06e414a876eb62ef99</td><td></td><td></td><td></td></tr><tr><td>f35a493afa78a671b9d2392c69642dcc3dd2cdc2</td><td>Automatic Attribute Discovery with Neural +</td></tr><tr><td>f355e54ca94a2d8bbc598e06e414a876eb62ef99</td><td></td><td></td><td></td></tr><tr><td>f3df296de36b7c114451865778e211350d153727</td><td>Spatio-Temporal Facial Expression Recognition Using Convolutional +<br/>Neural Networks and Conditional Random Fields +<br/><b>University of Denver, Denver, CO</b></td><td>('3093835', 'Mohammad H. Mahoor', 'mohammad h. mahoor')</td><td>behzad.hasani@du.edu, and mmahoor@du.edu +</td></tr><tr><td>f3ea181507db292b762aa798da30bc307be95344</td><td>Covariance Pooling for Facial Expression Recognition +<br/>†Computer Vision Lab, ETH Zurich, Switzerland +<br/>‡VISICS, KU Leuven, Belgium +</td><td>('32610154', 'Dinesh Acharya', 'dinesh acharya')<br/>('7945869', 'Zhiwu Huang', 'zhiwu huang')<br/>('35268081', 'Danda Pani Paudel', 'danda pani paudel')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>{acharyad, zhiwu.huang, paudel, vangool}@vision.ee.ethz.ch +</td></tr><tr><td>f3fed71cc4fc49b02067b71c2df80e83084b2a82</td><td>Published as a conference paper at ICLR 2018 +<br/>LEARNING SPARSE LATENT REPRESENTATIONS WITH +<br/>THE DEEP COPULA INFORMATION BOTTLENECK +<br/><b>University of Basel, Switzerland</b></td><td>('30069186', 'Aleksander Wieczorek', 'aleksander wieczorek')<br/>('30537851', 'Mario Wieser', 'mario wieser')<br/>('2620254', 'Damian Murezzan', 'damian murezzan')<br/>('39891341', 'Volker Roth', 'volker roth')</td><td>{firstname.lastname}@unibas.ch +</td></tr><tr><td>f3cf10c84c4665a0b28734f5233d423a65ef1f23</td><td>Title +<br/>Temporal Exemplar-based Bayesian Networks for facial +<br/>expression recognition +<br/>Author(s) +<br/>Shang, L; Chan, KP +<br/>Citation +<br/>Proceedings - 7Th International Conference On Machine +<br/>Learning And Applications, Icmla 2008, 2008, p. 16-22 +<br/>Issued Date +<br/>2008 +<br/>URL +<br/>http://hdl.handle.net/10722/61208 +<br/>Rights +<br/>This work is licensed under a Creative Commons Attribution- +<br/>NonCommercial-NoDerivatives 4.0 International License.; +<br/>International Conference on Machine Learning and Applications +<br/>Proceedings. Copyright © IEEE.; ©2008 IEEE. Personal use of +<br/>this material is permitted. However, permission to +<br/>reprint/republish this material for advertising or promotional +<br/>purposes or for creating new collective works for resale or +<br/>redistribution to servers or lists, or to reuse any copyrighted +<br/>component of this work in other works must be obtained from +<br/>the IEEE. +</td><td></td><td></td></tr><tr><td>f35a493afa78a671b9d2392c69642dcc3dd2cdc2</td><td>Automatic Attribute Discovery with Neural <br/>Activations <br/><b>University of North Carolina at Chapel Hill, USA</b><br/>2 NTT Media Intelligence Laboratories, Japan -<br/><b>Tohoku University, Japan</b></td><td>('3302783', 'Sirion Vittayakorn', 'sirion vittayakorn')<br/>('1706592', 'Takayuki Umeda', 'takayuki umeda')<br/>('2023568', 'Kazuhiko Murasaki', 'kazuhiko murasaki')<br/>('1745497', 'Kyoko Sudo', 'kyoko sudo')<br/>('1718872', 'Takayuki Okatani', 'takayuki okatani')<br/>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')</td><td></td></tr><tr><td>ebedc841a2c1b3a9ab7357de833101648281ff0e</td><td></td><td></td><td></td></tr><tr><td>eb526174fa071345ff7b1fad1fad240cd943a6d7</td><td>Deeply Vulnerable – A Study of the Robustness of Face Recognition to +<br/><b>Tohoku University, Japan</b></td><td>('3302783', 'Sirion Vittayakorn', 'sirion vittayakorn')<br/>('1706592', 'Takayuki Umeda', 'takayuki umeda')<br/>('2023568', 'Kazuhiko Murasaki', 'kazuhiko murasaki')<br/>('1745497', 'Kyoko Sudo', 'kyoko sudo')<br/>('1718872', 'Takayuki Okatani', 'takayuki okatani')<br/>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')</td><td></td></tr><tr><td>f3b7938de5f178e25a3cf477107c76286c0ad691</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, MARCH 2017 +<br/>Object Detection with Deep Learning: A Review +</td><td>('33698309', 'Zhong-Qiu Zhao', 'zhong-qiu zhao')<br/>('36659418', 'Peng Zheng', 'peng zheng')<br/>('51132438', 'Shou-tao Xu', 'shou-tao xu')<br/>('1748808', 'Xindong Wu', 'xindong wu')</td><td></td></tr><tr><td>ebedc841a2c1b3a9ab7357de833101648281ff0e</td><td></td><td></td><td></td></tr><tr><td>eb526174fa071345ff7b1fad1fad240cd943a6d7</td><td>Deeply Vulnerable – A Study of the Robustness of Face Recognition to <br/>Presentation Attacks -</td><td>('1990628', 'Amir Mohammadi', 'amir mohammadi')<br/>('1952348', 'Sushil Bhattacharjee', 'sushil bhattacharjee')</td><td></td></tr><tr><td>eb6ee56e085ebf473da990d032a4249437a3e462</td><td>Age/Gender Classification with Whole-Component +</td><td>('1990628', 'Amir Mohammadi', 'amir mohammadi')<br/>('1952348', 'Sushil Bhattacharjee', 'sushil bhattacharjee')</td><td></td></tr><tr><td>eb100638ed73b82e1cce8475bb8e180cb22a09a2</td><td>Temporal Action Detection with Structured Segment Networks +<br/><b>The Chinese University of Hong Kong</b><br/>2Computer Vision Laboratory, ETH Zurich, Switzerland +</td><td>('47827548', 'Yue Zhao', 'yue zhao')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('2765994', 'Zhirong Wu', 'zhirong wu')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')<br/>('1807606', 'Dahua Lin', 'dahua lin')</td><td></td></tr><tr><td>eb6ee56e085ebf473da990d032a4249437a3e462</td><td>Age/Gender Classification with Whole-Component <br/>Convolutional Neural Networks (WC-CNN) <br/><b>University of Southern California, Los Angeles, CA 90089, USA</b></td><td>('39004239', 'Chun-Ting Huang', 'chun-ting huang')<br/>('7022231', 'Yueru Chen', 'yueru chen')<br/>('35521292', 'Ruiyuan Lin', 'ruiyuan lin')<br/>('9363144', 'C.-C. Jay Kuo', 'c.-c. jay kuo')</td><td>E-mail: {chuntinh, yueruche, ruiyuanl}@usc.edu, cckuo@sipi.usc.edu +</td></tr><tr><td>eb8519cec0d7a781923f68fdca0891713cb81163</td><td>Temporal Non-Volume Preserving Approach to Facial Age-Progression and +<br/>Age-Invariant Face Recognition +<br/><b>Computer Science and Software Engineering, Concordia University, Montr eal, Qu ebec, Canada</b><br/>2 CyLab Biometrics Center and the Department of Electrical and Computer Engineering, +<br/><b>Carnegie Mellon University, Pittsburgh, PA, USA</b></td><td>('1876581', 'Chi Nhan Duong', 'chi nhan duong')<br/>('2687827', 'Kha Gia Quach', 'kha gia quach')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('6131978', 'T. Hoang Ngan Le', 't. hoang ngan le')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td>{chinhand, kquach, kluu, thihoanl}@andrew.cmu.edu, msavvid@ri.cmu.edu </td></tr><tr><td>ebb1c29145d31c4afa3c9be7f023155832776cd3</td><td>CASME II: An Improved Spontaneous Micro-Expression <br/>Database and the Baseline Evaluation -<br/><b>State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China, 2 University of Chinese Academy of Sciences</b><br/><b>Beijing, China, 3 Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland, 4 TNList, Department of</b><br/><b>Computer Science and Technology, Tsinghua University, Beijing, China</b></td><td>('9185305', 'Wen-Jing Yan', 'wen-jing yan')<br/>('39522870', 'Xiaobai Li', 'xiaobai li')<br/>('2819642', 'Su-Jing Wang', 'su-jing wang')<br/>('1757287', 'Guoying Zhao', 'guoying zhao')<br/>('1715826', 'Yong-Jin Liu', 'yong-jin liu')<br/>('1838009', 'Yu-Hsin Chen', 'yu-hsin chen')<br/>('1684007', 'Xiaolan Fu', 'xiaolan fu')</td><td></td></tr><tr><td>eb9312458f84a366e98bd0a2265747aaed40b1a6</td><td>1-4244-1437-7/07/$20.00 ©2007 IEEE +<br/><b>State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China, 2 University of Chinese Academy of Sciences</b><br/><b>Beijing, China, 3 Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland, 4 TNList, Department of</b><br/><b>Computer Science and Technology, Tsinghua University, Beijing, China</b></td><td>('9185305', 'Wen-Jing Yan', 'wen-jing yan')<br/>('39522870', 'Xiaobai Li', 'xiaobai li')<br/>('2819642', 'Su-Jing Wang', 'su-jing wang')<br/>('1757287', 'Guoying Zhao', 'guoying zhao')<br/>('1715826', 'Yong-Jin Liu', 'yong-jin liu')<br/>('1838009', 'Yu-Hsin Chen', 'yu-hsin chen')<br/>('1684007', 'Xiaolan Fu', 'xiaolan fu')</td><td></td></tr><tr><td>eb566490cd1aa9338831de8161c6659984e923fd</td><td>From Lifestyle Vlogs to Everyday Interactions +<br/>EECS Department, UC Berkeley +</td><td>('1786435', 'David F. Fouhey', 'david f. fouhey')<br/>('1763086', 'Alexei A. Efros', 'alexei a. efros')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td></td></tr><tr><td>eb9312458f84a366e98bd0a2265747aaed40b1a6</td><td>1-4244-1437-7/07/$20.00 ©2007 IEEE <br/>IV - 473 <br/>ICIP 2007 </td><td></td><td></td></tr><tr><td>eb716dd3dbd0f04e6d89f1703b9975cad62ffb09</td><td>Copyright <br/>by <br/>2012 -</td><td>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td></td></tr><tr><td>ebabd1f7bc0274fec88a3dabaf115d3e226f198f</td><td>Driver drowsiness detection system based on feature +</td><td>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td></td></tr><tr><td>eb4d2ec77fae67141f6cf74b3ed773997c2c0cf6</td><td>Int. J. Information Technology and Management, Vol. 11, Nos. 1/2, 2012 +<br/>35 +<br/>A new soft biometric approach for keystroke +<br/>dynamics based on gender recognition +<br/><b>GREYC Research Lab</b><br/>ENSICAEN – Université de Caen Basse Normandie – CNRS, +<br/>14000 Caen, France +<br/>Fax: +33-231538110 +<br/>*Corresponding author +</td><td>('2615638', 'Romain Giot', 'romain giot')<br/>('1793765', 'Christophe Rosenberger', 'christophe rosenberger')</td><td>E-mail: romain.giot@ensicaen.fr +<br/>E-mail: christophe.rosenberger@ensicaen.fr +</td></tr><tr><td>ebb7cc67df6d90f1c88817b20e7a3baad5dc29b9</td><td>Journal of Computational Mathematics +<br/>Vol.xx, No.x, 200x, 1–25. +<br/>http://www.global-sci.org/jcm +<br/>doi:?? +<br/>Fast algorithms for Higher-order Singular Value Decomposition +<br/>from incomplete data* +<br/><b>University of Alabama, Tuscaloosa, AL</b></td><td>('40507939', 'Yangyang Xu', 'yangyang xu')</td><td>Email: yangyang.xu@ua.edu +</td></tr><tr><td>ebabd1f7bc0274fec88a3dabaf115d3e226f198f</td><td>Driver drowsiness detection system based on feature <br/>representation learning using various deep networks <br/>School of Electrical Engineering, KAIST, <br/>Guseong-dong, Yuseong-gu, Dajeon, Rep. of Korea </td><td>('1989730', 'Sanghyuk Park', 'sanghyuk park')<br/>('1773194', 'Fei Pan', 'fei pan')<br/>('3315036', 'Sunghun Kang', 'sunghun kang')</td><td>{shine0624, feipan, sunghun.kang, cd yoo}@kaist.ac.kr -</td></tr><tr><td>ebb9d53668205c5797045ba130df18842e3eadef</td><td></td><td></td><td></td></tr><tr><td>eb7b387a3a006609b89ca5ed0e6b3a1d5ecb5e5a</td><td>Facial Expression Recognition using Neural +</td></tr><tr><td>eb70c38a350d13ea6b54dc9ebae0b64171d813c9</td><td>On Graph-Structured Discrete +<br/>Labelling Problems in Computer +<br/>Vision: Learning, Inference and +<br/>Applications +<br/>Submitted in partial fulfillment of the requirements for +<br/>the degree of +<br/>Doctor of Philosophy +<br/>in +<br/>Electrical and Computer Engineering +<br/><b>M.S., Electrical and Computer Engineering, Carnegie Mellon University</b><br/><b>B.Tech., Electronics Engineering, Institute of Technology, Banaras Hindu University</b><br/><b>Carnegie Mellon University</b><br/>August, 2010 +</td><td>('1746610', 'Dhruv Batra', 'dhruv batra')</td><td></td></tr><tr><td>ebb9d53668205c5797045ba130df18842e3eadef</td><td></td><td></td><td></td></tr><tr><td>eb027969f9310e0ae941e2adee2d42cdf07d938c</td><td>VGGFace2: A dataset for recognising faces across pose and age +<br/><b>Visual Geometry Group, University of Oxford</b></td><td>('46632720', 'Qiong Cao', 'qiong cao')<br/>('46980108', 'Li Shen', 'li shen')<br/>('10096695', 'Weidi Xie', 'weidi xie')<br/>('3188342', 'Omkar M. Parkhi', 'omkar m. parkhi')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{qiong,lishen,weidi,omkar,az}@robots.ox.ac.uk +</td></tr><tr><td>eb48a58b873295d719827e746d51b110f5716d6c</td><td>Face Alignment Using K-cluster Regression Forests +<br/>With Weighted Splitting +</td><td>('2393538', 'Marek Kowalski', 'marek kowalski')<br/>('1930272', 'Jacek Naruniec', 'jacek naruniec')</td><td></td></tr><tr><td>eb7b387a3a006609b89ca5ed0e6b3a1d5ecb5e5a</td><td>Facial Expression Recognition using Neural <br/>Network <br/><b>National Cheng Kung University</b><br/>Tainan, Taiwan, R.O.C. <br/> @@ -11126,16 +13695,50 @@ <br/>Submitted for the degree of Doctor of Philosophy <br/>Department of Computer Science <br/><b>The University of York</b><br/>June, 2011 -</td><td>('37519514', 'Ankur Patel', 'ankur patel')</td><td></td></tr><tr><td>c7e4c7be0d37013de07b6d829a3bf73e1b95ad4e</td><td>The International Journal of Multimedia & Its Applications (IJMA) Vol.5, No.5, October 2013 +</td><td>('37519514', 'Ankur Patel', 'ankur patel')</td><td></td></tr><tr><td>c7c53d75f6e963b403057d8ba5952e4974a779ad</td><td><b>Purdue University</b><br/>Purdue e-Pubs +<br/>Open Access Theses +<br/>8-2016 +<br/>Theses and Dissertations +<br/>Aging effects in automated face recognition +<br/><b>Purdue University</b><br/>Follow this and additional works at: http://docs.lib.purdue.edu/open_access_theses +<br/>Recommended Citation +<br/>Agamez, Miguel Cedeno, "Aging effects in automated face recognition" (2016). Open Access Theses. 930. +<br/>http://docs.lib.purdue.edu/open_access_theses/930 +<br/>additional information. +</td><td></td><td>This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact epubs@purdue.edu for +</td></tr><tr><td>c79cf7f61441195404472102114bcf079a72138a</td><td>Pose-Invariant 2D Face Recognition by Matching +<br/>Using Graphical Models +<br/>Submitted for the Degree of +<br/>Doctor of Philosophy +<br/>from the +<br/><b>University of Surrey</b><br/>Center for Vision, Speech and Signal Processing +<br/>Faculty of Engineering and Physical Sciences +<br/><b>University of Surrey</b><br/>Guildford, Surrey GU2 7XH, U.K. +<br/>September 2010 +</td><td>('1690611', 'Shervin Rahimzadeh Arashloo', 'shervin rahimzadeh arashloo')<br/>('1690611', 'Shervin Rahimzadeh Arashloo', 'shervin rahimzadeh arashloo')</td><td></td></tr><tr><td>c73dd452c20460f40becb1fd8146239c88347d87</td><td>Manifold Constrained Low-Rank Decomposition +<br/>1State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang, China +<br/><b>Center for Research in Computer Vision (CRCV), University of Central Florida (UCF</b><br/><b>School of Automation Science and Electrical Engineering, Beihang University, Beijing, China</b><br/>4 Istituto Italiano di Tecnologia, Genova, Italy +</td><td>('9497155', 'Chen Chen', 'chen chen')<br/>('1740430', 'Baochang Zhang', 'baochang zhang')<br/>('1714730', 'Alessio Del Bue', 'alessio del bue')<br/>('1727204', 'Vittorio Murino', 'vittorio murino')</td><td>chenchen870713@gmail.com, alessio.delbue@iit.it, bczhang@buaa.edu.cn, vittorio.murino@iit.it ∗ +</td></tr><tr><td>c7e4c7be0d37013de07b6d829a3bf73e1b95ad4e</td><td>The International Journal of Multimedia & Its Applications (IJMA) Vol.5, No.5, October 2013 <br/>DYNEMO: A VIDEO DATABASE OF NATURAL FACIAL <br/>EXPRESSIONS OF EMOTIONS <br/>1LIP, Univ. Grenoble Alpes, BP 47 - 38040 Grenoble Cedex 9, France <br/>2LIG, Univ. Grenoble Alpes, BP 53 - 38041 Grenoble Cedex 9, France -</td><td>('3209946', 'Anna Tcherkassof', 'anna tcherkassof')<br/>('20944713', 'Damien Dupré', 'damien dupré')<br/>('2357225', 'Brigitte Meillon', 'brigitte meillon')<br/>('2872246', 'Nadine Mandran', 'nadine mandran')<br/>('1870899', 'Michel Dubois', 'michel dubois')<br/>('1828394', 'Jean-Michel Adam', 'jean-michel adam')</td><td></td></tr><tr><td>c74aba9a096379b3dbe1ff95e7af5db45c0fd680</td><td>Neuro-Fuzzy Analysis of Facial Action Units +</td><td>('3209946', 'Anna Tcherkassof', 'anna tcherkassof')<br/>('20944713', 'Damien Dupré', 'damien dupré')<br/>('2357225', 'Brigitte Meillon', 'brigitte meillon')<br/>('2872246', 'Nadine Mandran', 'nadine mandran')<br/>('1870899', 'Michel Dubois', 'michel dubois')<br/>('1828394', 'Jean-Michel Adam', 'jean-michel adam')</td><td></td></tr><tr><td>c72e6992f44ce75a40f44be4365dc4f264735cfb</td><td>Story Understanding in Video +<br/>Advertisements +<br/>Department of Computer Science +<br/><b>University of Pittsburgh</b><br/>Pennsylvania, United States +</td><td>('9085797', 'Keren Ye', 'keren ye')<br/>('51150048', 'Kyle Buettner', 'kyle buettner')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')<br/>('9085797', 'Keren Ye', 'keren ye')<br/>('51150048', 'Kyle Buettner', 'kyle buettner')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td>yekeren@cs.pitt.edu +<br/>buettnerk@pitt.edu +<br/>kovashka@cs.pitt.edu +</td></tr><tr><td>c74aba9a096379b3dbe1ff95e7af5db45c0fd680</td><td>Neuro-Fuzzy Analysis of Facial Action Units <br/>and Expressions <br/>Digital Signal Processing Lab, Department of Computer Engineering <br/><b>Sharif University of Technology</b><br/>Tehran, Iran, Tel: +98 21 6616 4632 </td><td>('1736464', 'Mahmoud Khademi', 'mahmoud khademi')<br/>('2936650', 'Mohammad Taghi Manzuri', 'mohammad taghi manzuri')<br/>('1702826', 'Mohammad Hadi Kiapour', 'mohammad hadi kiapour')</td><td>khademi@ce.sharif.edu, manzuri@sharif.edu, kiapour@ee.sharif.edu +</td></tr><tr><td>c7de0c85432ad17a284b5b97c4f36c23f506d9d1</td><td>INTERSPEECH 2011 +<br/>RANSAC-based Training Data Selection for Speaker State Recognition +<br/><b>Multimedia, Vision and Graphics Laboratory, Koc University, Istanbul, Turkey</b><br/><b>Bahc es ehir University, Istanbul, Turkey</b><br/><b>Ozye gin University, Istanbul, Turkey</b></td><td>('1777185', 'Elif Bozkurt', 'elif bozkurt')<br/>('1749677', 'Engin Erzin', 'engin erzin')</td><td>ebozkurt, eerzin@ku.edu.tr, cigdem.eroglu@bahcesehir.edu.tr, tanju.erdem@ozyegin.edu.tr </td></tr><tr><td>c7c5f0fe1fcaf3787c7f78f7dc62f3497dcfdf3c</td><td>THE IMPACT OF PRODUCT PHOTO ON ONLINE CONSUMER <br/>PURCHASE INTENTION: AN IMAGE-PROCESSING ENABLED <br/>EMPIRICAL STUDY @@ -11152,13 +13755,25 @@ <br/>By <br/>Crefeda Faviola Rodrigues <br/>School of Computer Science -</td><td></td><td></td></tr><tr><td>c758b9c82b603904ba8806e6193c5fefa57e9613</td><td>Heterogeneous Face Recognition with CNNs +</td><td></td><td></td></tr><tr><td>c71217b2b111a51a31cf1107c71d250348d1ff68</td><td>One Network to Solve Them All — Solving Linear Inverse Problems +<br/>using Deep Projection Models +<br/><b>Carnegie Mellon University, Pittsburgh, PA</b></td><td>('2088535', 'Chun-Liang Li', 'chun-liang li')<br/>('1783087', 'B. V. K. Vijaya Kumar', 'b. v. k. vijaya kumar')<br/>('1745861', 'Aswin C. Sankaranarayanan', 'aswin c. sankaranarayanan')</td><td></td></tr><tr><td>c758b9c82b603904ba8806e6193c5fefa57e9613</td><td>Heterogeneous Face Recognition with CNNs <br/>INRIA Grenoble, Laboratoire Jean Kuntzmann </td><td>('2143851', 'Shreyas Saxena', 'shreyas saxena')<br/>('34602236', 'Jakob Verbeek', 'jakob verbeek')</td><td>{firstname.lastname}@inria.fr </td></tr><tr><td>c7c03324833ba262eeaada0349afa1b5990c1ea7</td><td>A Wearable Face Recognition System on Google <br/>Glass for Assisting Social Interactions <br/><b>Institute for Infocomm Research, Singapore</b></td><td>('1709001', 'Bappaditya Mandal', 'bappaditya mandal')<br/>('35718875', 'Liyuan Li', 'liyuan li')<br/>('1694051', 'Cheston Tan', 'cheston tan')</td><td>Email address: bmandal@i2r.a-star.edu.sg (∗Contact author: Bappaditya Mandal); <br/>{scchia, lyli, vijay, cheston-tan, joohwee}@i2r.a-star.edu.sg +</td></tr><tr><td>c76f64e87f88475069f7707616ad9df1719a6099</td><td>T-RECS: Training for Rate-Invariant +<br/>Embeddings by Controlling Speed for Action +<br/>Recognition +<br/><b>University of Michigan</b></td><td>('31646172', 'Madan Ravi Ganesh', 'madan ravi ganesh')<br/>('24337238', 'Eric Hofesmann', 'eric hofesmann')<br/>('40893359', 'Byungsu Min', 'byungsu min')<br/>('40893002', 'Nadha Gafoor', 'nadha gafoor')<br/>('3587688', 'Jason J. Corso', 'jason j. corso')</td><td></td></tr><tr><td>c7f0c0636d27a1d45b8fcef37e545b902195d937</td><td>Towards Around-Device Interaction using Corneal Imaging +<br/><b>Coburg University</b><br/><b>Coburg University</b></td><td>('49770541', 'Daniel Schneider', 'daniel schneider')<br/>('2708269', 'Jens Grubert', 'jens grubert')</td><td>daniel.schneider@hs-coburg.de +<br/>jg@jensgrubert.de +</td></tr><tr><td>c7c8d150ece08b12e3abdb6224000c07a6ce7d47</td><td>DeMeshNet: Blind Face Inpainting for Deep MeshFace Verification +<br/>National Laboratory of Pattern Recognition, CASIA +<br/>Center for Research on Intelligent Perception and Computing, CASIA +</td><td>('50202300', 'Shu Zhang', 'shu zhang')</td><td>{shu.zhang,rhe,tnt}@nlpr.ia.ac.cn </td></tr><tr><td>c78fdd080df01fff400a32fb4cc932621926021f</td><td>Robust Automatic Facial Expression Detection <br/>Method <br/><b>Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan</b><br/><b>Institute for Pattern Recognition and Artificial Intelligence/ Huazhong University of Science and Technology, Wuhan</b><br/>China @@ -11176,6 +13791,8 @@ </td><td>('38746097', 'Xuan Zou', 'xuan zou')<br/>('39685698', 'Wenwu Wang', 'wenwu wang')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>xuan.zou@surrey.ac.uk <br/>w.wang@surrey.ac.uk <br/>j.kittler@surrey.ac.uk +</td></tr><tr><td>c75e6ce54caf17b2780b4b53f8d29086b391e839</td><td>ExpNet: Landmark-Free, Deep, 3D Facial Expressions +<br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b></td><td>('1752756', 'Feng-Ju Chang', 'feng-ju chang')<br/>('46634688', 'Anh Tuan Tran', 'anh tuan tran')<br/>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')</td><td>{fengjuch,anhttran,iacopoma,nevatia,medioni}@usc.edu, hassner@openu.ac.il </td></tr><tr><td>c0723e0e154a33faa6ff959d084aebf07770ffaf</td><td>Interpolation Between Eigenspaces Using <br/>Rotation in Multiple Dimensions <br/><b>Graduate School of Information Science, Nagoya University, Japan</b><br/>2 No Japan Society for the Promotion of Science @@ -11186,10 +13803,26 @@ <br/>I-vector Speaker Recognition System <br/><b>School of Computer Information Engineering, Jiangxi Normal University, Nanchang, China</b></td><td>('3308432', 'Zhenchun Lei', 'zhenchun lei')<br/>('2947033', 'Yanhong Wan', 'yanhong wan')<br/>('1853437', 'Jian Luo', 'jian luo')<br/>('2956877', 'Yingen Yang', 'yingen yang')</td><td>zhenchun.lei@hotmail.com, wyanhhappy@126.com, <br/>luo.jian@hotmail.com, ygyang@jxnu.edu.cn -</td></tr><tr><td>c043f8924717a3023a869777d4c9bee33e607fb5</td><td>Emotion Separation Is Completed Early and It Depends +</td></tr><tr><td>c038beaa228aeec174e5bd52460f0de75e9cccbe</td><td>Temporal Segment Networks for Action +<br/>Recognition in Videos +</td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('48708388', 'Zhe Wang', 'zhe wang')<br/>('40612284', 'Yu Qiao', 'yu qiao')<br/>('1807606', 'Dahua Lin', 'dahua lin')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td></td></tr><tr><td>c043f8924717a3023a869777d4c9bee33e607fb5</td><td>Emotion Separation Is Completed Early and It Depends <br/>on Visual Field Presentation <br/><b>Lab for Human Brain Dynamics, RIKEN Brain Science Institute, Wakoshi, Saitama, Japan, 2 Lab for Human Brain Dynamics, AAI Scientific Cultural Services Ltd., Nicosia</b><br/>Cyprus -</td><td>('2259342', 'Lichan Liu', 'lichan liu')<br/>('2348276', 'Andreas A. Ioannides', 'andreas a. ioannides')</td><td></td></tr><tr><td>c03e01717b2d93f04cce9b5fd2dcfd1143bcc180</td><td>Locality-constrained Active Appearance Model +</td><td>('2259342', 'Lichan Liu', 'lichan liu')<br/>('2348276', 'Andreas A. Ioannides', 'andreas a. ioannides')</td><td></td></tr><tr><td>c05a7c72e679745deab9c9d7d481f7b5b9b36bdd</td><td>NPS-CS-11-005 +<br/> +<br/> +<br/>NAVAL +<br/>POSTGRADUATE +<br/>SCHOOL +<br/>MONTEREY, CALIFORNIA +<br/>by +<br/>BIOMETRIC CHALLENGES FOR FUTURE DEPLOYMENTS: +<br/>A STUDY OF THE IMPACT OF GEOGRAPHY, CLIMATE, CULTURE, +<br/> AND SOCIAL CONDITIONS ON THE EFFECTIVE +<br/>COLLECTION OF BIOMETRICS +<br/>April 2011 +<br/>Approved for public release; distribution is unlimited +</td><td>('3337733', 'Paul C. Clark', 'paul c. clark')</td><td></td></tr><tr><td>c03e01717b2d93f04cce9b5fd2dcfd1143bcc180</td><td>Locality-constrained Active Appearance Model <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences <br/><b>CAS), Institute of Computing Technology, CAS, Beijing 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b></td><td>('1874505', 'Xiaowei Zhao', 'xiaowei zhao')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1695600', 'Xiujuan Chai', 'xiujuan chai')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>mathzxw2002@gmail.com,{sgshan,chaixiujuan,xlchen}@ict.ac.cn </td></tr><tr><td>c0ff7dc0d575658bf402719c12b676a34271dfcd</td><td>A New Incremental Optimal Feature Extraction @@ -11226,7 +13859,10 @@ <br/>because a higher resolution image will require larger filters and deeper networks which is turn hard to <br/>train [3]. So it is not clear whether the low resolution will cause challenge for fine-grained <br/>classification task. Last but not the least, there is not a large training database like PASCAL, MNIST -</td><td>('2355840', 'Chenyu Wang', 'chenyu wang')</td><td></td></tr><tr><td>c035c193eed5d72c7f187f0bc880a17d217dada0</td><td>Local Gradient Gabor Pattern (LGGP) with Applications in +</td><td>('2355840', 'Chenyu Wang', 'chenyu wang')</td><td></td></tr><tr><td>c0c8d720658374cc1ffd6116554a615e846c74b5</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>Modeling Multimodal Clues in a Hybrid Deep +<br/>Learning Framework for Video Classification +</td><td>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('3099139', 'Zuxuan Wu', 'zuxuan wu')<br/>('8053308', 'Jinhui Tang', 'jinhui tang')<br/>('3233021', 'Zechao Li', 'zechao li')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td></td></tr><tr><td>c035c193eed5d72c7f187f0bc880a17d217dada0</td><td>Local Gradient Gabor Pattern (LGGP) with Applications in <br/>Face Recognition, Cross-spectral Matching and Soft <br/>Biometrics <br/><b>West Virginia University</b><br/><b>Michigan State University</b><br/>Morgantown, WV, USA @@ -11249,6 +13885,9 @@ </td><td>('7652095', 'Young Bin Kim', 'young bin kim')<br/>('40267433', 'Shin Jin Kang', 'shin jin kang')<br/>('4972813', 'Sang Hyeok Lee', 'sang hyeok lee')<br/>('5702793', 'Jang Young Jung', 'jang young jung')<br/>('3000093', 'Hyeong Ryeol Kam', 'hyeong ryeol kam')<br/>('2013790', 'Jung Lee', 'jung lee')<br/>('2467280', 'Young Sun Kim', 'young sun kim')<br/>('3103240', 'Joonsoo Lee', 'joonsoo lee')<br/>('22232963', 'Chang Hun Kim', 'chang hun kim')</td><td></td></tr><tr><td>c0ca6b992cbe46ea3003f4e9b48f4ef57e5fb774</td><td>A Two-Layer Representation For Large-Scale Action Recognition <br/><b>Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University</b><br/>2Shanghai Key Lab of Digital Media Processing and Transmission, 3Microsoft Research Asia <br/><b>University of California, San Diego</b></td><td>('1701941', 'Jun Zhu', 'jun zhu')<br/>('2450889', 'Baoyuan Wang', 'baoyuan wang')<br/>('1795291', 'Xiaokang Yang', 'xiaokang yang')<br/>('38790729', 'Wenjun Zhang', 'wenjun zhang')<br/>('1736745', 'Zhuowen Tu', 'zhuowen tu')</td><td>{zhujun.sjtu,zhuowen.tu}@gmail.com, baoyuanw@microsoft.com, {xkyang,zhangwenjun}@sjtu.edu.cn +</td></tr><tr><td>c00df53bd46f78ae925c5768d46080159d4ef87d</td><td>Learning Bag-of-Features Pooling for Deep Convolutional Neural Networks +<br/><b>Aristotle University of Thessaloniki</b><br/>Thessaloniki, Greece +</td><td>('3200630', 'Nikolaos Passalis', 'nikolaos passalis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')</td><td>passalis@csd.auth.gr, tefas@aiia.csd.auth.gr </td></tr><tr><td>c0d5c3aab87d6e8dd3241db1d931470c15b9e39d</td><td></td><td></td><td></td></tr><tr><td>c05441dd1bc418fb912a6fafa84c0659a6850bf0</td><td>Received on 16th July 2014 <br/>Revised on 11th September 2014 <br/>Accepted on 23rd September 2014 @@ -11335,11 +13974,39 @@ <br/>Source: Machine Learning, Book edited by: Abdelhamid Mellouk and Abdennacer Chebira, <br/> ISBN 978-3-902613-56-1, pp. 450, February 2009, I-Tech, Vienna, Austria <br/>www.intechopen.com -</td><td>('1932760', 'Masaki Ishii', 'masaki ishii')<br/>('2052920', 'Kazuhito Sato', 'kazuhito sato')<br/>('1738333', 'Hirokazu Madokoro', 'hirokazu madokoro')<br/>('21063785', 'Makoto Nishida', 'makoto nishida')</td><td></td></tr><tr><td>ee7093e91466b81d13f4d6933bcee48e4ee63a16</td><td>Discovering Person Identity via +</td><td>('1932760', 'Masaki Ishii', 'masaki ishii')<br/>('2052920', 'Kazuhito Sato', 'kazuhito sato')<br/>('1738333', 'Hirokazu Madokoro', 'hirokazu madokoro')<br/>('21063785', 'Makoto Nishida', 'makoto nishida')</td><td></td></tr><tr><td>ee815f60dc4a090fa9fcfba0135f4707af21420d</td><td>EAC-Net: A Region-based Deep Enhancing and Cropping Approach for +<br/>Facial Action Unit Detection +<br/><b>Grove School of Engineering, CUNY City College, NY, USA</b><br/>2 Department of Computer Science, CUNY Graduate Center, NY, USA +<br/><b>Engineering and Applied Science, SUNY Binghamton University, NY, USA</b></td><td>('48625314', 'Wei Li', 'wei li')</td><td></td></tr><tr><td>eed7920682789a9afd0de4efd726cd9a706940c8</td><td>Computers to Help with Conversations: +<br/>Affective Framework to Enhance Human Nonverbal Skills +<br/>by +<br/>Mohammed Ehsan Hoque +<br/><b>B.S., Pennsylvania State University</b><br/><b>M.S., University of Memphis</b><br/>Submitted to the Program in Media Arts and Sciences, +<br/>School of Architecture and Planning, +<br/>In partial fulfilment of the requirements for the degree of +<br/>DOCTOR OF PHILOSOPHY +<br/>at the +<br/><b>MASSACHUSETTS INSTITUTE OF TECHNOLOGY</b><br/>September 2013 +<br/><b>Massachusetts Institute of Technology 2013. All rights reserved</b><br/>Author +<br/>Certified by +<br/>Accepted by +<br/> Program in Media Arts and Sciences +<br/>August 15, 2013 +<br/> Rosalind W. Picard +<br/> Professor of Media Arts and Sciences +<br/> Program in Media Arts and Sciences, MIT +<br/> Thesis supervisor +<br/>Pattie Maes +<br/>Associate Academic Head +<br/>Program in Media Arts and Sciences, MIT +</td><td></td><td></td></tr><tr><td>ee7093e91466b81d13f4d6933bcee48e4ee63a16</td><td>Discovering Person Identity via <br/>Large-Scale Observations <br/><b>Interactive and Digital Media Institute, National University of Singapore, SG</b><br/><b>School of Computing, National University of Singapore, SG</b></td><td>('3026404', 'Yongkang Wong', 'yongkang wong')<br/>('1986874', 'Lekha Chaisorn', 'lekha chaisorn')<br/>('1744045', 'Mohan S. Kankanhalli', 'mohan s. kankanhalli')</td><td></td></tr><tr><td>ee461d060da58d6053d2f4988b54eff8655ecede</td><td></td><td></td><td></td></tr><tr><td>eefb8768f60c17d76fe156b55b8a00555eb40f4d</td><td>Subspace Scores for Feature Selection in Computer Vision </td><td>('2032038', 'Cameron Musco', 'cameron musco')<br/>('2767340', 'Christopher Musco', 'christopher musco')</td><td>cnmusco@mit.edu <br/>cpmusco@mit.edu +</td></tr><tr><td>ee463f1f72a7e007bae274d2d42cd2e5d817e751</td><td>Automatically Extracting Qualia Relations for the Rich Event Ontology +<br/><b>University of Colorado Boulder, 2U.S. Army Research Lab</b></td><td>('51203051', 'Ghazaleh Kazeminejad', 'ghazaleh kazeminejad')<br/>('3202888', 'Claire Bonial', 'claire bonial')<br/>('1783500', 'Susan Windisch Brown', 'susan windisch brown')<br/>('1728285', 'Martha Palmer', 'martha palmer')</td><td>{ghazaleh.kazeminejad, susan.brown, martha.palmer}@colorado.edu +<br/>claire.n.bonial.civ@mail.mil </td></tr><tr><td>eed1dd2a5959647896e73d129272cb7c3a2e145c</td><td></td><td></td><td></td></tr><tr><td>ee92d36d72075048a7c8b2af5cc1720c7bace6dd</td><td>FACE RECOGNITION USING MIXTURES OF PRINCIPAL COMPONENTS <br/>Video and Display Processing <br/>Philips Research USA @@ -11349,7 +14016,32 @@ <br/>of Oriented Gradients and Adaboost Classifier <br/>Electrical and Computer Engineering Department <br/><b>University of California, San Diego</b></td><td>('2812409', 'Kevan Yuen', 'kevan yuen')</td><td>kcyuen@eng.ucsd.edu -</td></tr><tr><td>c94b3a05f6f41d015d524169972ae8fd52871b67</td><td>The Fastest Deformable Part Model for Object Detection +</td></tr><tr><td>eee06d68497be8bf3a8aba4fde42a13aa090b301</td><td>CR-GAN: Learning Complete Representations for Multi-view Generation +<br/><b>Rutgers University</b><br/><b>University of North Carolina at Charlotte</b></td><td>('6812347', 'Yu Tian', 'yu tian')<br/>('4340744', 'Xi Peng', 'xi peng')<br/>('33860220', 'Long Zhao', 'long zhao')<br/>('1753384', 'Shaoting Zhang', 'shaoting zhang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>{yt219, px13, lz311, dnm}@cs.rutgers.edu, szhang16@uncc.edu +</td></tr><tr><td>eee2d2ac461f46734c8e674ae14ed87bbc8d45c6</td><td>Generalized Rank Pooling for Activity Recognition +<br/>1Australian Centre for Robotic Vision, 2Data61/CSIRO +<br/><b>The Australian National University, Canberra, Australia</b></td><td>('2691929', 'Anoop Cherian', 'anoop cherian')<br/>('1688071', 'Basura Fernando', 'basura fernando')<br/>('23911916', 'Mehrtash Harandi', 'mehrtash harandi')<br/>('49384847', 'Stephen Gould', 'stephen gould')</td><td>firstname.lastname@{anu.edu.au, data61.csiro.au} +</td></tr><tr><td>eed93d2e16b55142b3260d268c9e72099c53d5bc</td><td>ICFVR 2017: 3rd International Competition on Finger Vein Recognition +<br/><b>Chittagong University of Engineering and Technology</b><br/>∗ These authors contributed equally to this work +<br/><b>Peking University</b><br/>2Shenzhen Maidi Technology Co., LTD. +<br/>3TigerIT +</td><td>('46867002', 'Yi Zhang', 'yi zhang')<br/>('2560109', 'Houjun Huang', 'houjun huang')<br/>('38728899', 'Haifeng Zhang', 'haifeng zhang')<br/>('3142600', 'Liao Ni', 'liao ni')<br/>('47210488', 'Wei Xu', 'wei xu')<br/>('1694788', 'Nasir Uddin Ahmed', 'nasir uddin ahmed')<br/>('9336364', 'Md. Shakil Ahmed', 'md. shakil ahmed')<br/>('9372198', 'Yilun Jin', 'yilun jin')<br/>('23100665', 'Yingjie Chen', 'yingjie chen')<br/>('35273470', 'Jingxuan Wen', 'jingxuan wen')<br/>('39201759', 'Wenxin Li', 'wenxin li')</td><td></td></tr><tr><td>eedfb384a5e42511013b33104f4cd3149432bd9e</td><td>Multimodal Probabilistic Person +<br/>Tracking and Identification +<br/>in Smart Spaces +<br/>zur Erlangung des akademischen Grades eines +<br/>Doktors der Ingenieurwissenschaften +<br/>der Fakultät für Informatik +<br/>der Universität Fridericiana zu Karlsruhe (TH) +<br/>genehmigte +<br/>Dissertation +<br/>von +<br/>aus Karlsruhe +<br/>Tag der mündlichen Prüfung: 20.11.2009 +<br/>Erster Gutachter: +<br/>Zweiter Gutachter: +<br/>Prof. Dr. A. Waibel +<br/>Prof. Dr. R. Stiefelhagen +</td><td>('1701229', 'Keni Bernardin', 'keni bernardin')</td><td></td></tr><tr><td>c94b3a05f6f41d015d524169972ae8fd52871b67</td><td>The Fastest Deformable Part Model for Object Detection <br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition <br/><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>('1721677', 'Junjie Yan', 'junjie yan')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('39774417', 'Longyin Wen', 'longyin wen')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{jjyan,zlei,lywen,szli}@nlpr.ia.ac.cn </td></tr><tr><td>c9424d64b12a4abe0af201e7b641409e182babab</td><td>Article @@ -11363,14 +14055,23 @@ <br/>statistical-like moments <br/><b>Integrated Research Center, Universit`a Campus Bio-Medico di Roma</b><br/>Via Alvaro del Portillo, 00128 Roma, Italy </td><td>('1679260', 'Giulio Iannello', 'giulio iannello')<br/>('1720099', 'Paolo Soda', 'paolo soda')</td><td>{r.dambrosio, g.iannello, p.soda}@unicampus.it -</td></tr><tr><td>c903af0d69edacf8d1bff3bfd85b9470f6c4c243</td><td></td><td></td><td></td></tr><tr><td>c95cd36779fcbe45e3831ffcd3314e19c85defc5</td><td>FACE RECOGNITION USING MULTI-MODAL LOW-RANK DICTIONARY LEARNING +</td></tr><tr><td>c903af0d69edacf8d1bff3bfd85b9470f6c4c243</td><td></td><td></td><td></td></tr><tr><td>c97a5f2241cc6cd99ef0c4527ea507a50841f60b</td><td>Person Search in Videos with One Portrait +<br/>Through Visual and Temporal Links +<br/><b>CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong</b><br/><b>Tsinghua University</b><br/>3 SenseTime Research +</td><td>('39360892', 'Qingqiu Huang', 'qingqiu huang')<br/>('40584026', 'Wentao Liu', 'wentao liu')<br/>('1807606', 'Dahua Lin', 'dahua lin')</td><td>{hq016,dhlin}@ie.cuhk.edu.hk +<br/>liuwtwinter@gmail.com +</td></tr><tr><td>c95cd36779fcbe45e3831ffcd3314e19c85defc5</td><td>FACE RECOGNITION USING MULTI-MODAL LOW-RANK DICTIONARY LEARNING <br/><b>University of Alberta, Edmonton, Canada</b></td><td>('1807674', 'Homa Foroughi', 'homa foroughi')<br/>('2627414', 'Moein Shakeri', 'moein shakeri')<br/>('1772846', 'Nilanjan Ray', 'nilanjan ray')<br/>('1734058', 'Hong Zhang', 'hong zhang')</td><td></td></tr><tr><td>c9e955cb9709f16faeb0c840f4dae92eb875450a</td><td>Proposal of Novel Histogram Features <br/>for Face Detection <br/><b>Harbin Institute of Technology, School of Computer Science and Technology</b><br/>P.O.Box 1071, Harbin, Heilongjiang 150001, China <br/><b>Heilongjiang University, College of Computer Science and Technology, China</b></td><td>('2607285', 'Haijing Wang', 'haijing wang')<br/>('40426020', 'Peihua Li', 'peihua li')<br/>('1821107', 'Tianwen Zhang', 'tianwen zhang')</td><td>ninhaijing@yahoo.com <br/>peihualj@hotmail.com </td></tr><tr><td>c92bb26238f6e30196b0c4a737d8847e61cfb7d4</td><td>BEYOND CONTEXT: EXPLORING SEMANTIC SIMILARITY FOR TINY FACE DETECTION -<br/><b>School of Computer Science, Northwestern Polytechnical University, P.R.China</b><br/><b>Global Big Data Technologies Centre (GBDTC), University of Technology Sydney, Australia</b><br/><b>School of Data and Computer Science, Sun Yat-sen University, P.R.China</b></td><td>('24336288', 'Yue Xi', 'yue xi')<br/>('3104013', 'Jiangbin Zheng', 'jiangbin zheng')<br/>('1714410', 'Wenjing Jia', 'wenjing jia')<br/>('3031842', 'Hanhui Li', 'hanhui li')</td><td></td></tr><tr><td>c9f588d295437009994ddaabb64fd4e4c499b294</td><td>Predicting Professions through +<br/><b>School of Computer Science, Northwestern Polytechnical University, P.R.China</b><br/><b>Global Big Data Technologies Centre (GBDTC), University of Technology Sydney, Australia</b><br/><b>School of Data and Computer Science, Sun Yat-sen University, P.R.China</b></td><td>('24336288', 'Yue Xi', 'yue xi')<br/>('3104013', 'Jiangbin Zheng', 'jiangbin zheng')<br/>('1714410', 'Wenjing Jia', 'wenjing jia')<br/>('3031842', 'Hanhui Li', 'hanhui li')</td><td></td></tr><tr><td>c9bbd7828437e70cc3e6863b278aa56a7d545150</td><td>Unconstrained Fashion Landmark Detection via +<br/>Hierarchical Recurrent Transformer Networks +<br/><b>The Chinese University of Hong Kong</b><br/>2SenseTime Group Limited +</td><td>('1979911', 'Sijie Yan', 'sijie yan')<br/>('3243969', 'Ziwei Liu', 'ziwei liu')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1725421', 'Shi Qiu', 'shi qiu')</td><td>{ys016,lz013,pluo,xtang}@ie.cuhk.edu.hk,sqiu@sensetime.com,xgwang@ee.cuhk.edu.hk +</td></tr><tr><td>c9f588d295437009994ddaabb64fd4e4c499b294</td><td>Predicting Professions through <br/>Probabilistic Model under Social Context <br/><b>Northeastern University</b><br/>Boston, MA, 02115 </td><td>('2025056', 'Ming Shao', 'ming shao')<br/>('2897748', 'Liangyue Li', 'liangyue li')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td>mingshao@ccs.neu.edu, {liangyue, yunfu}@ece.neu.edu @@ -11384,7 +14085,21 @@ <br/>Department of Electrical Engineering <br/><b>National Chiao-Tung University</b><br/>Hsinchu, Taiwan, R.O.C </td><td>('4525043', 'Kuo-Yu Chiu', 'kuo-yu chiu')<br/>('1707677', 'Sheng-Fuu Lin', 'sheng-fuu lin')</td><td>Alvin_cgr@hotmail.com -</td></tr><tr><td>fc1e37fb16006b62848def92a51434fc74a2431a</td><td>DRAFT +</td></tr><tr><td>c98983592777952d1751103b4d397d3ace00852d</td><td>Face Synthesis from Facial Identity Features +<br/>Google Research +<br/>Google Research +<br/><b>University of Massachusetts Amherst</b><br/>Google Research +<br/>Google Research +<br/>CSAIL, MIT and Google Research +</td><td>('39578349', 'Forrester Cole', 'forrester cole')<br/>('8707513', 'Aaron Sarna', 'aaron sarna')<br/>('2636941', 'David Belanger', 'david belanger')<br/>('1707347', 'Dilip Krishnan', 'dilip krishnan')<br/>('2138834', 'Inbar Mosseri', 'inbar mosseri')<br/>('1768236', 'William T. Freeman', 'william t. freeman')</td><td>fcole@google.com +<br/>sarna@google.com +<br/>belanger@cs.umass.edu +<br/>dilipkay@google.com +<br/>inbarm@google.com +<br/>wfreeman@google.com +</td></tr><tr><td>c9367ed83156d4d682cefc59301b67f5460013e0</td><td>Geometry-Contrastive GAN for Facial Expression +<br/>Transfer +<br/><b>Institute of Software, Chinese Academy of Sciences</b></td><td>('35790820', 'Fengchun Qiao', 'fengchun qiao')<br/>('35996065', 'Zirui Jiao', 'zirui jiao')<br/>('3238696', 'Zhihao Li', 'zhihao li')<br/>('1804472', 'Hui Chen', 'hui chen')<br/>('7643981', 'Hongan Wang', 'hongan wang')</td><td></td></tr><tr><td>fc1e37fb16006b62848def92a51434fc74a2431a</td><td>DRAFT <br/>A Comprehensive Analysis of Deep Regression </td><td>('2793152', 'Pablo Mesejo', 'pablo mesejo')<br/>('1780201', 'Xavier Alameda-Pineda', 'xavier alameda-pineda')<br/>('1794229', 'Radu Horaud', 'radu horaud')</td><td></td></tr><tr><td>fc5bdb98ff97581d7c1e5eb2d24d3f10714aa192</td><td>Initialization Strategies of Spatio-Temporal <br/>Convolutional Neural Networks @@ -11398,7 +14113,14 @@ <br/>Editor: Donald Geman </td><td>('5692650', 'Chao-Chun Liu', 'chao-chun liu')<br/>('1726138', 'Dao-Qing Dai', 'dao-qing dai')<br/>('1718530', 'Hong Yan', 'hong yan')</td><td>STSDDQ@MAIL.SYSU.EDU.CN <br/>H.YAN@CITYU.EDU.HK -</td></tr><tr><td>fc516a492cf09aaf1d319c8ff112c77cfb55a0e5</td><td></td><td></td><td></td></tr><tr><td>fcbec158e6a4ace3d4311b26195482b8388f0ee9</td><td>Face Recognition from Still Images and Videos +</td></tr><tr><td>fc516a492cf09aaf1d319c8ff112c77cfb55a0e5</td><td></td><td></td><td></td></tr><tr><td>fc0f5859a111fb17e6dcf6ba63dd7b751721ca61</td><td>Design of an Automatic +<br/>Facial Expression Detector +<br/>An essay presented for the degree +<br/>of +<br/>M.Math +<br/>Applied Mathematics +<br/><b>University of Waterloo</b><br/>2018/01/26 +</td><td>('2662893', 'Jian Liang', 'jian liang')</td><td></td></tr><tr><td>fcbec158e6a4ace3d4311b26195482b8388f0ee9</td><td>Face Recognition from Still Images and Videos <br/>Center for Automation Research (CfAR) and <br/>Department of Electrical and Computer Engineering <br/><b>University of Maryland, College Park, MD</b><br/>I. INTRODUCTION @@ -11431,7 +14153,10 @@ <br/>Recognition <br/>Bogaziçi Un. Electronics Eng. Dept. March 2010 </td><td>('3398552', 'Bilgin Esme', 'bilgin esme')</td><td></td></tr><tr><td>fcd77f3ca6b40aad6edbd1dab9681d201f85f365</td><td>c(cid:13)Copyright 2014 -</td><td>('3299424', 'Miro Enev', 'miro enev')</td><td></td></tr><tr><td>fc798314994bf94d1cde8d615ba4d5e61b6268b6</td><td>Face Recognition: face in video, age invariance, +</td><td>('3299424', 'Miro Enev', 'miro enev')</td><td></td></tr><tr><td>fcf91995dc4d9b0cee84bda5b5b0ce5b757740ac</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Asymmetric Discrete Graph Hashing +<br/><b>University of Florida, Gainesville, FL, 32611, USA</b></td><td>('2766473', 'Xiaoshuang Shi', 'xiaoshuang shi')<br/>('2082604', 'Fuyong Xing', 'fuyong xing')<br/>('46321210', 'Kaidi Xu', 'kaidi xu')<br/>('2599018', 'Manish Sapkota', 'manish sapkota')<br/>('49576071', 'Lin Yang', 'lin yang')</td><td>xsshi2015@ufl.edu +</td></tr><tr><td>fc798314994bf94d1cde8d615ba4d5e61b6268b6</td><td>Face Recognition: face in video, age invariance, <br/>and facial marks <br/>By <br/>A DISSERTATION @@ -11460,14 +14185,39 @@ <br/>Unsupervised Semantic Action Discovery from Video <br/>Collections <br/>Received: date / Accepted: date -</td><td>('3114252', 'Ozan Sener', 'ozan sener')<br/>('1681995', 'Ashutosh Saxena', 'ashutosh saxena')</td><td></td></tr><tr><td>fd4ac1da699885f71970588f84316589b7d8317b</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 +</td><td>('3114252', 'Ozan Sener', 'ozan sener')<br/>('1681995', 'Ashutosh Saxena', 'ashutosh saxena')</td><td></td></tr><tr><td>fdff2da5bdca66e0ab5874ef58ac2205fb088ed7</td><td>Continuous Supervised Descent Method for +<br/>Facial Landmark Localisation +<br/>1Universitat Oberta de Catalunya, 156 Rambla del Poblenou, Barcelona, Spain +<br/>2Universitat de Barcelona, 585 Gran Via de les Corts Catalanes, Barcelona, Spain +<br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA</b><br/>4Computer Vision Center, O Building, UAB Campus, Bellaterra, Spain +<br/><b>University of Pittsburgh, Pittsburgh, PA, USA</b></td><td>('3305641', 'Marc Oliu', 'marc oliu')<br/>('1733113', 'Takeo Kanade', 'takeo kanade')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')</td><td></td></tr><tr><td>fdfd57d4721174eba288e501c0c120ad076cdca8</td><td>An Analysis of Action Recognition Datasets for +<br/>Language and Vision Tasks +<br/><b>Institute for Language, Cognition and Computation</b><br/><b>School of Informatics, University of Edinburgh</b><br/>10 Crichton Street, Edinburgh EH8 9AB +</td><td>('2921001', 'Spandana Gella', 'spandana gella')<br/>('48716849', 'Frank Keller', 'frank keller')</td><td>S.Gella@sms.ed.ac.uk, keller@inf.ed.ac.uk +</td></tr><tr><td>fd4ac1da699885f71970588f84316589b7d8317b</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JANUARY 2007 <br/>Supervised Descent Method <br/>for Solving Nonlinear Least Squares <br/>Problems in Computer Vision -</td><td>('3182065', 'Xuehan Xiong', 'xuehan xiong')<br/>('1707876', 'Fernando De la Torre', 'fernando de la torre')</td><td></td></tr><tr><td>fdf533eeb1306ba418b09210387833bdf27bb756</td><td>951 -</td><td></td><td></td></tr><tr><td>fdfaf46910012c7cdf72bba12e802a318b5bef5a</td><td>Computerized Face Recognition in Renaissance +</td><td>('3182065', 'Xuehan Xiong', 'xuehan xiong')<br/>('1707876', 'Fernando De la Torre', 'fernando de la torre')</td><td></td></tr><tr><td>fd33df02f970055d74fbe69b05d1a7a1b9b2219b</td><td>Single Shot Temporal Action Detection +<br/><b>Shanghai Jiao Tong University, China. 2Columbia University, USA</b><br/><b>Cooperative Medianet Innovation Center (CMIC), Shanghai Jiao Tong University, China</b></td><td>('6873935', 'Tianwei Lin', 'tianwei lin')<br/>('1758267', 'Xu Zhao', 'xu zhao')<br/>('2195345', 'Zheng Shou', 'zheng shou')</td><td>{wzmsltw,zhaoxu}@sjtu.edu.cn,zs2262@columbia.edu +</td></tr><tr><td>fdf533eeb1306ba418b09210387833bdf27bb756</td><td>951 +</td><td></td><td></td></tr><tr><td>fdda5852f2cffc871fd40b0cb1aa14cea54cd7e3</td><td>Im2Flow: Motion Hallucination from Static Images for Action Recognition +<br/>UT Austin +<br/>UT Austin +<br/>UT Austin +</td><td>('3387849', 'Ruohan Gao', 'ruohan gao')<br/>('50398746', 'Bo Xiong', 'bo xiong')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>rhgao@cs.utexas.edu +<br/>bxiong@cs.utexas.edu +<br/>grauman@cs.utexas.edu +</td></tr><tr><td>fdfaf46910012c7cdf72bba12e802a318b5bef5a</td><td>Computerized Face Recognition in Renaissance <br/>Portrait Art -</td><td>('18640672', 'Ramya Srinivasan', 'ramya srinivasan')<br/>('3007257', 'Conrad Rudolph', 'conrad rudolph')<br/>('1688416', 'Amit Roy-Chowdhury', 'amit roy-chowdhury')</td><td></td></tr><tr><td>fd9feb21b3d1fab470ff82e3f03efce6a0e67a1f</td><td><b>University of Twente</b><br/>Department of Services, Cybersecurity and Safety +</td><td>('18640672', 'Ramya Srinivasan', 'ramya srinivasan')<br/>('3007257', 'Conrad Rudolph', 'conrad rudolph')<br/>('1688416', 'Amit Roy-Chowdhury', 'amit roy-chowdhury')</td><td></td></tr><tr><td>fd15e397629e0241642329fc8ee0b8cd6c6ac807</td><td>Semi-Supervised Clustering with Neural Networks +<br/>IIIT-Delhi, India +</td><td>('2200208', 'Ankita Shukla', 'ankita shukla')<br/>('39866663', 'Gullal Singh Cheema', 'gullal singh cheema')<br/>('34817359', 'Saket Anand', 'saket anand')</td><td>{ankitas, gullal1408, anands}@iiitd.ac.in +</td></tr><tr><td>fde41dc4ec6ac6474194b99e05b43dd6a6c4f06f</td><td>Multi-Expert Gender Classification on Age Group by Integrating Deep Neural +<br/>Networks +<br/><b>Yonsei University</b><br/>50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea. +</td><td>('51430701', 'Jun Beom Kho', 'jun beom kho')</td><td>kojb87@hanmail.net +</td></tr><tr><td>fd9feb21b3d1fab470ff82e3f03efce6a0e67a1f</td><td><b>University of Twente</b><br/>Department of Services, Cybersecurity and Safety <br/>Master Thesis <br/>Deep Verification Learning <br/>Author: @@ -11494,10 +14244,24 @@ <br/>under the 7th Framework Programme (FP7) for Research and Technological Development under grant <br/>under the 7th Framework Programme (FP7) for Research and Technological Development under grant <br/>agreement n°2010-248085. -</td><td></td><td></td></tr><tr><td>fd96432675911a702b8a4ce857b7c8619498bf9f</td><td>Improved Face Detection and Alignment using Cascade +</td><td></td><td></td></tr><tr><td>fd53be2e0a9f33080a9db4b5a5e416e24ae8e198</td><td>Apparent Age Estimation Using Ensemble of Deep Learning Models +<br/>Refik Can Mallı∗ +<br/>Mehmet Ayg¨un∗ +<br/>Hazım Kemal Ekenel +<br/><b>Istanbul Technical University</b><br/>Istanbul, Turkey +</td><td></td><td>{mallir,aygunme,ekenel}@itu.edu.tr +</td></tr><tr><td>fd71ae9599e8a51d8a61e31e6faaaf4a23a17d81</td><td>Action Detection from a Robot-Car Perspective +<br/>Universit´a degli Studi Federico II +<br/>Naples, Italy +<br/><b>Oxford Brookes University</b><br/>Oxford, UK +</td><td>('39078800', 'Valentina Fontana', 'valentina fontana')<br/>('51149466', 'Manuele Di Maio', 'manuele di maio')<br/>('51152717', 'Stephen Akrigg', 'stephen akrigg')<br/>('1931660', 'Gurkirt Singh', 'gurkirt singh')<br/>('49348905', 'Suman Saha', 'suman saha')<br/>('1754181', 'Fabio Cuzzolin', 'fabio cuzzolin')</td><td>vale.fontana@studenti.unina.it, man.dimaio@gmail.com +<br/>15057204@brookes.ac.uk, gurkirt.singh-2015@brookes.ac.uk, +<br/>suman.saha-2014@brookes.ac.uk, fabio.cuzzolin@brookes.ac.uk +</td></tr><tr><td>fd96432675911a702b8a4ce857b7c8619498bf9f</td><td>Improved Face Detection and Alignment using Cascade <br/>Deep Convolutional Network <br/>†Beijing Key Laboratory of Intelligent Information Technology, School of -<br/><b>Computer Science, Beijing Institute of Technology, Beijing 100081, P.R.China</b><br/><b>China Mobile Research Institute, Xuanwu Men West Street, Beijing</b></td><td>('22244104', 'Weilin Cong', 'weilin cong')<br/>('2901725', 'Sanyuan Zhao', 'sanyuan zhao')<br/>('1698061', 'Hui Tian', 'hui tian')<br/>('34926055', 'Jianbing Shen', 'jianbing shen')</td><td></td></tr><tr><td>fd7b6c77b46420c27725757553fcd1fb24ea29a8</td><td>MEXSVMs: Mid-level Features for Scalable Action Recognition +<br/><b>Computer Science, Beijing Institute of Technology, Beijing 100081, P.R.China</b><br/><b>China Mobile Research Institute, Xuanwu Men West Street, Beijing</b></td><td>('22244104', 'Weilin Cong', 'weilin cong')<br/>('2901725', 'Sanyuan Zhao', 'sanyuan zhao')<br/>('1698061', 'Hui Tian', 'hui tian')<br/>('34926055', 'Jianbing Shen', 'jianbing shen')</td><td></td></tr><tr><td>fd10b0c771a2620c0db294cfb82b80d65f73900d</td><td>Identifying The Most Informative Features Using A Structurally Interacting Elastic Net +<br/><b>Central University of Finance and Economics, Beijing, China</b><br/><b>Xiamen University, Xiamen, Fujian, China</b><br/><b>University of York, York, UK</b></td><td>('2290930', 'Lixin Cui', 'lixin cui')<br/>('1749518', 'Lu Bai', 'lu bai')<br/>('47295137', 'Zhihong Zhang', 'zhihong zhang')<br/>('49416727', 'Yue Wang', 'yue wang')<br/>('1679753', 'Edwin R. Hancock', 'edwin r. hancock')</td><td></td></tr><tr><td>fd7b6c77b46420c27725757553fcd1fb24ea29a8</td><td>MEXSVMs: Mid-level Features for Scalable Action Recognition <br/><b>Dartmouth College</b><br/>6211 Sudikoff Lab, Hanover, NH 03755 <br/>Dartmouth Computer Science Technical Report TR2013-726 </td><td>('1687325', 'Du Tran', 'du tran')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')</td><td>{dutran,lorenzo}@cs.dartmouth.edu @@ -11573,7 +14337,71 @@ <br/>et al., 2014). <br/>The SOM makes use of an unsupervised learning </td><td>('2274078', 'Francisco A. Pujol', 'francisco a. pujol')</td><td>e-mail: {fpujol,hmora}@dtic.ua.es,jags20@alu.ua.es -</td></tr><tr><td>fde0180735699ea31f6c001c71eae507848b190f</td><td>International Journal of Computer Applications (0975 – 8887) +</td></tr><tr><td>fdbacf2ff0fc21e021c830cdcff7d347f2fddd8e</td><td>ORIGINAL RESEARCH +<br/>published: 17 August 2018 +<br/>doi: 10.3389/fnhum.2018.00327 +<br/>Recognizing Frustration of Drivers +<br/>From Face Video Recordings and +<br/>Brain Activation Measurements With +<br/>Functional Near-Infrared +<br/>Spectroscopy +<br/><b>Institute of Transportation Systems, German Aerospace Center (DLR), Braunschweig</b><br/><b>Germany, University of Oldenburg, Oldenburg, Germany</b><br/>Experiencing frustration while driving can harm cognitive processing, result in aggressive +<br/>behavior and hence negatively influence driving performance and traffic safety. Being +<br/>able to automatically detect frustration would allow adaptive driver assistance and +<br/>automation systems to adequately react to a driver’s frustration and mitigate potential +<br/>negative consequences. To identify reliable and valid indicators of driver’s frustration, +<br/>we conducted two driving simulator experiments. In the first experiment, we aimed to +<br/>reveal facial expressions that indicate frustration in continuous video recordings of the +<br/>driver’s face taken while driving highly realistic simulator scenarios in which frustrated +<br/>or non-frustrated emotional states were experienced. An automated analysis of facial +<br/>expressions combined with multivariate logistic regression classification revealed that +<br/>frustrated time intervals can be discriminated from non-frustrated ones with accuracy +<br/>of 62.0% (mean over 30 participants). A further analysis of the facial expressions +<br/>revealed that frustrated drivers tend to activate muscles in the mouth region (chin +<br/>raiser, lip pucker, lip pressor). In the second experiment, we measured cortical activation +<br/>with almost whole-head functional near-infrared spectroscopy (fNIRS) while participants +<br/>experienced frustrating and non-frustrating driving simulator scenarios. Multivariate +<br/>logistic regression applied to the fNIRS measurements allowed us to discriminate +<br/>between frustrated and non-frustrated driving intervals with higher accuracy of 78.1% +<br/>(mean over 12 participants). Frustrated driving intervals were indicated by increased +<br/>activation in the inferior frontal, putative premotor and occipito-temporal cortices. +<br/>Our results show that facial and cortical markers of +<br/>frustration can be informative +<br/>for time resolved driver state identification in complex realistic driving situations. The +<br/>markers derived here can potentially be used as an input for future adaptive driver +<br/>assistance and automation systems that detect driver frustration and adaptively react +<br/>to mitigate it. +<br/>Keywords: frustration, driver state recognition, facial expressions, functional near-infrared spectroscopy, adaptive +<br/>automation +<br/>Edited by: +<br/>Guido P. H. Band, +<br/><b>Leiden University, Netherlands</b><br/>Reviewed by: +<br/>Paola Pinti, +<br/><b>University College London</b><br/>United Kingdom +<br/>Edmund Wascher, +<br/>Leibniz-Institut für Arbeitsforschung +<br/>an der TU Dortmund (IfADo), +<br/>Germany +<br/>*Correspondence: +<br/>Received: 17 April 2018 +<br/>Accepted: 25 July 2018 +<br/>Published: 17 August 2018 +<br/>Citation: +<br/>Ihme K, Unni A, Zhang M, Rieger JW +<br/>and Jipp M (2018) Recognizing +<br/>Frustration of Drivers From Face +<br/>Video Recordings and Brain +<br/>Activation Measurements With +<br/>Functional Near-Infrared +<br/>Spectroscopy. +<br/>Front. Hum. Neurosci. 12:327. +<br/>doi: 10.3389/fnhum.2018.00327 +<br/>Frontiers in Human Neuroscience | www.frontiersin.org +<br/>August 2018 | Volume 12 | Article 327 +</td><td>('2873465', 'Klas Ihme', 'klas ihme')<br/>('34722642', 'Anirudh Unni', 'anirudh unni')<br/>('48984951', 'Meng Zhang', 'meng zhang')<br/>('2743311', 'Jochem W. Rieger', 'jochem w. rieger')<br/>('50093361', 'Meike Jipp', 'meike jipp')<br/>('2873465', 'Klas Ihme', 'klas ihme')</td><td>klas.ihme@dlr.de +</td></tr><tr><td>fd892e912149e3f5ddd82499e16f9ea0f0063fa3</td><td>GazeDirector: Fully Articulated Eye Gaze Redirection in Video +<br/><b>University of Cambridge, UK 2Carnegie Mellon University, USA</b><br/><b>Max Planck Institute for Informatics, Germany</b><br/>4Microsoft +</td><td>('34399452', 'Erroll Wood', 'erroll wood')<br/>('49933077', 'Louis-Philippe Morency', 'louis-philippe morency')</td><td></td></tr><tr><td>fde0180735699ea31f6c001c71eae507848b190f</td><td>International Journal of Computer Applications (0975 – 8887) <br/>Volume 76– No.3, August 2013 <br/>Face Detection and Sex Identification from Color Images <br/>using AdaBoost with SVM based Component Classifier @@ -11589,10 +14417,36 @@ <br/><b>International University of</b><br/>Business Agriculture and <br/>Technology (IUBAT) <br/>Dhaka-1230, Bangladesh -</td><td>('1804849', 'Tonmoy Das', 'tonmoy das')<br/>('2832495', 'Md. Hafizur Rahman', 'md. hafizur rahman')</td><td></td></tr><tr><td>fd615118fb290a8e3883e1f75390de8a6c68bfde</td><td>Joint Face Alignment with Non-Parametric +</td><td>('1804849', 'Tonmoy Das', 'tonmoy das')<br/>('2832495', 'Md. Hafizur Rahman', 'md. hafizur rahman')</td><td></td></tr><tr><td>fdf8e293a7618f560e76bd83e3c40a0788104547</td><td>Interspecies Knowledge Transfer for Facial Keypoint Detection +<br/><b>University of California, Davis</b><br/><b>Zhejiang University</b><br/><b>University of California, Davis</b></td><td>('35157022', 'Maheen Rashid', 'maheen rashid')<br/>('10734287', 'Xiuye Gu', 'xiuye gu')<br/>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td>mhnrashid@ucdavis.edu +<br/>gxy0922@zju.edu.cn +<br/>yongjaelee@ucdavis.edu +</td></tr><tr><td>fd615118fb290a8e3883e1f75390de8a6c68bfde</td><td>Joint Face Alignment with Non-Parametric <br/>Shape Models <br/><b>University of Wisconsin Madison</b><br/>http://www.cs.wisc.edu/~lizhang/projects/joint-align/ -</td><td>('1893050', 'Brandon M. Smith', 'brandon m. smith')<br/>('40396555', 'Li Zhang', 'li zhang')</td><td></td></tr><tr><td>f24e379e942e134d41c4acec444ecf02b9d0d3a9</td><td>International Scholarly Research Network +</td><td>('1893050', 'Brandon M. Smith', 'brandon m. smith')<br/>('40396555', 'Li Zhang', 'li zhang')</td><td></td></tr><tr><td>fdaf65b314faee97220162980e76dbc8f32db9d6</td><td>Accepted Manuscript +<br/>Face recognition using both visible light image and near-infrared image and a deep +<br/>network +<br/>PII: +<br/>DOI: +<br/>Reference: +<br/>S2468-2322(17)30014-8 +<br/>10.1016/j.trit.2017.03.001 +<br/>TRIT 41 +<br/>To appear in: +<br/>CAAI Transactions on Intelligence Technology +<br/>Received Date: 30 January 2017 +<br/>Accepted Date: 28 March 2017 +<br/>Please cite this article as: K. Guo, S. Wu, Y. Xu, Face recognition using both visible light image and +<br/>near-infrared image and a deep network, CAAI Transactions on Intelligence Technology (2017), doi: +<br/>10.1016/j.trit.2017.03.001. +<br/>This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to +<br/>our customers we are providing this early version of the manuscript. The manuscript will undergo +<br/>copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please +<br/>note that during the production process errors may be discovered which could affect the content, and all +<br/>legal disclaimers that apply to the journal pertain. +</td><td>('48477652', 'Kai Guo', 'kai guo')<br/>('40200363', 'Shuai Wu', 'shuai wu')</td><td></td></tr><tr><td>f22d6d59e413ee255e5e0f2104f1e03be1a6722e</td><td>Lattice Long Short-Term Memory for Human Action Recognition +<br/><b>The Hong Kong University of Science and Technology</b><br/><b>Stanford University</b><br/><b>South China University of Technology</b></td><td>('41191188', 'Lin Sun', 'lin sun')<br/>('2370507', 'Kui Jia', 'kui jia')<br/>('1794604', 'Kevin Chen', 'kevin chen')<br/>('2131088', 'Bertram E. Shi', 'bertram e. shi')<br/>('1702137', 'Silvio Savarese', 'silvio savarese')</td><td></td></tr><tr><td>f24e379e942e134d41c4acec444ecf02b9d0d3a9</td><td>International Scholarly Research Network <br/>ISRN Machine Vision <br/>Volume 2012, Article ID 505974, 7 pages <br/>doi:10.5402/2012/505974 @@ -11685,7 +14539,98 @@ <br/><b>Nanjing University, Nanjing 210093, P.R.China</b><br/>2Department of Computer Science <br/><b>North Dakota State University, Fargo, ND58105, USA</b></td><td>('7878359', 'Wu-Jun Li', 'wu-jun li')<br/>('2697799', 'Chong-Jun Wang', 'chong-jun wang')<br/>('1737124', 'Bin Luo', 'bin luo')</td><td>Email: {liwujun, chjwang}@ai.nju.edu.cn <br/>Email: Dianxiang.xu@ndsu.nodak.edu -</td></tr><tr><td>f2e9494d0dca9fb6b274107032781d435a508de6</td><td></td><td></td><td></td></tr><tr><td>f2c568fe945e5743635c13fe5535af157b1903d1</td><td></td><td></td><td></td></tr><tr><td>f26097a1a479fb6f32b27a93f8f32609cfe30fdc</td><td></td><td></td><td></td></tr><tr><td>f214bcc6ecc3309e2efefdc21062441328ff6081</td><td></td><td></td><td></td></tr><tr><td>f5149fb6b455a73734f1252a96a9ce5caa95ae02</td><td>Low-Rank-Sparse Subspace Representation for Robust Regression +</td></tr><tr><td>f2e9494d0dca9fb6b274107032781d435a508de6</td><td></td><td></td><td></td></tr><tr><td>f2c568fe945e5743635c13fe5535af157b1903d1</td><td></td><td></td><td></td></tr><tr><td>f2a7f9bd040aa8ea87672d38606a84c31163e171</td><td>Human Action Recognition without Human +<br/><b>National Institute of Advanced Industrial Science and Technology (AIST</b><br/>Tsukuba, Ibaraki, Japan +</td><td>('1713046', 'Yun He', 'yun he')<br/>('3393640', 'Soma Shirakabe', 'soma shirakabe')<br/>('1732705', 'Yutaka Satoh', 'yutaka satoh')<br/>('1730200', 'Hirokatsu Kataoka', 'hirokatsu kataoka')</td><td>{yun.he, shirakabe-s, yu.satou, hirokatsu.kataoka}@aist.go.jp +</td></tr><tr><td>f257300b2b4141aab73f93c146bf94846aef5fa1</td><td>Eigen Evolution Pooling for Human Action Recognition +<br/><b>Stony Brook University, Stony Brook, NY 11794, USA</b></td><td>('2295608', 'Yang Wang', 'yang wang')<br/>('49701507', 'Vinh Tran', 'vinh tran')<br/>('2356016', 'Minh Hoai', 'minh hoai')</td><td>{wang33, tquangvinh, minhhoai}@cs.stonybrook.edu +</td></tr><tr><td>f20e0eefd007bc310d2a753ba526d33a8aba812c</td><td>Lee et al.: RGB-D FACE RECOGNITION WITH A DEEP LEARNING APPROACH +<br/>Accurate and robust face recognition from +<br/>RGB-D images with a deep learning +<br/>approach +<br/>Yuancheng Lee +<br/>http://cv.cs.nthu.edu.tw/php/people/profile.php?uid=150 +<br/>http://cv.cs.nthu.edu.tw/php/people/profile.php?uid=153 +<br/>Ching-Wei Tseng +<br/>http://cv.cs.nthu.edu.tw/php/people/profile.php?uid=156 +<br/>Computer Vision Lab, +<br/>Department of +<br/>Computer Science, +<br/>National Tsing Hua +<br/><b>University</b><br/>Hsinchu, Taiwan +<br/>http://www.cs.nthu.edu.tw/~lai/ +</td><td>('7557765', 'Jiancong Chen', 'jiancong chen')<br/>('1696527', 'Shang-Hong Lai', 'shang-hong lai')</td><td></td></tr><tr><td>f26097a1a479fb6f32b27a93f8f32609cfe30fdc</td><td></td><td></td><td></td></tr><tr><td>f231046d5f5d87e2ca5fae88f41e8d74964e8f4f</td><td>We are IntechOpen, +<br/>the first native scientific +<br/>publisher of Open Access books +<br/>3,350 +<br/>108,000 +<br/>1.7 M +<br/>Open access books available +<br/>International authors and editors +<br/>Downloads +<br/>Our authors are among the +<br/>151 +<br/>Countries delivered to +<br/>TOP 1% +<br/>12.2% +<br/>most cited scientists +<br/>Contributors from top 500 universities +<br/>Selection of our books indexed in the Book Citation Index +<br/>in Web of Science™ Core Collection (BKCI) +<br/>Interested in publishing with us? +<br/>Numbers displayed above are based on latest data collected. +<br/>For more information visit www.intechopen.com +</td><td></td><td>Contact book.department@intechopen.com +</td></tr><tr><td>f28b7d62208fdaaa658716403106a2b0b527e763</td><td>Clustering-driven Deep Embedding with Pairwise Constraints +<br/><b>JACOB GOLDBERGER, Bar-Ilan University</b><br/>Fig. 1. Employing deep embeddings for clustering 3D shapes. Above, we use PCA to visualize the output embedding of point clouds of chairs. We also highlight +<br/>(in unique colors) a few random clusters and display a few representative chairs from these clusters. +<br/>Recently, there has been increasing interest to leverage the competence +<br/>of neural networks to analyze data. In particular, new clustering meth- +<br/>ods that employ deep embeddings have been presented. In this paper, we +<br/>depart from centroid-based models and suggest a new framework, called +<br/>Clustering-driven deep embedding with PAirwise Constraints (CPAC), for +<br/>non-parametric clustering using a neural network. We present a clustering- +<br/>driven embedding based on a Siamese network that encourages pairs of data +<br/>points to output similar representations in the latent space. Our pair-based +<br/>model allows augmenting the information with labeled pairs to constitute a +<br/>semi-supervised framework. Our approach is based on analyzing the losses +<br/>associated with each pair to refine the set of constraints. We show that clus- +<br/>tering performance increases when using this scheme, even with a limited +<br/>amount of user queries. We demonstrate how our architecture is adapted +<br/>for various types of data and present the first deep framework to cluster 3D +<br/>shapes. +<br/>INTRODUCTION +<br/>Autoencoders provide means to analyze data without supervision. +<br/>Autoencoders based on deep neural networks include non-linear +<br/>neurons which significantly strengthen the power of the analysis. +<br/>The key idea is that the encoders project the data into an embedding +<br/>latent space, where the L2 proximity among the projected elements +<br/>better expresses their similarity. To further enhance the data prox- +<br/>imity in the embedding space, the encoder can be encouraged to +<br/>form tight clusters in the embedding space. Xie et al. [2016] have +<br/>presented an unsupervised embedding driven by a centroid-based +<br/>clustering. They have shown that their deep embedding leads to +<br/>better clustering of the data. More advanced clustering-driven em- +<br/>bedding techniques have been recently presented [Dizaji et al. 2017; +<br/>Yang et al. 2016]. These techniques are all centroid-based and para- +<br/>metric, in the sense that the number of clusters is known a-priori. +<br/>In this paper, we present a clustering-driven embedding technique +<br/>that allows semi-supervision. The idea is to depart from centroid- +<br/>based methods and use pairwise constraints to drive the clustering. +<br/>Most, or all the constraints, can be learned with no supervision, +<br/>while possibly a small portion of the data is supervised. More specifi- +<br/>cally, we adopt robust continuous clustering (RCC) [Shah and Koltun +<br/>2017] as a driving mechanism to encourage a tight clustering of the +<br/>embedded data. +<br/>The idea is to extract pairwise constraints using a mutual k- +<br/>nearest neighbors analysis, and use these pairs as must-link con- +<br/>straints. With no supervision, the set of constraints is imperfect +<br/>and contains false positive pairs on one hand. Our technique allows +<br/>removing false positive pairs and strengthening true positive pairs +<br/>actively by a user. We present an approach that analyzes the losses +<br/>associated with the pairs to form a set of false positive candidates. +<br/>See Figure 2(b)-(c) for a visualization of the distribution of the data +</td><td>('40901326', 'Sharon Fogel', 'sharon fogel')<br/>('1793313', 'Hadar Averbuch-Elor', 'hadar averbuch-elor')<br/>('1701009', 'Daniel Cohen-Or', 'daniel cohen-or')</td><td></td></tr><tr><td>f214bcc6ecc3309e2efefdc21062441328ff6081</td><td></td><td></td><td></td></tr><tr><td>f5149fb6b455a73734f1252a96a9ce5caa95ae02</td><td>Low-Rank-Sparse Subspace Representation for Robust Regression <br/><b>Harbin Institute of Technology</b><br/><b>Harbin Institute of Technology;Shenzhen University</b><br/>Harbin, China <br/>Harbin, China;Shenzhen, China <br/><b>The University of Sydney</b><br/><b>Harbin Institute of Technology</b><br/>Sydney, Australia @@ -11694,6 +14639,30 @@ <br/>d.m.shi@hotmail.com <br/>junbin.gao@sydney.edu.au <br/>cdsinhit@hit.edu.cn +</td></tr><tr><td>f58d584c4ac93b4e7620ef6e5a8f20c6f6da295e</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Feature Selection Guided Auto-Encoder +<br/>1Department of Electrical & Computer Engineering, +<br/><b>College of Computer and Information Science</b><br/><b>Northeastern University, Boston, MA, USA</b></td><td>('47673521', 'Shuyang Wang', 'shuyang wang')<br/>('2788685', 'Zhengming Ding', 'zhengming ding')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td>{shuyangwang, allanding, yunfu}@ece.neu.edu +</td></tr><tr><td>f5eb0cf9c57716618fab8e24e841f9536057a28a</td><td>Rethinking Feature Distribution for Loss Functions in Image Classification +<br/><b>Tsinghua University, Beijing, China</b><br/><b>University of at Urbana-Champaign, Illinois, USA</b></td><td>('47718901', 'Weitao Wan', 'weitao wan')<br/>('1752427', 'Jiansheng Chen', 'jiansheng chen')<br/>('8802368', 'Yuanyi Zhong', 'yuanyi zhong')<br/>('2641581', 'Tianpeng Li', 'tianpeng li')</td><td>wwt16@mails.tsinghua.edu.cn +<br/>yuanyiz2@illinois.edu +<br/>ltp16@mails.tsinghua.edu.cn +<br/>jschenthu@mail.tsinghua.edu.cn +</td></tr><tr><td>f571fe3f753765cf695b75b1bd8bed37524a52d2</td><td>Submodular Attribute Selection for Action +<br/>Recognition in Video +<br/>Jinging Zheng +<br/><b>UMIACS, University of Maryland</b><br/><b>College Park, MD, USA</b><br/>Noah’s Ark Lab +<br/>Huawei Technologies +<br/><b>UMIACS, University of Maryland</b><br/><b>National Institute of Standards and Technology</b><br/><b>College Park, MD, USA</b><br/>Gaithersburg, MD, USA +</td><td>('34145947', 'Zhuolin Jiang', 'zhuolin jiang')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('32028519', 'P. Jonathon Phillips', 'p. jonathon phillips')</td><td>zjngjng@umiacs.umd.edu +<br/>zhuolin.jiang@huawei.com +<br/>rama@umiacs.umd.edu +<br/>jonathon.phillips@nist.gov +</td></tr><tr><td>f5fae7810a33ed67852ad6a3e0144cb278b24b41</td><td>Multilingual Gender Classification with Multi-view +<br/>Deep Learning +<br/>Notebook for PAN at CLEF 2018 +<br/><b>Jo ef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia</b><br/>2 Jožef Stefan International Postgraduate School, Jamova 39, 1000 Ljubljana, Slovenia +<br/><b>USHER Institute, University of Edinburgh, United Kingdom</b></td><td>('22684661', 'Matej Martinc', 'matej martinc')<br/>('40235216', 'Senja Pollak', 'senja pollak')</td><td>{matej.martinc,blaz.skrlj,senja.pollak}@ijs.si </td></tr><tr><td>f5af4e9086b0c3aee942cb93ece5820bdc9c9748</td><td>ENHANCING PERSON ANNOTATION <br/>FOR PERSONAL PHOTO MANAGEMENT <br/>USING CONTENT AND CONTEXT @@ -11704,7 +14673,9 @@ <br/>DEGREE OF DOCTOR OF PHILOSOPHY <br/>September 2008 <br/>SCHOOL OF ELECTRONIC ENGINEERING -<br/><b>DUBLIN CITY UNIVERSITY</b></td><td>('2668569', 'Saman H. Cooray', 'saman h. cooray')</td><td></td></tr><tr><td>f5aee1529b98136194ef80961ba1a6de646645fe</td><td>Large-Scale Learning of +<br/><b>DUBLIN CITY UNIVERSITY</b></td><td>('2668569', 'Saman H. Cooray', 'saman h. cooray')</td><td></td></tr><tr><td>f5770dd225501ff3764f9023f19a76fad28127d4</td><td>Real Time Online Facial Expression Transfer +<br/>with Single Video Camera +</td><td></td><td></td></tr><tr><td>f5aee1529b98136194ef80961ba1a6de646645fe</td><td>Large-Scale Learning of <br/>Discriminative Image Representations <br/>D.Phil Thesis <br/>Robotics Research Group @@ -11721,7 +14692,17 @@ <br/>aEURECOM, Campus SophiaTech, 450 Route des Chappes, CS 50193 - 06904 Biot Sophia <br/> <br/>Antipolis cedex, FRANCE -</td><td>('24362694', 'V. Chiesa', 'v. chiesa')</td><td></td></tr><tr><td>f558af209dd4c48e4b2f551b01065a6435c3ef33</td><td>International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) +</td><td>('24362694', 'V. Chiesa', 'v. chiesa')</td><td></td></tr><tr><td>f5eb411217f729ad7ae84bfd4aeb3dedb850206a</td><td>Tackling Low Resolution for Better Scene Understanding +<br/>Thesis submitted in partial fulfillment +<br/>of the requirements for the degree of +<br/>MS in Computer Science and Engineering +<br/>By Research +<br/>by +<br/>201202172 +<br/><b>International Institute of Information Technology</b><br/>Hyderabad - 500 032, INDIA +<br/>July 2018 +</td><td>('41033644', 'Harish Krishna', 'harish krishna')</td><td>harishkrishna.v@research.iiit.ac.in +</td></tr><tr><td>f558af209dd4c48e4b2f551b01065a6435c3ef33</td><td>International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) <br/>ISSN: 0976-1353 Volume 23 Issue 1 –JUNE 2016. <br/>AN ENHANCED ATTRIBUTE <br/>RERANKING DESIGN FOR WEB IMAGE @@ -11729,13 +14710,33 @@ <br/>#Student,Cse, CIET, Lam,Guntur, India <br/>* Assistant Professort,Cse, CIET, Lam,Guntur , India </td><td>('4384318', 'G K Kishore Babu', 'g k kishore babu')</td><td></td></tr><tr><td>e378ce25579f3676ca50c8f6454e92a886b9e4d7</td><td>Robust Video Super-Resolution with Learned Temporal Dynamics -<br/><b>University of Illinois at Urbana-Champaign 2Adobe Research</b><br/><b>Facebook 4Texas AandM University 5IBM Research</b></td><td>('1771885', 'Ding Liu', 'ding liu')<br/>('2969311', 'Zhangyang Wang', 'zhangyang wang')</td><td></td></tr><tr><td>e35b09879a7df814b2be14d9102c4508e4db458b</td><td>Optimal Sensor Placement and +<br/><b>University of Illinois at Urbana-Champaign 2Adobe Research</b><br/><b>Facebook 4Texas AandM University 5IBM Research</b></td><td>('1771885', 'Ding Liu', 'ding liu')<br/>('2969311', 'Zhangyang Wang', 'zhangyang wang')</td><td></td></tr><tr><td>e393a038d520a073b9835df7a3ff104ad610c552</td><td>Automatic temporal segment +<br/>detection via bilateral long short- +<br/>term memory recurrent neural +<br/>networks +<br/>detection via bilateral long short-term memory recurrent neural networks,” J. +<br/>Electron. Imaging 26(2), 020501 (2017), doi: 10.1117/1.JEI.26.2.020501. +<br/>Downloaded From: http://electronicimaging.spiedigitallibrary.org/ on 03/03/2017 Terms of Use: http://spiedigitallibrary.org/ss/termsofuse.aspx </td><td>('49447269', 'Bo Sun', 'bo sun')<br/>('7886608', 'Siming Cao', 'siming cao')<br/>('49264106', 'Jun He', 'jun he')<br/>('8834504', 'Lejun Yu', 'lejun yu')<br/>('2089565', 'Liandong Li', 'liandong li')<br/>('49447269', 'Bo Sun', 'bo sun')<br/>('7886608', 'Siming Cao', 'siming cao')<br/>('49264106', 'Jun He', 'jun he')<br/>('8834504', 'Lejun Yu', 'lejun yu')<br/>('2089565', 'Liandong Li', 'liandong li')</td><td></td></tr><tr><td>e35b09879a7df814b2be14d9102c4508e4db458b</td><td>Optimal Sensor Placement and <br/>Enhanced Sparsity for Classification -<br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>Institute for Disease Modeling, Intellectual Ventures Laboratory, Bellevue, WA 98004, United States</b></td><td>('1824880', 'Bingni W. Brunton', 'bingni w. brunton')<br/>('3083169', 'Steven L. Brunton', 'steven l. brunton')<br/>('2424683', 'Joshua L. Proctor', 'joshua l. proctor')<br/>('1937069', 'J. Nathan Kutz', 'j. nathan kutz')</td><td></td></tr><tr><td>e3657ab4129a7570230ff25ae7fbaccb4ba9950c</td><td></td><td></td><td></td></tr><tr><td>e315959d6e806c8fbfc91f072c322fb26ce0862b</td><td>An Efficient Face Recognition System Based on Sub-Window +<br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>University of Washington, Seattle, WA 98195, United States</b><br/><b>Institute for Disease Modeling, Intellectual Ventures Laboratory, Bellevue, WA 98004, United States</b></td><td>('1824880', 'Bingni W. Brunton', 'bingni w. brunton')<br/>('3083169', 'Steven L. Brunton', 'steven l. brunton')<br/>('2424683', 'Joshua L. Proctor', 'joshua l. proctor')<br/>('1937069', 'J. Nathan Kutz', 'j. nathan kutz')</td><td></td></tr><tr><td>e3b324101157daede3b4d16bdc9c2388e849c7d4</td><td>Robust Real-Time 3D Face Tracking from RGBD Videos under Extreme Pose, +<br/>Depth, and Expression Variations +<br/>Hai X. Pham +<br/><b>Rutgers University, USA</b></td><td>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')</td><td>{hxp1,vladimir}@cs.rutgers.edu +</td></tr><tr><td>e3657ab4129a7570230ff25ae7fbaccb4ba9950c</td><td></td><td></td><td></td></tr><tr><td>e315959d6e806c8fbfc91f072c322fb26ce0862b</td><td>An Efficient Face Recognition System Based on Sub-Window <br/>International Journal of Soft Computing and Engineering (IJSCE) <br/>ISSN: 2231-2307, Volume-1, Issue-6, January 2012 <br/>Extraction Algorithm -</td><td>('1696227', 'Manish Gupta', 'manish gupta')<br/>('36776003', 'Govind sharma', 'govind sharma')</td><td></td></tr><tr><td>e39a0834122e08ba28e7b411db896d0fdbbad9ba</td><td>1368 +</td><td>('1696227', 'Manish Gupta', 'manish gupta')<br/>('36776003', 'Govind sharma', 'govind sharma')</td><td></td></tr><tr><td>e3c011d08d04c934197b2a4804c90be55e21d572</td><td>How to Train Triplet Networks with 100K Identities? +<br/>Orion Star +<br/>Beijing, China +<br/>Orion Star +<br/>Beijing, China +<br/>Orion Star +<br/>Beijing, China +</td><td>('1747751', 'Chong Wang', 'chong wang')<br/>('46447079', 'Xue Zhang', 'xue zhang')<br/>('26403761', 'Xipeng Lan', 'xipeng lan')</td><td>chongwang.nlpr@gmail.com +<br/>yuannixue@126.com +<br/>xipeng.lan@gmail.com +</td></tr><tr><td>e39a0834122e08ba28e7b411db896d0fdbbad9ba</td><td>1368 <br/>Maximum Likelihood Estimation of Depth Maps <br/>Using Photometric Stereo </td><td>('2964822', 'Adam P. Harrison', 'adam p. harrison')<br/>('39367958', 'Dileepan Joseph', 'dileepan joseph')</td><td></td></tr><tr><td>e3bb83684817c7815f5005561a85c23942b1f46b</td><td>Face Verification using Correlation Filters @@ -11802,9 +14803,29 @@ <br/>each session 13 conditions with varying facial expressions, illumination and occlusion were captured. Figure 1 shows an <br/>example for each condition. So far, more than 200 research groups have accessed the database. </td><td>('33731953', 'Ralph Gross', 'ralph gross')</td><td>Email: {rgross}@cs.cmu.edu +</td></tr><tr><td>e39a66a6d1c5e753f8e6c33cd5d335f9bc9c07fa</td><td><b>University of Massachusetts - Amherst</b><br/>Dissertations +<br/>5-1-2012 +<br/>Dissertations and Theses +<br/>Weakly Supervised Learning for Unconstrained +<br/>Face Processing +<br/>Follow this and additional works at: http://scholarworks.umass.edu/open_access_dissertations +<br/>Recommended Citation +<br/>Huang, Gary B., "Weakly Supervised Learning for Unconstrained Face Processing" (2012). Dissertations. Paper 559. +</td><td>('3219900', 'Gary B. Huang', 'gary b. huang')</td><td>ScholarWorks@UMass Amherst +<br/>University of Massachusetts - Amherst, garybhuang@gmail.com +<br/>This Open Access Dissertation is brought to you for free and open access by the Dissertations and Theses at ScholarWorks@UMass Amherst. It has +<br/>been accepted for inclusion in Dissertations by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact +<br/>scholarworks@library.umass.edu. </td></tr><tr><td>e3a6e9ddbbfc4c5160082338d46808cea839848a</td><td>Vision-Based Classification of Developmental Disorders <br/>Using Eye-Movements -<br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b></td><td>('3147852', 'Guido Pusiol', 'guido pusiol')<br/>('1811529', 'Andre Esteva', 'andre esteva')<br/>('3472674', 'Arnold Milstein', 'arnold milstein')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>e3917d6935586b90baae18d938295e5b089b5c62</td><td>152 +<br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b></td><td>('3147852', 'Guido Pusiol', 'guido pusiol')<br/>('1811529', 'Andre Esteva', 'andre esteva')<br/>('3472674', 'Arnold Milstein', 'arnold milstein')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>e3c8e49ffa7beceffca3f7f276c27ae6d29b35db</td><td>Families in the Wild (FIW): Large-Scale Kinship Image +<br/>Database and Benchmarks +<br/><b>Northeastern University, Boston, USA</b><br/><b>College of Computer and Information Science, Northeastern University, Boston, USA</b></td><td>('4056993', 'Joseph P. Robinson', 'joseph p. robinson')<br/>('49248003', 'Ming Shao', 'ming shao')<br/>('47096713', 'Yue Wu', 'yue wu')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td>{jrobins1, mingshao, yuewu, yunfu}@ece.neu.edu +</td></tr><tr><td>e38371b69be4f341baa95bc854584e99b67c6d3a</td><td>DYAN: A Dynamical Atoms-Based Network +<br/>For Video Prediction(cid:63) +<br/><b>Electrical and Computer Engineering, Northeastern University, Boston, MA</b><br/>http://robustsystems.coe.neu.edu +</td><td>('40366599', 'WenQian Liu', 'wenqian liu')<br/>('1785252', 'Abhishek Sharma', 'abhishek sharma')<br/>('30929906', 'Octavia Camps', 'octavia camps')<br/>('1687866', 'Mario Sznaier', 'mario sznaier')</td><td>liu.wenqi,sharma.abhis@husky.neu.edu, camps,msznaier@northeastern.edu +</td></tr><tr><td>e3917d6935586b90baae18d938295e5b089b5c62</td><td>152 <br/>Face Localization and Authentication <br/>Using Color and Depth Images </td><td>('1807962', 'Filareti Tsalakanidou', 'filareti tsalakanidou')<br/>('1744180', 'Sotiris Malassiotis', 'sotiris malassiotis')<br/>('1721460', 'Michael G. Strintzis', 'michael g. strintzis')</td><td></td></tr><tr><td>e328d19027297ac796aae2470e438fe0bd334449</td><td>Automatic Micro-expression Recognition from @@ -11819,7 +14840,10 @@ <br/>Optical-Flow Estimation in the Wild <br/><b>University of Freiburg</b><br/>Germany </td><td>('31656404', 'Nima Sedaghat', 'nima sedaghat')</td><td>nima@cs.uni-freiburg.de -</td></tr><tr><td>cffebdf88e406c27b892857d1520cb2d7ccda573</td><td>LEARNING FROM LARGE-SCALE VISUAL DATA +</td></tr><tr><td>e3a6e5a573619a97bd6662b652ea7d088ec0b352</td><td>Compare and Contrast: Learning Prominent Visual Differences +<br/><b>The University of Texas at Austin</b></td><td>('50357985', 'Steven Chen', 'steven chen')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td></td></tr><tr><td>cfeb26245b57dd10de8f187506d4ed5ce1e2b7dd</td><td>CapsNet comparative performance evaluation for image +<br/>classification +<br/><b>University of Waterloo, ON, Canada</b></td><td>('30421594', 'Rinat Mukhometzianov', 'rinat mukhometzianov')<br/>('36957611', 'Juan Carrillo', 'juan carrillo')</td><td></td></tr><tr><td>cffebdf88e406c27b892857d1520cb2d7ccda573</td><td>LEARNING FROM LARGE-SCALE VISUAL DATA <br/>FOR ROBOTS <br/>A Dissertation <br/>Presented to the Faculty of the Graduate School @@ -11828,13 +14852,18 @@ <br/>by <br/>Ozan S¸ener <br/>August 2016 -</td><td></td><td></td></tr><tr><td>cfa572cd6ba8dfc2ee8ac3cc7be19b3abff1a8a2</td><td></td><td></td><td></td></tr><tr><td>cfd933f71f4a69625390819b7645598867900eab</td><td>INTERNATIONAL JOURNAL OF TECHNOLOGY ENHANCEMENTS AND EMERGING ENGINEERING RESEARCH, VOL 3, ISSUE 03 55 +</td><td></td><td></td></tr><tr><td>cfa572cd6ba8dfc2ee8ac3cc7be19b3abff1a8a2</td><td></td><td></td><td></td></tr><tr><td>cfffae38fe34e29d47e6deccfd259788176dc213</td><td>TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, DECEMBER 2012 +<br/>Matrix Completion for Weakly-supervised +<br/>Multi-label Image Classification +</td><td>('1707876', 'Fernando De la Torre', 'fernando de la torre')<br/>('2884203', 'Alexandre Bernardino', 'alexandre bernardino')</td><td></td></tr><tr><td>cfd4004054399f3a5f536df71f9b9987f060f434</td><td>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. ??, NO. ??, ?? 20?? +<br/>Person Recognition in Personal Photo Collections +</td><td>('2390510', 'Seong Joon Oh', 'seong joon oh')<br/>('1798000', 'Rodrigo Benenson', 'rodrigo benenson')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td></td></tr><tr><td>cfd933f71f4a69625390819b7645598867900eab</td><td>INTERNATIONAL JOURNAL OF TECHNOLOGY ENHANCEMENTS AND EMERGING ENGINEERING RESEARCH, VOL 3, ISSUE 03 55 <br/>ISSN 2347-4289 <br/>Person Authentication Using Face And Palm Vein: <br/>A Survey Of Recognition And Fusion Techniques <br/><b>College of Engineering, Pune, India</b><br/>Image Processing & Machine Vision Section, Electronics & Instrumentation Services Division, BARC </td><td>('38561481', 'Dhanashree Vaidya', 'dhanashree vaidya')<br/>('2623250', 'Madhuri A. Joshi', 'madhuri a. joshi')</td><td>Email: preethimedu@gmail.com, dvaidya33@gmail.com, hod.extc@coep.ac.in, maj.extc@coep.ac.in, skar@barc.gov.in -</td></tr><tr><td>cf875336d5a196ce0981e2e2ae9602580f3f6243</td><td>7 What 1 +</td></tr><tr><td>cfb8bc66502fb5f941ecdb22aec1fdbfdb73adce</td><td></td><td></td><td></td></tr><tr><td>cf875336d5a196ce0981e2e2ae9602580f3f6243</td><td>7 What 1 <br/>Rosalind W. Picard <br/>It Mean for a Computer to "Have" Emotions? <br/>There is a lot of talk about giving machines emotions, some of @@ -11885,15 +14914,66 @@ <br/>Qu´ebec, Canada </td><td>('2811524', 'Md. Kamrul Hasan', 'md. kamrul hasan')</td><td>md-kamrul.hasan@polymtl.ca <br/>christopher.pal@polymtl.ca -</td></tr><tr><td>cf5c9b521c958b84bb63bea9d5cbb522845e4ba7</td><td>Towards Arbitrary-View Face Alignment by Recommendation Trees∗ +</td></tr><tr><td>cfa92e17809e8d20ebc73b4e531a1b106d02b38c</td><td>Advances in Data Analysis and Classification manuscript No. +<br/>(will be inserted by the editor) +<br/>Parametric Classification with Soft Labels using the +<br/>Evidential EM Algorithm +<br/>Linear Discriminant Analysis vs. Logistic Regression +<br/>Received: date / Accepted: date +</td><td>('1772306', 'Benjamin Quost', 'benjamin quost')<br/>('2259794', 'Shoumei Li', 'shoumei li')</td><td></td></tr><tr><td>cf5c9b521c958b84bb63bea9d5cbb522845e4ba7</td><td>Towards Arbitrary-View Face Alignment by Recommendation Trees∗ <br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b><br/>2SenseTime Group </td><td>('2226254', 'Shizhan Zhu', 'shizhan zhu')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>zs014@ie.cuhk.edu.hk, chengli@sensetime.com, ccloy@ie.cuhk.edu.hk, xtang@ie.cuhk.edu.hk +</td></tr><tr><td>cf5a0115d3f4dcf95bea4d549ec2b6bdd7c69150</td><td>Detection of emotions from video in non-controlled +<br/>environment +<br/>To cite this version: +<br/>Processing. Universit´e Claude Bernard - Lyon I, 2013. English. <NNT : 2013LYO10227>. +<br/><tel-01166539v2> +<br/>HAL Id: tel-01166539 +<br/>https://tel.archives-ouvertes.fr/tel-01166539v2 +<br/>Submitted on 23 Jun 2015 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destin´ee au d´epˆot et `a la diffusion de documents +<br/>scientifiques de niveau recherche, publi´es ou non, +<br/>´emanant des ´etablissements d’enseignement et de +<br/>recherche fran¸cais ou ´etrangers, des laboratoires +<br/>publics ou priv´es. +</td><td>('1943666', 'Rizwan Ahmed Khan', 'rizwan ahmed khan')<br/>('1943666', 'Rizwan Ahmed Khan', 'rizwan ahmed khan')</td><td></td></tr><tr><td>cfdc632adcb799dba14af6a8339ca761725abf0a</td><td>Probabilistic Formulations of Regression with Mixed +<br/>Guidance +</td><td>('38688704', 'Aubrey Gress', 'aubrey gress')<br/>('38673135', 'Ian Davidson', 'ian davidson')</td><td>adgress@ucdavis.edu, davidson@cs.ucdavis.edu +</td></tr><tr><td>cfa931e6728a825caada65624ea22b840077f023</td><td>Deformable Generator Network: Unsupervised Disentanglement of +<br/>Appearance and Geometry +<br/><b>College of Automation, Harbin Engineering University, Heilongjiang, China</b><br/><b>University of California, Los Angeles, California, USA</b></td><td>('7306249', 'Xianglei Xing', 'xianglei xing')<br/>('9659905', 'Ruiqi Gao', 'ruiqi gao')<br/>('50495880', 'Tian Han', 'tian han')<br/>('3133970', 'Song-Chun Zhu', 'song-chun zhu')<br/>('39092098', 'Ying Nian Wu', 'ying nian wu')</td><td></td></tr><tr><td>cfc30ce53bfc204b8764ebb764a029a8d0ad01f4</td><td>Regularizing Deep Neural Networks by Noise: +<br/>Its Interpretation and Optimization +<br/>Dept. of Computer Science and Engineering, POSTECH, Korea +</td><td>('2018393', 'Hyeonwoo Noh', 'hyeonwoo noh')<br/>('2205770', 'Tackgeun You', 'tackgeun you')<br/>('8511875', 'Jonghwan Mun', 'jonghwan mun')<br/>('40030651', 'Bohyung Han', 'bohyung han')</td><td>{shgusdngogo,tackgeun.you,choco1916,bhhan}@postech.ac.kr +</td></tr><tr><td>cff911786b5ac884bb71788c5bc6acf6bf569eff</td><td>Multi-task Learning of Cascaded CNN for +<br/>Facial Attribute Classification +<br/><b>School of Information Science and Engineering, Xiamen University, Xiamen 361005, China</b><br/><b>School of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</b></td><td>('41034942', 'Ni Zhuang', 'ni zhuang')<br/>('40461734', 'Yan Yan', 'yan yan')<br/>('47336404', 'Si Chen', 'si chen')<br/>('37414077', 'Hanzi Wang', 'hanzi wang')</td><td>Email: ni.zhuang@foxmail.com, {yanyan, hanzi.wang}@xmu.edu.cn, chensi@xmut.edu.cn </td></tr><tr><td>cf09e2cb82961128302b99a34bff91ec7d198c7c</td><td>OFFICE ENTRANCE CONTROL WITH FACE RECOGNITION <br/> Dept. of Computer Science and Information Engineering, <br/><b>National Taiwan University, Taiwan</b><br/> Dept. of Computer Science and Information Engineering, <br/><b>National Taiwan University, Taiwan</b></td><td>('1721106', 'Yun-Che Tsai', 'yun-che tsai')<br/>('1703041', 'Chiou-Shann Fuh', 'chiou-shann fuh')</td><td>E-mail: jpm9ie8c@gmail.com <br/>E-mail: fuh@csie.ntu.edu.tw -</td></tr><tr><td>cf86616b5a35d5ee777585196736dfafbb9853b5</td><td>This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. +</td></tr><tr><td>cfc4aa456d9da1a6fabd7c6ca199332f03e35b29</td><td><b>University of Amsterdam and Renmin University at TRECVID</b><br/>Searching Video, Detecting Events and Describing Video +<br/><b>University of Amsterdam</b><br/><b>Zhejiang University</b><br/>Amsterdam, The Netherlands +<br/>Hangzhou, China +<br/><b>Renmin University of China</b><br/>Beijing, China +</td><td>('46741353', 'Cees G. M. Snoek', 'cees g. m. snoek')<br/>('40240283', 'Jianfeng Dong', 'jianfeng dong')<br/>('9931285', 'Xirong Li', 'xirong li')<br/>('48631563', 'Xiaoxu Wang', 'xiaoxu wang')<br/>('24332496', 'Qijie Wei', 'qijie wei')<br/>('2896042', 'Weiyu Lan', 'weiyu lan')<br/>('2304222', 'Efstratios Gavves', 'efstratios gavves')<br/>('13142264', 'Noureldien Hussein', 'noureldien hussein')<br/>('1769315', 'Dennis C. Koelma', 'dennis c. koelma')<br/>('1705182', 'Arnold W. M. Smeulders', 'arnold w. m. smeulders')</td><td></td></tr><tr><td>cf805d478aeb53520c0ab4fcdc9307d093c21e52</td><td>Finding Tiny Faces in the Wild with Generative Adversarial Network +<br/>Mingli Ding2 +<br/><b>Visual Computing Center, King Abdullah University of Science and Technology (KAUST</b><br/><b>School of Electrical Engineering and Automation, Harbin Institute of Technology (HIT</b><br/><b>Institute of Software, Chinese Academy of Sciences (CAS</b><br/>Figure1. The detection results of tiny faces in the wild. (a) is the original low-resolution blurry face, (b) is the result of +<br/>re-sizing directly by a bi-linear kernel, (c) is the generated image by the super-resolution method, and our result (d) is learned +<br/>by the super-resolution (×4 upscaling) and refinement network simultaneously. Best viewed in color and zoomed in. +</td><td>('2860057', 'Yancheng Bai', 'yancheng bai')<br/>('48378890', 'Yongqiang Zhang', 'yongqiang zhang')<br/>('2931652', 'Bernard Ghanem', 'bernard ghanem')</td><td>baiyancheng20@gmail.com +<br/>{zhangyongqiang, dingml}@hit.edu.cn +<br/>bernard.ghanem@kaust.edu.sa +</td></tr><tr><td>cfdc4d0f8e1b4b9ced35317d12b4229f2e3311ab</td><td>Quaero at TRECVID 2010: Semantic Indexing +<br/>1UJF-Grenoble 1 / UPMF-Grenoble 2 / Grenoble INP / CNRS, LIG UMR 5217, Grenoble, F-38041, France +<br/><b>Karlsruhe Institute of Technology, P.O. Box 3640, 76021 Karlsruhe, Germany</b></td><td>('2357942', 'Bahjat Safadi', 'bahjat safadi')<br/>('1921500', 'Yubing Tong', 'yubing tong')<br/>('1981024', 'Franck Thollard', 'franck thollard')<br/>('40303076', 'Tobias Gehrig', 'tobias gehrig')<br/>('3025777', 'Hazim Kemal Ekenel', 'hazim kemal ekenel')</td><td></td></tr><tr><td>cf86616b5a35d5ee777585196736dfafbb9853b5</td><td>This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. <br/>Learning Multiscale Active Facial Patches for <br/>Expression Analysis </td><td>('29803023', 'Lin Zhong', 'lin zhong')<br/>('1734954', 'Qingshan Liu', 'qingshan liu')<br/>('39606160', 'Peng Yang', 'peng yang')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td></td></tr><tr><td>cacd51221c592012bf2d9e4894178c1c1fa307ca</td><td> @@ -11921,7 +15001,18 @@ <br/>Weighted Interactions from Other Attributes <br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition <br/><b>Institute of Automation, Chinese Academy of Sciences</b></td><td>('1739258', 'Jianqing Zhu', 'jianqing zhu')<br/>('40397682', 'Shengcai Liao', 'shengcai liao')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>jianqingzhu@foxmail.com, {scliao, zlei, szli}@cbsr.ia.ac.cn -</td></tr><tr><td>cadba72aa3e95d6dcf0acac828401ddda7ed8924</td><td>THÈSE PRÉSENTÉE À LA FACULTÉ DES SCIENCES +</td></tr><tr><td>cad24ba99c7b6834faf6f5be820dd65f1a755b29</td><td>Understanding hand-object +<br/>manipulation by modeling the +<br/>contextual relationship between actions, +<br/>grasp types and object attributes +<br/>Journal Title +<br/>XX(X):1–14 +<br/>c(cid:13)The Author(s) 2016 +<br/>Reprints and permission: +<br/>sagepub.co.uk/journalsPermissions.nav +<br/>DOI: 10.1177/ToBeAssigned +<br/>www.sagepub.com/ +</td><td>('3172280', 'Minjie Cai', 'minjie cai')<br/>('37991449', 'Kris M. Kitani', 'kris m. kitani')<br/>('9467266', 'Yoichi Sato', 'yoichi sato')</td><td></td></tr><tr><td>cadba72aa3e95d6dcf0acac828401ddda7ed8924</td><td>THÈSE PRÉSENTÉE À LA FACULTÉ DES SCIENCES <br/>POUR L’OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES <br/>Algorithms and VLSI Architectures <br/>for Low-Power Mobile Face Verification @@ -11935,7 +15026,9 @@ <br/>INSTITUT DE MICROTECHNIQUE <br/>UNIVERSITÉ DE NEUCHÂTEL <br/>2006 -</td><td>('1844418', 'Jean-Luc Nagel', 'jean-luc nagel')</td><td></td></tr><tr><td>ca606186715e84d270fc9052af8500fe23befbda</td><td>Using Subclass Discriminant Analysis, Fuzzy Integral and Symlet Decomposition for +</td><td>('1844418', 'Jean-Luc Nagel', 'jean-luc nagel')</td><td></td></tr><tr><td>ca37eda56b9ee53610c66951ee7ca66a35d0a846</td><td>Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection +<br/><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney</b><br/><b>Language Technologies Institute, Carnegie Mellon University</b><br/><b>Carnegie Mellon University</b></td><td>('1729163', 'Xiaojun Chang', 'xiaojun chang')<br/>('39033919', 'Yi Yang', 'yi yang')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')<br/>('1752601', 'Eric P. Xing', 'eric p. xing')</td><td>{cxj273, yee.i.yang}@gmail.com, {alex, epxing, yaoliang}@cs.cmu.edu +</td></tr><tr><td>ca606186715e84d270fc9052af8500fe23befbda</td><td>Using Subclass Discriminant Analysis, Fuzzy Integral and Symlet Decomposition for <br/>Face Recognition <br/>Department of Electrical Engineering, <br/>Iran Univ. of Science and Technology, @@ -12023,6 +15116,24 @@ <br/>Weighted Feature Extraction and Fuzzy Classifier </td><td>('2121174', 'Maryam Imani', 'maryam imani')<br/>('1801348', 'Gholam Ali Montazer', 'gholam ali montazer')</td><td></td></tr><tr><td>e4391993f5270bdbc621b8d01702f626fba36fc2</td><td>Author manuscript, published in "18th Scandinavian Conference on Image Analysis (2013)" <br/> DOI : 10.1007/978-3-642-38886-6_31 +</td><td></td><td></td></tr><tr><td>e43045a061421bd79713020bc36d2cf4653c044d</td><td>A New Representation of Skeleton Sequences for 3D Action Recognition +<br/><b>The University of Western Australia</b><br/><b>Murdoch University</b></td><td>('2796959', 'Qiuhong Ke', 'qiuhong ke')<br/>('1698675', 'Mohammed Bennamoun', 'mohammed bennamoun')<br/>('1782428', 'Senjian An', 'senjian an')</td><td>qiuhong.ke@research.uwa.edu.au +<br/>{mohammed.bennamoun,senjian.an,farid.boussaid}@uwa.edu.au +<br/>f.sohel@murdoch.edu.au +</td></tr><tr><td>e4d8ba577cabcb67b4e9e1260573aea708574886</td><td>UM SISTEMA DE RECOMENDAC¸ ˜AO INTELIGENTE BASEADO EM V´IDIO +<br/>AULAS PARA EDUCAC¸ ˜AO A DIST ˆANCIA +<br/>Gaspare Giuliano Elias Bruno +<br/>Tese de Doutorado apresentada ao Programa +<br/>de P´os-gradua¸c˜ao em Engenharia de Sistemas e +<br/>Computa¸c˜ao, COPPE, da Universidade Federal +<br/>do Rio de Janeiro, como parte dos requisitos +<br/>necess´arios `a obten¸c˜ao do t´ıtulo de Doutor em +<br/>Engenharia de Sistemas e Computa¸c˜ao. +<br/>Orientadores: Edmundo Albuquerque de +<br/>Souza e Silva +<br/>Rosa Maria Meri Le˜ao +<br/>Rio de Janeiro +<br/>Janeiro de 2016 </td><td></td><td></td></tr><tr><td>e475deadd1e284428b5e6efd8fe0e6a5b83b9dcd</td><td>Accepted in Pattern Recognition Letters <br/>Pattern Recognition Letters <br/>journal homepage: www.elsevier.com @@ -12031,7 +15142,12 @@ <br/>IIIT-Delhi, New Delhi, 110020, India <br/>Article history: <br/>Received 15 March 2017 -</td><td>('2220719', 'Maneet Singh', 'maneet singh')<br/>('1925017', 'Shruti Nagpal', 'shruti nagpal')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('39129417', 'Richa Singh', 'richa singh')</td><td></td></tr><tr><td>e4d0e87d0bd6ead4ccd39fc5b6c62287560bac5b</td><td>Implicit Video Multi-Emotion Tagging by Exploiting Multi-Expression +</td><td>('2220719', 'Maneet Singh', 'maneet singh')<br/>('1925017', 'Shruti Nagpal', 'shruti nagpal')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('39129417', 'Richa Singh', 'richa singh')</td><td></td></tr><tr><td>e4abc40f79f86dbc06f5af1df314c67681dedc51</td><td>Head Detection with Depth Images in the Wild +<br/>Department of Engineering ”Enzo Ferrari” +<br/><b>University of Modena and Reggio Emilia, Italy</b><br/>Keywords: +<br/>Head Detection, Head Localization, Depth Maps, Convolutional Neural Network +</td><td>('6125279', 'Diego Ballotta', 'diego ballotta')<br/>('12010968', 'Guido Borghi', 'guido borghi')<br/>('1723285', 'Roberto Vezzani', 'roberto vezzani')<br/>('1741922', 'Rita Cucchiara', 'rita cucchiara')</td><td>{name.surname}@unimore.it +</td></tr><tr><td>e4d0e87d0bd6ead4ccd39fc5b6c62287560bac5b</td><td>Implicit Video Multi-Emotion Tagging by Exploiting Multi-Expression <br/>Relations </td><td>('1771215', 'Zhilei Liu', 'zhilei liu')<br/>('1791319', 'Shangfei Wang', 'shangfei wang')<br/>('3558606', 'Zhaoyu Wang', 'zhaoyu wang')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td></td></tr><tr><td>e48e94959c4ce799fc61f3f4aa8a209c00be8d7f</td><td>Hindawi Publishing Corporation <br/>The Scientific World Journal @@ -12135,7 +15251,58 @@ <br/>www.iosrjournals.org <br/>Performance Evaluation of Gabor Wavelet Features for Face <br/>Representation and Recognition -<br/><b>Bapuji Institute of Engineering and Technology Davanagere, Karnataka, India</b><br/><b>University B.D.T.College of Engineering, Visvesvaraya</b><br/><b>Technological University, Davanagere, Karnataka, India</b></td><td>('2038371', 'M. E. Ashalatha', 'm. e. ashalatha')<br/>('3283067', 'Mallikarjun S. Holi', 'mallikarjun s. holi')</td><td></td></tr><tr><td>fe5df5fe0e4745d224636a9ae196649176028990</td><td><b>University of Massachusetts - Amherst</b><br/>Dissertations +<br/><b>Bapuji Institute of Engineering and Technology Davanagere, Karnataka, India</b><br/><b>University B.D.T.College of Engineering, Visvesvaraya</b><br/><b>Technological University, Davanagere, Karnataka, India</b></td><td>('2038371', 'M. E. Ashalatha', 'm. e. ashalatha')<br/>('3283067', 'Mallikarjun S. Holi', 'mallikarjun s. holi')</td><td></td></tr><tr><td>fe464b2b54154d231671750053861f5fd14454f5</td><td>Multi Joint Action in CoTeSys +<br/>- Setup and Challenges - +<br/>Technical report CoTeSys-TR-10-01 +<br/>D. Brˇsˇci´c, F. Rohrm¨uller, O. Kourakos, S. Sosnowski, D. Althoff, M. Lawitzky, +<br/>{drazen, rohrm, omirosk, sosnowski, dalthoff, lawitzky, moertl, rambow, vicky, +<br/>M. Eggers, C. Mayer, T. Kruse, A. Kirsch, M. Beetz and B. Radig 2 +<br/>T. Lorenz and A. Schub¨o 4 +<br/>P. Basili and S. Glasauer 5 +<br/>W. Maier and E. Steinbach 7 +<br/><b>Institute of Automatic Control</b><br/>4 Experimental Psychology Unit +<br/>Engineering +<br/>Department of Psychology +<br/>Department of Electrical Engineering +<br/>Ludwig-Maximilians-Universit¨at +<br/>and Information Technology +<br/>Technische Universit¨at M¨unchen +<br/>Arcisstraße 21, 80333 M¨unchen +<br/>2Intelligent Autonomous Systems +<br/>Department of Informatics +<br/>M¨unchen +<br/>Leopoldstraße 13, 80802 M¨unchen +<br/>5Center for Sensorimotor Research +<br/>Clinical Neurosciences and +<br/>Department of Neurology +<br/>Technische Universit¨at M¨unchen +<br/>Ludwig-Maximilians-Universit¨at +<br/>Boltzmannstraße 3, 85748 Garching +<br/>M¨unchen +<br/>bei M¨unchen +<br/>Marchionistraße 23, 81377 M¨unchen +<br/><b>Institute for Human-Machine</b><br/>6Robotics and Embedded Systems +<br/>Communication +<br/>Department of Informatics +<br/>Department of Electrical Engineering +<br/>Technische Universit¨at M¨unchen +<br/>and Information Technology +<br/>Boltzmannstraße 3, 85748 Garching +<br/>Technische Universit¨at M¨unchen +<br/>Arcisstraße 21, 80333 M¨unchen +<br/>bei M¨unchen +<br/><b>Institute for Media Technology</b><br/>Department of Electrical Engineering +<br/>and Information Technology +<br/>Technische Universit¨at M¨unchen +<br/>Arcisstraße 21, 80333 M¨unchen +</td><td>('46953125', 'X. Zang', 'x. zang')<br/>('47824592', 'W. Wang', 'w. wang')<br/>('48172476', 'A. Bannat', 'a. bannat')<br/>('30849638', 'G. Panin', 'g. panin')</td><td>medina, xueliang zang, wangwei, dirk, kuehnlen, hirche, buss}@lsr.ei.tum.de +<br/>{eggers, mayerc, kruset, kirsch, beetz, radig}@in.tum.de +<br/>{blume, bannat, rehrl, wallhoff}@tum.de +<br/>{lorenz, schuboe}@psy.lmu.de +<br/>{p.basili,s.glasauer}@lrz.uni-muenchen.de +<br/>{lenz,roeder,panin,knoll}@in.tum.de +<br/>{werner.maier, eckehard.steinbach}@tum.de +</td></tr><tr><td>fe7c0bafbd9a28087e0169259816fca46db1a837</td><td></td><td></td><td></td></tr><tr><td>fe5df5fe0e4745d224636a9ae196649176028990</td><td><b>University of Massachusetts - Amherst</b><br/>Dissertations <br/>9-1-2010 <br/>Dissertations and Theses <br/>Using Context to Enhance the Understanding of @@ -12183,6 +15350,11 @@ <br/>mhussain@ksu.edu.sa <br/>ghulam@ksu.edu.sa <br/>anwar.m.mirza@gmail.com +</td></tr><tr><td>fe48f0e43dbdeeaf4a03b3837e27f6705783e576</td><td></td><td></td><td></td></tr><tr><td>fea83550a21f4b41057b031ac338170bacda8805</td><td>Learning a Metric Embedding +<br/>for Face Recognition +<br/>using the Multibatch Method +<br/>Orcam Ltd., Jerusalem, Israel +</td><td>('46273386', 'Oren Tadmor', 'oren tadmor')<br/>('1743988', 'Yonatan Wexler', 'yonatan wexler')<br/>('31601132', 'Tal Rosenwein', 'tal rosenwein')<br/>('2554670', 'Shai Shalev-Shwartz', 'shai shalev-shwartz')<br/>('3140335', 'Amnon Shashua', 'amnon shashua')</td><td>firstname.lastname@orcam.com </td></tr><tr><td>feeb0fd0e254f38b38fe5c1022e84aa43d63f7cc</td><td>EURECOM <br/>Multimedia Communications Department <br/>and @@ -12198,7 +15370,13 @@ <br/>Last update June 1st, 2011 <br/>1EURECOM’s research is partially supported by its industrial members: BMW Group, Cisco, <br/>Monaco Telecom, Orange, SAP, SFR, Sharp, STEricsson, Swisscom, Symantec, Thales. -</td><td>('3299530', 'Antitza Dantcheva', 'antitza dantcheva')<br/>('15758502', 'Arun Singh', 'arun singh')<br/>('1688531', 'Petros Elia', 'petros elia')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td></td></tr><tr><td>fe108803ee97badfa2a4abb80f27fa86afd9aad9</td><td></td><td></td><td></td></tr><tr><td>c8db8764f9d8f5d44e739bbcb663fbfc0a40fb3d</td><td>Modeling for part-based visual object +</td><td>('3299530', 'Antitza Dantcheva', 'antitza dantcheva')<br/>('15758502', 'Arun Singh', 'arun singh')<br/>('1688531', 'Petros Elia', 'petros elia')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td></td></tr><tr><td>fe108803ee97badfa2a4abb80f27fa86afd9aad9</td><td></td><td></td><td></td></tr><tr><td>fe0c51fd41cb2d5afa1bc1900bbbadb38a0de139</td><td>Rahman et al. EURASIP Journal on Image and Video Processing (2015) 2015:35 +<br/>DOI 10.1186/s13640-015-0090-5 +<br/>RESEARCH +<br/>Open Access +<br/>Bayesian face recognition using 2D +<br/>Gaussian-Hermite moments +</td><td>('47081388', 'S. M. Mahbubur Rahman', 's. m. mahbubur rahman')<br/>('2021126', 'Tamanna Howlader', 'tamanna howlader')</td><td></td></tr><tr><td>c8db8764f9d8f5d44e739bbcb663fbfc0a40fb3d</td><td>Modeling for part-based visual object <br/>detection based on local features <br/>Von der Fakult¨at f¨ur Elektrotechnik und Informationstechnik <br/>der Rheinisch-Westf¨alischen Technischen Hochschule Aachen @@ -12213,15 +15391,210 @@ <br/>Tag der m¨undlichen Pr¨ufung: 28. September 2011 <br/>Diese Dissertation ist auf den Internetseiten der <br/>Hochschulbibliothek online verf¨ugbar. -</td><td>('2447988', 'Mark Asbach', 'mark asbach')</td><td></td></tr><tr><td>c8a4b4fe5ff2ace9ab9171a9a24064b5a91207a3</td><td>LOCATING FACIAL LANDMARKS WITH BINARY MAP CROSS-CORRELATIONS +</td><td>('2447988', 'Mark Asbach', 'mark asbach')</td><td></td></tr><tr><td>c86e6ed734d3aa967deae00df003557b6e937d3d</td><td>Generative Adversarial Networks with +<br/>Decoder-Encoder Output Noise +<br/>conditional distribution of their neighbors. In [32], Portilla and +<br/>Simoncelli proposed a parametric texture model based on joint +<br/>statistics, which uses a decomposition method that is called +<br/>steerable pyramid decomposition to decompose the texture +<br/>of images. An example-based super-resolution algorithm [11] +<br/>was proposed in 2002, which uses a Markov network to model +<br/>the spatial relationship between the pixels of an image. A +<br/>scene completion algorithm [16] was proposed in 2007, which +<br/>applied a semantic scene match technique. These traditional +<br/>algorithms can be applied to particular image generation tasks, +<br/>such as texture synthesis and super-resolution. Their common +<br/>characteristic is that they predict the images pixel by pixel +<br/>rather than generate an image as a whole, and the basic idea +<br/>of them is to make an interpolation according to the existing +<br/>part of the images. Here, the problem is, given a set of images, +<br/>can we generate totally new images with the same distribution +<br/>of the given ones? +</td><td>('2421012', 'Guoqiang Zhong', 'guoqiang zhong')<br/>('46874300', 'Wei Gao', 'wei gao')<br/>('3142351', 'Yongbin Liu', 'yongbin liu')<br/>('47796538', 'Youzhao Yang', 'youzhao yang')</td><td></td></tr><tr><td>c8a4b4fe5ff2ace9ab9171a9a24064b5a91207a3</td><td>LOCATING FACIAL LANDMARKS WITH BINARY MAP CROSS-CORRELATIONS <br/>J´er´emie Nicolle <br/>K´evin Bailly <br/>Univ. Pierre & Marie Curie, ISIR - CNRS UMR 7222, F-75005, Paris - France </td><td>('3074790', 'Vincent Rapp', 'vincent rapp')<br/>('1680828', 'Mohamed Chetouani', 'mohamed chetouani')</td><td>{nicolle, bailly, rapp, chetouani}@isir.upmc.fr +</td></tr><tr><td>c87f7ee391d6000aef2eadb49f03fc237f4d1170</td><td>1 +<br/>A real-time and unsupervised face Re-Identification system for Human-Robot +<br/>Interaction +<br/><b>Intelligent Behaviour Understanding Group, Imperial College London, London, UK</b><br/>A B S T R A C T +<br/>In the context of Human-Robot Interaction (HRI), face Re-Identification (face Re-ID) aims to verify if certain detected faces have already been +<br/>observed by robots. The ability of distinguishing between different users is crucial in social robots as it will enable the robot to tailor the interaction +<br/>strategy toward the users’ individual preferences. So far face recognition research has achieved great success, however little attention has been paid +<br/>to the realistic applications of Face Re-ID in social robots. In this paper, we present an effective and unsupervised face Re-ID system which +<br/>simultaneously re-identifies multiple faces for HRI. This Re-ID system employs Deep Convolutional Neural Networks to extract features, and an +<br/>online clustering algorithm to determine the face’s ID. Its performance is evaluated on two datasets: the TERESA video dataset collected by the +<br/>TERESA robot, and the YouTube Face Dataset (YTF Dataset). We demonstrate that the optimised combination of techniques achieves an overall +<br/>93.55% accuracy on TERESA dataset and an overall 90.41% accuracy on YTF dataset. We have implemented the proposed method into a software +<br/>module in the HCI^2 Framework [1] for it to be further integrated into the TERESA robot [2], and has achieved real-time performance at 10~26 +<br/>Frames per second. +<br/>Keywords: Real-Time Face Re-Identification, Open Set Re-ID, Multiple Re-ID, Human-Robot Interaction, CNN Descriptors, Online Clustering +<br/>1. Introduction +<br/>Face recognition problem is one of the oldest topics in +<br/>Computer Vision [3]. Recently, the interest in this problem has +<br/>been revamped, mostly due to the observation that standard face +<br/>recognition approaches do not perform well in real-time +<br/>scenarios where faces can be rotated, occluded, and under +<br/>unconstrained illumination. Face recognition tasks are generally +<br/>classified into two categories: +<br/>1. Face Verification. Given two face images, the task of face +<br/>verification is to determine if these two faces belong to the same +<br/>person. +<br/>2. Face Identification. This refers to the process of finding the +<br/>identity of an unknown face image given a database of known +<br/>faces. +<br/>However, there are certain situations where a third type of +<br/>face recognition is needed: face re-identification (face Re-ID). In +<br/>the context of Human-Robot Interaction (HRI), the goal of face +<br/>Re-ID is to determine if certain faces have been seen by the robot +<br/>before, and if so, to determine their identity. +<br/>Generally, a real-time and unsupervised face re-identification +<br/>system is required to achieve effective interactions between +<br/>humans and robots. In the realistic scenarios of HRI, the face re- +<br/>identification task is confronted with the following challenges: +<br/>a. The system needs to be able to build and update the run- +<br/>time user gallery on the fly as there is usually no prior +<br/>knowledge about the interaction targets in advance. +<br/>b. The system should achieve high processing speed in +<br/>order for the robot to maintain real-time interaction with +<br/>the users. +<br/>c. The method should be robust against high intra-class +<br/>illumination changes, partial +<br/>variance caused by +<br/> +<br/>occlusion, pose variation, and/or the display of facial +<br/>expressions. +<br/>d. The system should achieve high recognition accuracy on +<br/>low-quality images resulted from motion blur (when the +<br/>robot and / or the user is moving), out-of-focus blur, +<br/>and/or over /under-exposure. +<br/>Recently, deep-learning approaches, especially Convolutional +<br/>Neural Networks (CNNs), have achieved great success in solving +<br/>face recognition problems [4]–[8]. Comparing +<br/>to classic +<br/>approaches, deep-learning-based methods are characterised by +<br/>their powerful feature extraction abilities. However, as existing +<br/>works mostly focused on traditional face identification problems, +<br/>the potential applications of deep-learning-based methods in +<br/>solving face Re-ID problems is yet to be explored. +<br/>that can work effectively +<br/>In this paper, we present a real-time unsupervised face re- +<br/>identification system +<br/>in an +<br/>unconstrained environment. Firstly, we employ a pre-trained +<br/>CNN [7] as the feature extractor and try to improve its +<br/>performance and processing speed in HRI context by utilising a +<br/>variety of pre-processing techniques. In the Re-Identification step, +<br/>we then use an online clustering algorithm to build and update a +<br/>run-time face gallery and to output the probe faces’ ID. +<br/>Experiments show that our system can achieve a Re-ID accuracy +<br/>of 93.55% and 90.41% on the TERESA video dataset and the +<br/>YTF Dataset respectively and is able to achieve a real-time +<br/>processing speed of 10~26 FPS. +<br/>2. Related Works +<br/>Various methods [9]–[15] have been developed to solve the +<br/>person Re-ID problem in surveillance context. However, most of +<br/>them [9]–[13] are unsuitable to HRI applications as these +<br/>approaches often rely on soft biometrics (i.e. clothing’s colours +<br/>and textures) that are unavailable to the robot (which usually only +<br/>sees the user’s face). Due to the unavailability of such soft +<br/>biometrics, it is difficult to apply person re-identification +</td><td>('2563750', 'Yujiang Wang', 'yujiang wang')<br/>('49927631', 'Jie Shen', 'jie shen')<br/>('2403354', 'Stavros Petridis', 'stavros petridis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>c866a2afc871910e3282fd9498dce4ab20f6a332</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Surveillance Face Recognition Challenge +<br/>Received: date / Accepted: date +</td><td>('5314735', 'Zhiyi Cheng', 'zhiyi cheng')</td><td></td></tr><tr><td>c8ca6a2dc41516c16ea0747e9b3b7b1db788dbdd</td><td>1 Department of Computer Science +<br/><b>Rutgers University</b><br/>New Jersey, USA +<br/>2 Department of Computer Science +<br/><b>The University of Texas at Arlington</b><br/>Texas, USA +<br/>PENG, XI: TRACK FACIAL POINTS IN UNCONSTRAINED VIDEOS +<br/>Track Facial Points in Unconstrained Videos +</td><td>('4340744', 'Xi Peng', 'xi peng')<br/>('40420376', 'Qiong Hu', 'qiong hu')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>xipeng.cs@rutgers.edu +<br/>qionghu.cs@rutgers.edu +<br/>jzhuang@uta.edu +<br/>dnm@cs.rutgers.edu </td></tr><tr><td>c8292aa152a962763185e12fd7391a1d6df60d07</td><td>Camera Distance from Face Images <br/><b>University of California, San Diego</b><br/>9500 Gilman Drive, La Jolla, CA, USA </td><td>('25234832', 'Arturo Flores', 'arturo flores')</td><td>{aflores,echristiansen,kriegman,sjb}@cs.ucsd.edu -</td></tr><tr><td>c82c147c4f13e79ad49ef7456473d86881428b89</td><td></td><td></td><td></td></tr><tr><td>c8e84cdff569dd09f8d31e9f9ba3218dee65e961</td><td>Dictionaries for Image and Video-based Face Recognition +</td></tr><tr><td>c82c147c4f13e79ad49ef7456473d86881428b89</td><td></td><td></td><td></td></tr><tr><td>c84233f854bbed17c22ba0df6048cbb1dd4d3248</td><td>Exploring Locally Rigid Discriminative +<br/>Patches for Learning Relative Attributes +<br/>http://researchweb.iiit.ac.in/~yashaswi.verma/ +<br/>http://www.iiit.ac.in/~jawahar/ +<br/>CVIT +<br/>IIIT-Hyderabad, India +<br/>http://cvit.iiit.ac.in +</td><td>('1694502', 'C. V. Jawahar', 'c. v. jawahar')<br/>('2169614', 'Yashaswi Verma', 'yashaswi verma')<br/>('1694502', 'C. V. Jawahar', 'c. v. jawahar')</td><td></td></tr><tr><td>c829be73584966e3162f7ccae72d9284a2ebf358</td><td>shuttleNet: A biologically-inspired RNN with loop connection and parameter +<br/>sharing +<br/>1 National Engineering Laboratory for Video Technology, School of EE&CS, +<br/><b>Peking University, Beijing, China</b><br/>2 Cooperative Medianet Innovation Center, China +<br/>3 School of Information and Electronics, +<br/><b>Beijing Institute of Technology, Beijing, China</b></td><td>('38179026', 'Yemin Shi', 'yemin shi')<br/>('1705972', 'Yonghong Tian', 'yonghong tian')<br/>('5765799', 'Yaowei Wang', 'yaowei wang')<br/>('34097174', 'Tiejun Huang', 'tiejun huang')</td><td></td></tr><tr><td>c87d5036d3a374c66ec4f5870df47df7176ce8b9</td><td>ORIGINAL RESEARCH +<br/>published: 12 July 2018 +<br/>doi: 10.3389/fpsyg.2018.01190 +<br/>Temporal Dynamics of Natural Static +<br/>Emotional Facial Expressions +<br/>Decoding: A Study Using Event- and +<br/>Eye Fixation-Related Potentials +<br/><b>GIPSA-lab, Institute of Engineering, Universit Grenoble Alpes, Centre National de la Recherche Scienti que, Grenoble INP</b><br/>Grenoble, France, 2 Department of Conception and Control of Aeronautical and Spatial Vehicles, Institut Supérieur de +<br/>l’Aéronautique et de l’Espace, Université Fédérale de Toulouse, Toulouse, France, 3 Laboratoire InterUniversitaire de +<br/>Psychologie – Personnalité, Cognition, Changement Social, Université Grenoble Alpes, Université Savoie Mont Blanc, +<br/>Grenoble, France, 4 Exploration Fonctionnelle du Système Nerveux, Pôle Psychiatrie, Neurologie et Rééducation +<br/>Neurologique, CHU Grenoble Alpes, Grenoble, France, 5 Université Grenoble Alpes, Inserm, CHU Grenoble Alpes, Grenoble +<br/>Institut des Neurosciences, Grenoble, France +<br/>This study aims at examining the precise temporal dynamics of the emotional facial +<br/>decoding as it unfolds in the brain, according to the emotions displayed. To characterize +<br/>this processing as it occurs in ecological settings, we focused on unconstrained visual +<br/>explorations of natural emotional faces (i.e., free eye movements). The General Linear +<br/>Model (GLM; Smith and Kutas, 2015a,b; Kristensen et al., 2017a) enables such a +<br/>depiction. It allows deconvolving adjacent overlapping responses of the eye fixation- +<br/>related potentials (EFRPs) elicited by the subsequent fixations and the event-related +<br/>potentials (ERPs) elicited at the stimuli onset. Nineteen participants were displayed +<br/>with spontaneous static facial expressions of emotions (Neutral, Disgust, Surprise, and +<br/>Happiness) from the DynEmo database (Tcherkassof et al., 2013). Behavioral results +<br/>on participants’ eye movements show that the usual diagnostic features in emotional +<br/>decoding (eyes for negative facial displays and mouth for positive ones) are consistent +<br/>with the literature. The impact of emotional category on both the ERPs and the EFRPs +<br/>elicited by the free exploration of the emotional faces is observed upon the temporal +<br/>dynamics of the emotional facial expression processing. Regarding the ERP at stimulus +<br/>onset, there is a significant emotion-dependent modulation of the P2–P3 complex +<br/>and LPP components’ amplitude at the left frontal site for the ERPs computed by +<br/>averaging. Yet, the GLM reveals the impact of subsequent fixations on the ERPs time- +<br/>locked on stimulus onset. Results are also in line with the valence hypothesis. The +<br/>observed differences between the two estimation methods (Average vs. GLM) suggest +<br/>the predominance of the right hemisphere at the stimulus onset and the implication +<br/>of the left hemisphere in the processing of the information encoded by subsequent +<br/>fixations. Concerning the first EFRP, the Lambda response and the P2 component are +<br/>modulated by the emotion of surprise compared to the neutral emotion, suggesting +<br/>Edited by: +<br/>Eva G. Krumhuber, +<br/><b>University College London</b><br/>United Kingdom +<br/>Reviewed by: +<br/>Marie Arsalidou, +<br/><b>National Research University Higher</b><br/>School of Economics, Russia +<br/>Jaana Simola, +<br/><b>University of Helsinki, Finland</b><br/>*Correspondence: +<br/>Specialty section: +<br/>This article was submitted to +<br/>Emotion Science, +<br/>a section of the journal +<br/>Frontiers in Psychology +<br/>Received: 07 March 2018 +<br/>Accepted: 20 June 2018 +<br/>Published: 12 July 2018 +<br/>Citation: +<br/>Guérin-Dugué A, Roy RN, +<br/>Kristensen E, Rivet B, Vercueil L and +<br/>Tcherkassof A (2018) Temporal +<br/>Dynamics of Natural Static Emotional +<br/>Facial Expressions Decoding: A Study +<br/>Using Event- and Eye Fixation-Related +<br/>Potentials. Front. Psychol. 9:1190. +<br/>doi: 10.3389/fpsyg.2018.01190 +<br/>Frontiers in Psychology | www.frontiersin.org +<br/>July 2018 | Volume 9 | Article 1190 +</td><td>('7200702', 'Anne Guérin-Dugué', 'anne guérin-dugué')<br/>('20903548', 'Raphaëlle N. Roy', 'raphaëlle n. roy')<br/>('33987947', 'Emmanuelle Kristensen', 'emmanuelle kristensen')<br/>('48223466', 'Bertrand Rivet', 'bertrand rivet')<br/>('2544058', 'Laurent Vercueil', 'laurent vercueil')<br/>('3209946', 'Anna Tcherkassof', 'anna tcherkassof')<br/>('7200702', 'Anne Guérin-Dugué', 'anne guérin-dugué')</td><td>anne.guerin@gipsa-lab.grenoble-inp.fr +</td></tr><tr><td>c8e84cdff569dd09f8d31e9f9ba3218dee65e961</td><td>Dictionaries for Image and Video-based Face Recognition <br/><b>Center for Automation Research, UMIACS, University of Maryland, College Park, MD 20742, USA</b><br/><b>National Institute of Standards and Technology, Gaithersburg, MD 20899, USA</b><br/>In recent years, sparse representation and dictionary learning-based methods have emerged as <br/>powerful tools for efficiently processing data in non-traditional ways. A particular area of promise <br/>for these theories is face recognition. @@ -12319,7 +15692,15 @@ <br/>Labeled Facial Images <br/><b>Savitribai Phule Pune University</b><br/><b>D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune</b><br/>Mahatma Phulenagar, 120/2 Mahaganpati soc, Chinchwad, Pune-19, MH, India <br/><b>D.Y.Patil Institute of Engineering and Technology, Pimpri, Pune-18, Savitribai Phule Pune University</b><br/>DYPIET, Pimpri, Pune-18, MH, India -</td><td>('15731441', 'Shital Shinde', 'shital shinde')<br/>('3392505', 'Archana Chaugule', 'archana chaugule')</td><td></td></tr><tr><td>c88ce5ef33d5e544224ab50162d9883ff6429aa3</td><td>Face Match for Family Reunification: +</td><td>('15731441', 'Shital Shinde', 'shital shinde')<br/>('3392505', 'Archana Chaugule', 'archana chaugule')</td><td></td></tr><tr><td>c83a05de1b4b20f7cd7cd872863ba2e66ada4d3f</td><td>BREUER, KIMMEL: A DEEP LEARNING PERSPECTIVE ON FACIAL EXPRESSIONS +<br/>A Deep Learning Perspective on the Origin +<br/>of Facial Expressions +<br/>Department of Computer Science +<br/><b>Technion - Israel Institute of Technology</b><br/>Technion City, Haifa, Israel +<br/>Figure 1: Demonstration of the filter visualization process. +</td><td>('50484701', 'Ran Breuer', 'ran breuer')<br/>('1692832', 'Ron Kimmel', 'ron kimmel')</td><td>rbreuer@cs.technion.ac.il +<br/>ron@cs.technion.ac.il +</td></tr><tr><td>c88ce5ef33d5e544224ab50162d9883ff6429aa3</td><td>Face Match for Family Reunification: <br/>Real-world Face Image Retrieval <br/>U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA <br/><b>Central Washington University, 400 E. University Way, Ellensburg, WA 98926, USA</b></td><td>('1744255', 'Eugene Borovikov', 'eugene borovikov')<br/>('34928283', 'Michael Gill', 'michael gill')<br/>('35029039', 'Szilárd Vajda', 'szilárd vajda')</td><td>(FaceMatch@NIH.gov) @@ -12329,33 +15710,194 @@ <br/>Department of Computer Science and Engineering <br/><b>The Chinese University of Hong Kong</b><br/>Shatin, Hong Kong </td><td>('2899702', 'Ho-Man Tang', 'ho-man tang')<br/>('1681775', 'Michael R. Lyu', 'michael r. lyu')<br/>('1706259', 'Irwin King', 'irwin king')</td><td>fhmtang, lyu, kingg@cse.cuhk.edu.hk -</td></tr><tr><td>c8adbe00b5661ab9b3726d01c6842c0d72c8d997</td><td>Deep Architectures for Face Attributes +</td></tr><tr><td>c88c21eb9a8e08b66c981db35f6556f4974d27a8</td><td>Attribute Learning +<br/>Using Joint Human and Machine Computation +<br/>Edith Law +<br/>April 2011 +<br/>Machine Learning Department +<br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA 15213 +<br/>Thesis Committee: +<br/>Luis von Ahn (co-Chair) +<br/>Tom Mitchell (co-Chair) +<br/>Jaime Carbonell +<br/>Eric Horvitz, Microsoft Research +<br/>Rob Miller, MIT +<br/>Submitted in partial fulfillment of the requirements +<br/>for the degree of Doctor of Philosophy. +<br/>Copyright c(cid:13) 2011 Edith Law +</td><td></td><td></td></tr><tr><td>c8adbe00b5661ab9b3726d01c6842c0d72c8d997</td><td>Deep Architectures for Face Attributes <br/>Computer Vision and Machine Learning Group, Flickr, Yahoo, </td><td>('3469274', 'Tobi Baumgartner', 'tobi baumgartner')<br/>('31922487', 'Jack Culpepper', 'jack culpepper')</td><td>{tobi, jackcul}@yahoo-inc.com </td></tr><tr><td>fb4545782d9df65d484009558e1824538030bbb1</td><td></td><td></td><td></td></tr><tr><td>fbf196d83a41d57dfe577b3a54b1b7fa06666e3b</td><td>Extreme Learning Machine for Large-Scale <br/>Action Recognition -<br/><b>Bo gazi ci University, Turkey</b></td><td>('1764521', 'Albert Ali Salah', 'albert ali salah')</td><td></td></tr><tr><td>fbb6ee4f736519f7231830a8e337b263e91f06fe</td><td>Illumination Robust Facial Feature Detection via +<br/><b>Bo gazi ci University, Turkey</b></td><td>('1764521', 'Albert Ali Salah', 'albert ali salah')</td><td></td></tr><tr><td>fb2cc3501fc89f92f5ee130d66e69854f8a9ddd1</td><td>Learning Discriminative Features via Label Consistent Neural Network +<br/>†Raytheon BBN Technologies, Cambridge, MA, 02138 +<br/><b>University of Maryland, College Park, MD</b></td><td>('34145947', 'Zhuolin Jiang', 'zhuolin jiang')<br/>('1691470', 'Yaming Wang', 'yaming wang')<br/>('2502892', 'Viktor Rozgic', 'viktor rozgic')</td><td>{zjiang,wandrews,vrozgic}@bbn.com, {wym,lsd}@umiacs.umd.edu +</td></tr><tr><td>fbb6ee4f736519f7231830a8e337b263e91f06fe</td><td>Illumination Robust Facial Feature Detection via <br/>Decoupled Illumination and Texture Features <br/><b>University of Waterloo, Waterloo ON N2L3G1, Canada</b><br/>WWW home page: http://vip.uwaterloo.ca/ (cid:63) </td><td>('2797326', 'Brendan Chwyl', 'brendan chwyl')<br/>('1685952', 'Alexander Wong', 'alexander wong')<br/>('1720258', 'David A. Clausi', 'david a. clausi')</td><td>{bchwyl,a28wong,dclausi}@uwaterloo.ca, -</td></tr><tr><td>fb5280b80edcf088f9dd1da769463d48e7b08390</td><td></td><td></td><td></td></tr><tr><td>fba464cb8e3eff455fe80e8fb6d3547768efba2f</td><td> +</td></tr><tr><td>fb87045600da73b07f0757f345a937b1c8097463</td><td>JIA, YANG, ZHU, KUANG, NIU, CHAN: RCCR FOR LARGE POSE +<br/>Reflective Regression of 2D-3D Face Shape +<br/>Across Large Pose +<br/><b>The University of Hong Kong</b><br/><b>National University of Defense</b><br/>Technology +<br/>3 Tencent Inc. +<br/>4 Sensetime Inc. +</td><td>('34760532', 'Xuhui Jia', 'xuhui jia')<br/>('2966679', 'Heng Yang', 'heng yang')<br/>('35130187', 'Xiaolong Zhu', 'xiaolong zhu')<br/>('1874900', 'Zhanghui Kuang', 'zhanghui kuang')<br/>('1939702', 'Yifeng Niu', 'yifeng niu')<br/>('40392393', 'Kwok-Ping Chan', 'kwok-ping chan')</td><td>xhjia@cs.hku.hk +<br/>yanghengnudt@gmail.com +<br/>lucienzhu@gmail.com +<br/>kuangzhanghui@sensetime.com +<br/>niuyifeng@nudt.edu.cn +<br/>kpchan@cs.hku.hk +</td></tr><tr><td>fb85867c989b9ee6b7899134136f81d6372526a9</td><td>Learning to Align Images using Weak Geometric Supervision +<br/><b>Georgia Institute of Technology</b><br/>2 Microsoft Research +</td><td>('1703391', 'Jing Dong', 'jing dong')<br/>('3288815', 'Byron Boots', 'byron boots')<br/>('2038264', 'Frank Dellaert', 'frank dellaert')<br/>('1757937', 'Sudipta N. Sinha', 'sudipta n. sinha')</td><td></td></tr><tr><td>fb5280b80edcf088f9dd1da769463d48e7b08390</td><td></td><td></td><td></td></tr><tr><td>fb54d3c37dc82891ff9dc7dd8caf31de00c40d6a</td><td>Beauty and the Burst: +<br/>Remote Identification of Encrypted Video Streams +<br/><b>Tel Aviv University, Cornell Tech</b><br/>Cornell Tech +<br/><b>Tel Aviv University, Columbia University</b></td><td>('39347554', 'Roei Schuster', 'roei schuster')<br/>('1723945', 'Vitaly Shmatikov', 'vitaly shmatikov')<br/>('2337345', 'Eran Tromer', 'eran tromer')</td><td>rs864@cornell.edu +<br/>shmat@cs.cornell.edu +<br/>tromer@cs.tau.ac.il +</td></tr><tr><td>fba464cb8e3eff455fe80e8fb6d3547768efba2f</td><td> <br/>International Journal of Engineering and Applied Sciences (IJEAS) <br/> ISSN: 2394-3661, Volume-3, Issue-2, February 2016 <br/>Survey Paper on Emotion Recognition <br/> -</td><td>('40502287', 'Prachi Shukla', 'prachi shukla')<br/>('2229305', 'Sandeep Patil', 'sandeep patil')</td><td></td></tr><tr><td>fb084b1fe52017b3898c871514cffcc2bdb40b73</td><td>RESEARCH ARTICLE +</td><td>('40502287', 'Prachi Shukla', 'prachi shukla')<br/>('2229305', 'Sandeep Patil', 'sandeep patil')</td><td></td></tr><tr><td>fbb2f81fc00ee0f257d4aa79bbef8cad5000ac59</td><td>Reading Hidden Emotions: Spontaneous +<br/>Micro-expression Spotting and Recognition +</td><td>('50079101', 'Xiaobai Li', 'xiaobai li')<br/>('1836646', 'Xiaopeng Hong', 'xiaopeng hong')<br/>('39056318', 'Antti Moilanen', 'antti moilanen')<br/>('47932625', 'Xiaohua Huang', 'xiaohua huang')<br/>('1757287', 'Guoying Zhao', 'guoying zhao')</td><td></td></tr><tr><td>fb084b1fe52017b3898c871514cffcc2bdb40b73</td><td>RESEARCH ARTICLE <br/>Illumination Normalization of Face Image <br/>Based on Illuminant Direction Estimation and <br/>Improved Retinex <br/><b>School of Electronic and Information Engineering, Beihang University, Beijing, 100191, China</b><br/><b>Polytechnic University of Milan, Milan, 20156, Italy, 3 Applied Electronics</b><br/><b>University POLITEHNICA Timisoara, Timisoara, 300223, Romania</b></td><td>('1699804', 'Jizheng Yi', 'jizheng yi')<br/>('1724834', 'Xia Mao', 'xia mao')<br/>('35153304', 'Lijiang Chen', 'lijiang chen')<br/>('3399189', 'Yuli Xue', 'yuli xue')<br/>('1734732', 'Alberto Rovetta', 'alberto rovetta')<br/>('1860887', 'Catalin-Daniel Caleanu', 'catalin-daniel caleanu')</td><td>* clj@ee.buaa.edu.cn -</td></tr><tr><td>ed28e8367fcb7df7e51963add9e2d85b46e2d5d6</td><td>International J. of Engg. Research & Indu. Appls. (IJERIA). +</td></tr><tr><td>fb9ad920809669c1b1455cc26dbd900d8e719e61</td><td>3D Gaze Estimation from Remote RGB-D Sensors +<br/>THÈSE NO 6680 (2015) +<br/>PRÉSENTÉE LE 9 OCTOBRE 2015 +<br/>À LA FACULTÉ DES SCIENCES ET TECHNIQUES DE L'INGÉNIEUR +<br/>LABORATOIRE DE L'IDIAP +<br/>PROGRAMME DOCTORAL EN GÉNIE ÉLECTRIQUE +<br/>ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE +<br/>POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES +<br/>PAR +<br/>acceptée sur proposition du jury: +<br/>Prof. K. Aminian, président du jury +<br/>Dr J.-M. Odobez, directeur de thèse +<br/>Prof. L.-Ph. Morency, rapporteur +<br/>Prof. D. Witzner Hansen, rapporteur +<br/>Dr R. Boulic, rapporteur +<br/>Suisse +<br/>2015 +</td><td>('9206411', 'Kenneth Alberto Funes Mora', 'kenneth alberto funes mora')</td><td></td></tr><tr><td>ed28e8367fcb7df7e51963add9e2d85b46e2d5d6</td><td>International J. of Engg. Research & Indu. Appls. (IJERIA). <br/>ISSN 0974-1518, Vol.9, No. III (December 2016), pp.23-42 <br/>A NOVEL APPROACH OF FACE RECOGNITION USING <br/>CONVOLUTIONAL NEURAL NETWORKS WITH AUTO <br/>ENCODER <br/>1 Research Scholar, Dept. of Electronics & Communication Engineering, <br/><b>Rayalaseema University Kurnool, Andhra Pradesh</b><br/> 2 Research Supervisor, Professor, Dept. of Electronics & Communication Engineering, -<br/><b>Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh</b></td><td>('7006226', 'S. A. K JILANI', 's. a. k jilani')</td><td></td></tr><tr><td>ed08ac6da6f8ead590b390b1d14e8a9b97370794</td><td> +<br/><b>Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh</b></td><td>('7006226', 'S. A. K JILANI', 's. a. k jilani')</td><td></td></tr><tr><td>ed0cf5f577f5030ac68ab62fee1cf065349484cc</td><td>Revisiting Data Normalization for +<br/>Appearance-Based Gaze Estimation +<br/><b>Max Planck Institute for Informatics</b><br/>Saarland Informatics Campus, +<br/>Graduate School of Information +<br/>Science and Technology, Osaka +<br/><b>Max Planck Institute for Informatics</b><br/>Saarland Informatics Campus, +<br/>Germany +<br/><b>University, Japan</b><br/>Germany +</td><td>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('1751242', 'Yusuke Sugano', 'yusuke sugano')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td>xczhang@mpi-inf.mpg.de +<br/>sugano@ist.osaka-u.ac.jp +<br/>bulling@mpi-inf.mpg.de +</td></tr><tr><td>edde81b2bdd61bd757b71a7b3839b6fef81f4be4</td><td>SHIH, MALLYA, SINGH, HOIEM: MULTI-PROPOSAL PART LOCALIZATION +<br/>Part Localization using Multi-Proposal +<br/>Consensus for Fine-Grained Categorization +<br/><b>University of Illinois</b><br/>Urbana-Champaign +<br/>IL, US +</td><td>('2525469', 'Kevin J. Shih', 'kevin j. shih')<br/>('36508529', 'Arun Mallya', 'arun mallya')<br/>('37415643', 'Saurabh Singh', 'saurabh singh')<br/>('2433269', 'Derek Hoiem', 'derek hoiem')</td><td>kjshih2@illinois.edu +<br/>amallya2@illinois.edu +<br/>ss1@illinois.edu +<br/>dhoiem@illinois.edu +</td></tr><tr><td>edf98a925bb24e39a6e6094b0db839e780a77b08</td><td>Simplex Representation for Subspace Clustering +<br/><b>The Hong Kong Polytechnic University, Hong Kong SAR, China</b><br/><b>School of Mathematics and Statistics, Xi an Jiaotong University, Xi an, China</b><br/>Spectral clustering based methods have achieved leading performance on subspace clustering problem. State-of-the-art subspace +<br/>clustering methods follow a three-stage framework: compute a coefficient matrix from the data by solving an optimization problem; +<br/>construct an affinity matrix from the coefficient matrix; and obtain the final segmentation by applying spectral clustering to the +<br/>affinity matrix. To construct a feasible affinity matrix, these methods mostly employ the operations of exponentiation, absolutely +<br/>symmetrization, or squaring, etc. However, all these operations will force the negative entries (which cannot be explicitly avoided) +<br/>the data. In this paper, we introduce the simplex representation (SR) to remedy this problem of representation based subspace +<br/>clustering. We propose an SR based least square regression (SRLSR) model to construct a physically more meaningful affinity matrix +<br/>by integrating the nonnegative property of graph into the representation coefficient computation while maintaining the discrimination +<br/>of original data. The SRLSR model is reformulated as a linear equality-constrained problem, which is solved efficiently under the +<br/>alternating direction method of multipliers framework. Experiments on benchmark datasets demonstrate that the proposed SRLSR +<br/>algorithm is very efficient and outperforms state-of-the-art subspace clustering methods on accuracy. +<br/>Index Terms—Subspace clustering, simplex representation, spectral clustering. +<br/>I. INTRODUCTION +<br/>H IGH-dimensional data are commonly observed in var- +<br/>ious computer vision and image processing prob- +<br/>lems. Contrary to their high-dimensional appearance, +<br/>the +<br/>latent structure of those data usually lie in a union of +<br/>low-dimensional subspaces [1]. Recovering the latent low- +<br/>dimensional subspaces from the high-dimensional observation +<br/>can not only reduce the computational cost and memory +<br/>requirements of subsequent algorithms, but also reduce the +<br/>learning and computer vision tasks, we need to find the clusters +<br/>of high-dimensional data such that each cluster can be fitted +<br/>by a subspace, which is referred to as the subspace clustering +<br/>(SC) problem [1]. +<br/>SC has been extensively studied in the past decades [2]– +<br/>[33]. Most of existing SC methods can be categorized into +<br/>four categories: iterative based methods [2], [3], algebraic +<br/>based methods [4]–[6], statistical based methods [7]–[10], and +<br/>spectral clustering based methods [14]–[33]. Among these four +<br/>categories, spectral clustering based methods have become the +<br/>mainstream due to their theoretical guarantees and promising +<br/>performance on real-world applications such as motion seg- +<br/>mentation [16] and face clustering [18]. The spectral clustering +<br/>based methods usually follow a three-step framework: Step +<br/>1) obtain a coefficient matrix of the data points by solving +<br/>an optimization problem, which usually incorporates sparse +<br/>or low rank regularizations due to their good mathematical +<br/>properties; Step 2) construct an affinity matrix from the +<br/>coefficient matrix by employing exponentiation [14], abso- +<br/>lutely symmetrization [15], [16], [20], [23]–[31], and squaring +<br/>operations [17]–[19], [32], [33], etc.; Step 3) apply spectral +<br/>analysis techniques [34] to the affinity matrix and obtain the +<br/>final clusters of the data points. +<br/>Most spectral clustering based methods [14]–[33] obtain +<br/>the expected coefficient matrix under the self-expressiveness +<br/>property [15], [16], which states that each data point in a union +<br/>of multiple subspaces can be linearly represented by the other +<br/>data points in the same subspace. However, in some real-world +<br/>applications, the data points lie in a union of multiple affine +<br/>subspaces rather than linear subspaces [16]. A trivial solution +<br/>is to ignore the affine structure of the data points and directly +<br/>perform clustering as in the subspaces of linear structures. +<br/>A non-negligible drawback of this solution is the increasing +<br/>dimension of the intersection of two subspaces, which can +<br/>make the subspaces indistinguishable from each other [16]. To +<br/>cluster data points lying in affine subspaces instead of linear +<br/>subspaces, the affine constraint is introduced [15], [16], in +<br/>which each data point can be written as an affine combination +<br/>of other points with the sum of coefficients being one. +<br/>Despite their high clustering accuracy, most of spectral +<br/>clustering based methods [14]–[33] suffer from three major +<br/>drawbacks. First, under the affine constraint, the coefficient +<br/>vector is not flexible enough to handle real-world applications +<br/>Second, negative coefficients cannot be fully avoided since +<br/>the existing methods do not explicitly consider non-negative +<br/>constraint +<br/>in real-world applications, +<br/>it is physically problematic to reconstruct a data point by +<br/>allowing the others to “cancel each other out” with complex +<br/>additions and subtractions [35]. Thus, most of these methods +<br/>are limited by being stranded at this physical bottleneck. Third, +<br/>the exponentiation, absolutely symmetrization, and squaring +<br/>operations in Step 2 will force the negative coefficients to +<br/>among the data points. +<br/>in Step 1. However, +<br/>To solve the three drawbacks mentioned above, we intro- +<br/>duce the Simplex Representation (SR) for spectral clustering +<br/>based SC. Specifically, the SR is introduced from two in- +<br/>terdependent aspects. First, to broaden its adaptivity to real +<br/>scenarios, we extend the affine constraint to the scaled affine +<br/>constraint, in which the coefficient vector in the optimization +</td><td>('47882783', 'Jun Xu', 'jun xu')<br/>('1803714', 'Deyu Meng', 'deyu meng')<br/>('48571185', 'Lei Zhang', 'lei zhang')</td><td></td></tr><tr><td>ed08ac6da6f8ead590b390b1d14e8a9b97370794</td><td> <br/> <br/> <br/> @@ -12369,18 +15911,47 @@ <br/>Vol. 3, Issue 9, September 2015 <br/>An Efficient Approach for 3D Face <br/>Recognition Using ANN Based Classifiers -<br/><b>Shri Shivaji College, Parbhani, M.S, India</b><br/><b>Arts, Commerce and Science College, Gangakhed, M.S, India</b><br/><b>Dnyanopasak College Parbhani, M.S, India</b></td><td>('34443070', 'Vaibhav M. Pathak', 'vaibhav m. pathak')</td><td></td></tr><tr><td>edef98d2b021464576d8d28690d29f5431fd5828</td><td>Pixel-Level Alignment of Facial Images +<br/><b>Shri Shivaji College, Parbhani, M.S, India</b><br/><b>Arts, Commerce and Science College, Gangakhed, M.S, India</b><br/><b>Dnyanopasak College Parbhani, M.S, India</b></td><td>('34443070', 'Vaibhav M. Pathak', 'vaibhav m. pathak')</td><td></td></tr><tr><td>ed9d11e995baeec17c5d2847ec1a8d5449254525</td><td>Efficient Gender Classification Using a Deep LDA-Pruned Net +<br/><b>McGill University</b><br/>845 Sherbrooke Street W, Montreal, QC H3A 0G4, Canada +</td><td>('48087399', 'Qing Tian', 'qing tian')<br/>('1699104', 'Tal Arbel', 'tal arbel')<br/>('1713608', 'James J. Clark', 'james j. clark')</td><td>{qtian,arbel,clark}@cim.mcgill.ca +</td></tr><tr><td>edef98d2b021464576d8d28690d29f5431fd5828</td><td>Pixel-Level Alignment of Facial Images <br/>for High Accuracy Recognition <br/>Using Ensemble of Patches </td><td>('1782221', 'Hoda Mohammadzade', 'hoda mohammadzade')<br/>('35809715', 'Amirhossein Sayyafan', 'amirhossein sayyafan')<br/>('24033665', 'Benyamin Ghojogh', 'benyamin ghojogh')</td><td></td></tr><tr><td>ed04e161c953d345bcf5b910991d7566f7c486f7</td><td>Combining facial expression analysis and synthesis on a <br/>Mirror my emotions! <br/>robot -</td><td>('2185308', 'Stefan Sosnowski', 'stefan sosnowski')<br/>('39124596', 'Christoph Mayer', 'christoph mayer')<br/>('1699132', 'Bernd Radig', 'bernd radig')</td><td></td></tr><tr><td>edd7504be47ebc28b0d608502ca78c0aea6a65a2</td><td>Recurrent Residual Learning for Action +</td><td>('2185308', 'Stefan Sosnowski', 'stefan sosnowski')<br/>('39124596', 'Christoph Mayer', 'christoph mayer')<br/>('1699132', 'Bernd Radig', 'bernd radig')</td><td></td></tr><tr><td>ed07856461da6c7afa4f1782b5b607b45eebe9f6</td><td>3D Morphable Models as Spatial Transformer Networks +<br/><b>University of York, UK</b><br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b></td><td>('39180407', 'Anil Bas', 'anil bas')<br/>('39976184', 'Patrik Huber', 'patrik huber')<br/>('1687021', 'William A. P. Smith', 'william a. p. smith')<br/>('46649582', 'Muhammad Awais', 'muhammad awais')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>{ab1792,william.smith}@york.ac.uk, {p.huber,m.a.rana,j.kittler}@surrey.ac.uk +</td></tr><tr><td>ed1886e233c8ecef7f414811a61a83e44c8bbf50</td><td>Deep Alignment Network: A convolutional neural network for robust face +<br/>alignment +<br/><b>Warsaw University of Technology</b></td><td>('2393538', 'Marek Kowalski', 'marek kowalski')<br/>('1930272', 'Jacek Naruniec', 'jacek naruniec')<br/>('1760267', 'Tomasz Trzcinski', 'tomasz trzcinski')</td><td>m.kowalski@ire.pw.edu.pl, j.naruniec@ire.pw.edu.pl, t.trzcinski@ii.pw.edu.pl +</td></tr><tr><td>edd7504be47ebc28b0d608502ca78c0aea6a65a2</td><td>Recurrent Residual Learning for Action <br/>Recognition <br/><b>University of Bonn, Germany</b></td><td>('3434584', 'Ahsan Iqbal', 'ahsan iqbal')<br/>('32774629', 'Alexander Richard', 'alexander richard')<br/>('2946643', 'Juergen Gall', 'juergen gall')</td><td>{iqbalm,richard,kuehne,gall}@iai.uni-bonn.de +</td></tr><tr><td>ed388878151a3b841f95a62c42382e634d4ab82e</td><td>DenseImage Network: Video Spatial-Temporal Evolution +<br/>Encoding and Understanding +<br/><b>Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('3162023', 'Xiaokai Chen', 'xiaokai chen')<br/>('2027479', 'Ke Gao', 'ke gao')</td><td>{chenxiaokai,kegao}@ict.ac.cn </td></tr><tr><td>edbb8cce0b813d3291cae4088914ad3199736aa0</td><td>Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence <br/>Efficient Subspace Segmentation via Quadratic Programming <br/><b>College of Computer Science and Technology, Zhejiang University, China</b><br/><b>National University of Singapore, Singapore</b><br/><b>School of Information Systems, Singapore Management University, Singapore</b></td><td>('35019367', 'Shusen Wang', 'shusen wang')<br/>('2026127', 'Tiansheng Yao', 'tiansheng yao')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('38203359', 'Jialie Shen', 'jialie shen')</td><td>wssatzju@gmail.com, eleyuanx@nus.edu.sg, tsyaoo@gmail.com, eleyans@nus.edu.sg, jlshen@smu.edu.sg +</td></tr><tr><td>edff76149ec44f6849d73f019ef9bded534a38c2</td><td>Privacy-Preserving Visual Learning Using +<br/>Doubly Permuted Homomorphic Encryption +<br/><b>The University of Tokyo</b><br/>Tokyo, Japan +<br/><b>Michigan State University</b><br/>East Lansing, MI, USA +<br/><b>The University of Tokyo</b><br/>Tokyo, Japan +<br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA, USA +</td><td>('1899753', 'Ryo Yonetani', 'ryo yonetani')<br/>('2232940', 'Vishnu Naresh Boddeti', 'vishnu naresh boddeti')<br/>('9467266', 'Yoichi Sato', 'yoichi sato')<br/>('37991449', 'Kris M. Kitani', 'kris m. kitani')</td><td>yonetani@iis.u-tokyo.ac.jp +<br/>vishnu@msu.edu +<br/>kkitani@cs.cmu.edu +<br/>ysato@iis.u-tokyo.ac.jp +</td></tr><tr><td>ed96f2eb1771f384df2349879970065a87975ca7</td><td>Adversarial Attacks on Face Detectors using Neural +<br/>Net based Constrained Optimization +<br/>Department of Electrical and +<br/>Computer Engineering +<br/><b>University of Toronto</b><br/>Department of Electrical and +<br/>Computer Engineering +<br/><b>University of Toronto</b></td><td>('26418299', 'Avishek Joey Bose', 'avishek joey bose')<br/>('3241876', 'Parham Aarabi', 'parham aarabi')</td><td>Email: joey.bose@mail.utoronto.ca +<br/>Email: parham@ecf.utoronto.ca </td></tr><tr><td>c178a86f4c120eca3850a4915134fff44cbccb48</td><td></td><td></td><td></td></tr><tr><td>c1d2d12ade031d57f8d6a0333cbe8a772d752e01</td><td>Journal of Math-for-Industry, Vol.2(2010B-5), pp.147–156 <br/>Convex optimization techniques for the efficient recovery of a sparsely <br/>corrupted low-rank matrix @@ -12391,6 +15962,8 @@ <br/>Selective Prior <br/>Department of Information Processing, School of Information Science, <br/><b>Japan Advanced Institute of Science and Technology, Ishikawa-ken 923-1211, Japan</b></td><td>('1753878', 'Fan Chen', 'fan chen')<br/>('1791753', 'Kazunori Kotani', 'kazunori kotani')</td><td>{chen-fan, ikko}@jaist.ac.jp +</td></tr><tr><td>c146aa6d56233ce700032f1cb179700778557601</td><td>3D Morphable Models as Spatial Transformer Networks +<br/><b>University of York, UK</b><br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b></td><td>('39180407', 'Anil Bas', 'anil bas')<br/>('39976184', 'Patrik Huber', 'patrik huber')<br/>('1687021', 'William A. P. Smith', 'william a. p. smith')<br/>('9170545', 'Muhammad Awais', 'muhammad awais')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>{ab1792,william.smith}@york.ac.uk, {p.huber,m.a.rana,j.kittler}@surrey.ac.uk </td></tr><tr><td>c1f07ec629be1c6fe562af0e34b04c54e238dcd1</td><td>A Novel Facial Feature Localization Method Using Probabilistic-like Output* <br/>Microsoft Research Asia <br/> @@ -12427,6 +16000,13 @@ </td><td>('1684635', 'Lei Zhang', 'lei zhang')<br/>('9310930', 'Long', 'long')<br/>('8392859', 'Mingjing Li', 'mingjing li')<br/>('38188346', 'Hongjiang Zhang', 'hongjiang zhang')<br/>('1679242', 'Longbin Chen', 'longbin chen')</td><td>{leizhang, mjli,hjzhang}@microsoft.com <br/>longzhu@msrchina.research.microsoft.com <br/>l.chen6@umiami.edu +</td></tr><tr><td>c1cc2a2a1ab66f6c9c6fabe28be45d1440a57c3d</td><td>Dual-Agent GANs for Photorealistic and Identity +<br/>Preserving Profile Face Synthesis +<br/><b>National University of Singapore</b><br/>3 Panasonic R&D Center Singapore +<br/><b>National University of Defense Technology</b><br/><b>Franklin. W. Olin College of Engineering</b><br/><b>Qihoo 360 AI Institute</b></td><td>('46509484', 'Jian Zhao', 'jian zhao')<br/>('33419682', 'Lin Xiong', 'lin xiong')<br/>('2757639', 'Jianshu Li', 'jianshu li')<br/>('40345914', 'Fang Zhao', 'fang zhao')<br/>('2513111', 'Zhecan Wang', 'zhecan wang')<br/>('2668358', 'Sugiri Pranata', 'sugiri pranata')<br/>('3493398', 'Shengmei Shen', 'shengmei shen')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')</td><td>{zhaojian90, jianshu}@u.nus.edu +<br/>{lin.xiong, karlekar.jayashree, sugiri.pranata, shengmei.shen}@sg.panasonic.com +<br/>zhecan.wang@students.olin.edu +<br/>{elezhf, eleyans, elefjia}@u.nus.edu </td></tr><tr><td>c10a15e52c85654db9c9343ae1dd892a2ac4a279</td><td>Int J Comput Vis (2012) 100:134–153 <br/>DOI 10.1007/s11263-011-0494-3 <br/>Learning the Relative Importance of Objects from Tagged Images @@ -12499,7 +16079,10 @@ <br/>Subspace Regression: Predicting a Subspace from one Sample <br/>Anonymous CVPR submission <br/>Paper ID 1369 -</td><td></td><td></td></tr><tr><td>c17a332e59f03b77921942d487b4b102b1ee73b6</td><td>Learning an appearance-based gaze estimator +</td><td></td><td></td></tr><tr><td>c11eb653746afa8148dc9153780a4584ea529d28</td><td>Global and Local Consistent Wavelet-domain Age +<br/>Synthesis +</td><td>('2112221', 'Peipei Li', 'peipei li')<br/>('49995036', 'Yibo Hu', 'yibo hu')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td></td></tr><tr><td>c1ebbdb47cb6a0ed49c4d1cf39d7565060e6a7ee</td><td>Robust Facial Landmark Localization Based on +</td><td>('19254504', 'Yiyun Pan', 'yiyun pan')<br/>('7934466', 'Junwei Zhou', 'junwei zhou')<br/>('46636537', 'Yongsheng Gao', 'yongsheng gao')<br/>('2065968', 'Shengwu Xiong', 'shengwu xiong')</td><td></td></tr><tr><td>c17a332e59f03b77921942d487b4b102b1ee73b6</td><td>Learning an appearance-based gaze estimator <br/>from one million synthesised images <br/>Tadas Baltruˇsaitis2 </td><td>('34399452', 'Erroll Wood', 'erroll wood')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')<br/>('39626495', 'Peter Robinson', 'peter robinson')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td>1University of Cambridge, United Kingdom {erroll.wood,peter.robinson}@cam.ac.uk @@ -12513,7 +16096,49 @@ </td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('35362682', 'Shen Yan', 'shen yan')<br/>('1685956', 'Hermann Ney', 'hermann ney')</td><td>hanselmann@cs.rwth-aachen.de <br/>shen.yan@rwth-aachen.de <br/>ney@cs.rwth-aachen.de -</td></tr><tr><td>c696c9bbe27434cb6279223a79b17535cd6e88c8</td><td>International Journal of Information Technology Vol.11 No.9 2005 +</td></tr><tr><td>c1298120e9ab0d3764512cbd38b47cd3ff69327b</td><td>Disguised Faces in the Wild +<br/>IIIT-Delhi, India +<br/><b>IBM TJ Watson Research Center, USA</b><br/>Rama Chellappa +<br/><b>University of Maryland, College Park, USA</b></td><td>('2573268', 'Vineet Kushwaha', 'vineet kushwaha')<br/>('2220719', 'Maneet Singh', 'maneet singh')<br/>('50631607', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('47733712', 'Nalini Ratha', 'nalini ratha')</td><td>{maneets, rsingh, mayank}@iiitd.ac.in +<br/>ratha@us.ibm.com +<br/>rama@umiacs.umd.ed +</td></tr><tr><td>c1dd69df9dfbd7b526cc89a5749f7f7fabc1e290</td><td>Unconstrained face identification with multi-scale block-based +<br/>correlation +<br/>Gaston, J., MIng, J., & Crookes, D. (2016). Unconstrained face identification with multi-scale block-based +<br/>correlation. In Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal +<br/><b>Processing (pp. 1477-1481). [978-1-5090-4117-6/17] Institute of Electrical and Electronics Engineers (IEEE</b><br/>Published in: +<br/>Proceedings of the 2017 IEEE International Conference on Acoustics, Speech and Signal Processing +<br/>Document Version: +<br/>Peer reviewed version +<br/><b>Queen's University Belfast - Research Portal</b><br/><b>Link to publication record in Queen's University Belfast Research Portal</b><br/>Publisher rights +<br/>© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future +<br/><b>media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or</b><br/>redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. +<br/>General rights +<br/><b>Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other</b><br/>copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated +<br/>with these rights. +<br/>Take down policy +<br/>The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to +<br/>ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the +<br/>Download date:29. Nov. 2017 +</td><td></td><td>Research Portal that you believe breaches copyright or violates any law, please contact openaccess@qub.ac.uk. +</td></tr><tr><td>c68ec931585847b37cde9f910f40b2091a662e83</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, +<br/>Vol. 9, No. 6, 2018 +<br/>A Comparative Evaluation of Dotted Raster- +<br/>Stereography and Feature-Based Techniques for +<br/>Automated Face Recognition +<br/>S. Talha Ahsan +<br/>Department of Computer Science +<br/>Department of Electrical Engineering +<br/><b>Usman Institute of Technology</b><br/><b>Usman Institute of Technology</b><br/>Karachi, Pakistan +<br/>Karachi, Pakistan +<br/>Department of Computer Science +<br/><b>Usman Institute of Technology</b><br/>Karachi, Pakistan +<br/>and +<br/>feature-based +<br/>system. The +<br/>techniques +<br/>two candidate +</td><td>('49508503', 'Muhammad Wasim', 'muhammad wasim')<br/>('3251091', 'Lubaid Ahmed', 'lubaid ahmed')<br/>('33238128', 'Syed Faisal Ali', 'syed faisal ali')</td><td></td></tr><tr><td>c696c9bbe27434cb6279223a79b17535cd6e88c8</td><td>International Journal of Information Technology Vol.11 No.9 2005 <br/>* <br/>Discriminant Analysis <br/>Facial Expression Recognition with Pyramid Gabor @@ -12566,17 +16191,29 @@ <br/>Edmund A. Hajim School of Engineering and Applied Sciences <br/><b>University of Rochester</b><br/>Rochester, New York <br/>2015 -</td><td>('2296971', 'Iftekhar Naim', 'iftekhar naim')</td><td></td></tr><tr><td>c62c910264658709e9bf0e769e011e7944c45c90</td><td>Recent Progress of Face Image Synthesis +</td><td>('2296971', 'Iftekhar Naim', 'iftekhar naim')</td><td></td></tr><tr><td>c6f3399edb73cfba1248aec964630c8d54a9c534</td><td>A Comparison of CNN-based Face and Head Detectors for +<br/>Real-Time Video Surveillance Applications +<br/>1 ´Ecole de technologie sup´erieure, Universit´e du Qu´ebec, Montreal, Canada +<br/>2 Genetec Inc., Montreal, Canada +</td><td>('38993564', 'Le Thanh Nguyen-Meidine', 'le thanh nguyen-meidine')<br/>('1697195', 'Eric Granger', 'eric granger')<br/>('40185782', 'Madhu Kiran', 'madhu kiran')<br/>('38755219', 'Louis-Antoine Blais-Morin', 'louis-antoine blais-morin')</td><td>lethanh@livia.etsmtl.ca, eric.granger@etsmtl.ca, mkiran@livia.etsmtl.ca +<br/>lablaismorin@genetec.com +</td></tr><tr><td>c62c910264658709e9bf0e769e011e7944c45c90</td><td>Recent Progress of Face Image Synthesis <br/>National Laboratory of Pattern Recognition, CASIA <br/>Center for Research on Intelligent Perception and Computing, CASIA <br/>Center for Excellence in Brain Science and Intelligence Technology, CAS <br/><b>University of Chinese Academy of Sciences, Beijing, 100049, China</b></td><td>('9702077', 'Zhihe Lu', 'zhihe lu')<br/>('7719475', 'Zhihang Li', 'zhihang li')<br/>('1680853', 'Jie Cao', 'jie cao')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>{luzhihe2016, lizhihang2016, caojie2016}@ia.ac.cn, {rhe, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>c678920facffd35853c9d185904f4aebcd2d8b49</td><td>Learning to Anonymize Faces for +<br/>Privacy Preserving Action Detection +<br/>1 EgoVid Inc., South Korea +<br/><b>University of California, Davis</b></td><td>('10805888', 'Zhongzheng Ren', 'zhongzheng ren')<br/>('1883898', 'Yong Jae Lee', 'yong jae lee')<br/>('1766489', 'Michael S. Ryoo', 'michael s. ryoo')</td><td>{zzren,yongjaelee}@ucdavis.edu, mryoo@egovid.com </td></tr><tr><td>c660500b49f097e3af67bb14667de30d67db88e3</td><td>www.elsevier.com/locate/cviu <br/>Facial asymmetry quantification for <br/>expression invariant human identification <br/>and Sinjini Mitrac <br/><b>a The Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA</b><br/><b>University of Pittsburgh, Pittsburgh, PA 15260, USA</b><br/><b>Carnegie Mellon University, Pittsburgh, PA 15213, USA</b><br/>Received 15 February 2002; accepted 24 March 2003 -</td><td>('1689241', 'Yanxi Liu', 'yanxi liu')<br/>('2185899', 'Karen L. Schmidt', 'karen l. schmidt')</td><td></td></tr><tr><td>c6ffa09c4a6cacbbd3c41c8ae7a728b0de6e10b6</td><td>This article appeared in a journal published by Elsevier. The attached +</td><td>('1689241', 'Yanxi Liu', 'yanxi liu')<br/>('2185899', 'Karen L. Schmidt', 'karen l. schmidt')</td><td></td></tr><tr><td>c6241e6fc94192df2380d178c4c96cf071e7a3ac</td><td>Action Recognition with Trajectory-Pooled Deep-Convolutional Descriptors +<br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen key lab of Comp. Vis. and Pat. Rec., Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('33427555', 'Yu Qiao', 'yu qiao')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>07wanglimin@gmail.com, yu.qiao@siat.ac.cn, xtang@ie.cuhk.edu.hk +</td></tr><tr><td>c6ffa09c4a6cacbbd3c41c8ae7a728b0de6e10b6</td><td>This article appeared in a journal published by Elsevier. The attached <br/>copy is furnished to the author for internal non-commercial research <br/><b>and education use, including for instruction at the authors institution</b><br/>and sharing with colleagues. <br/><b>Other uses, including reproduction and distribution, or selling or</b><br/>licensing copies, or posting to personal, institutional or third party @@ -12631,14 +16268,26 @@ <br/>trait anxiety interact to alter cognition has rarely been studied10. In particular, does induced anxiety have a <br/><b>Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, UK. 2Affective Brain</b><br/><b>Lab, University College London, London WC1H 0AP, UK. 3Clinical</b><br/><b>Psychopharmacology Unit, Educational and Health Psychology, University College</b><br/>London, WC1E 7HB. *These authors contributed equally to this work. †These authors jointly supervised this work. </td><td>('4177273', 'Chandni Hindocha', 'chandni hindocha')</td><td>Correspondence and requests for materials should be addressed to C.J.C. (email: caroline.charpentier.11@ucl.ac.uk) -</td></tr><tr><td>c65a394118d34beda5dd01ae0df163c3db88fceb</td><td>In press : Proceedings of the 30th European Conference On Information Retrieval +</td></tr><tr><td>c62c07de196e95eaaf614fb150a4fa4ce49588b4</td><td>Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18) +<br/>1078 +</td><td></td><td></td></tr><tr><td>c65a394118d34beda5dd01ae0df163c3db88fceb</td><td>In press : Proceedings of the 30th European Conference On Information Retrieval <br/>Glasgow, March-April 2008 <br/>Finding the Best Picture: <br/>Cross-Media Retrieval of Content <br/><b>Katholieke Universiteit Leuven</b><br/>Celestijnenlaan 200A, B-3001 Heverlee, Belgium <br/>http://www.cs.kuleuven.be/~liir/ </td><td>('1797588', 'Koen Deschacht', 'koen deschacht')<br/>('1802161', 'Marie-Francine Moens', 'marie-francine moens')</td><td>{Koen.Deschacht,Marie-Francine.Moens}@cs.kuleuven.be -</td></tr><tr><td>ec12f805a48004a90e0057c7b844d8119cb21b4a</td><td>Distance-Based Descriptors and Their +</td></tr><tr><td>ec90d333588421764dff55658a73bbd3ea3016d2</td><td>Research Article +<br/>Protocol for Systematic Literature Review of Face +<br/>Recognition in Uncontrolled Environment +<br/><b>Bacha Khan University, Charsadda, KPK, Pakistan</b></td><td>('12144785', 'Faizan Ullah', 'faizan ullah')<br/>('46463663', 'Sabir Shah', 'sabir shah')<br/>('49669073', 'Dilawar Shah', 'dilawar shah')<br/>('12579194', 'Shujaat Ali', 'shujaat ali')</td><td>faizanullah@bkuc.edu.pk +</td></tr><tr><td>ec8ec2dfd73cf3667f33595fef84c95c42125945</td><td>Pose-Invariant Face Alignment with a Single CNN +<br/><b>Michigan State University</b><br/>2Visualization Group, Bosch Research and Technology Center North America +</td><td>('2357264', 'Amin Jourabloo', 'amin jourabloo')<br/>('3876303', 'Mao Ye', 'mao ye')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')<br/>('3334600', 'Liu Ren', 'liu ren')</td><td>1,2 {jourablo, liuxm}@msu.edu, {mao.ye2, liu.ren}@us.bosch.com +</td></tr><tr><td>ec1e03ec72186224b93b2611ff873656ed4d2f74</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>3D Reconstruction of “In-the-Wild” Faces in +<br/>Images and Videos +</td><td>('47456731', 'James Booth', 'james booth')<br/>('2931390', 'Anastasios Roussos', 'anastasios roussos')<br/>('31243357', 'Evangelos Ververas', 'evangelos ververas')<br/>('2015036', 'Stylianos Ploumpis', 'stylianos ploumpis')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')</td><td></td></tr><tr><td>ec12f805a48004a90e0057c7b844d8119cb21b4a</td><td>Distance-Based Descriptors and Their <br/>Application in the Task of Object Detection <br/><b>Technical University of Ostrava, FEECS</b><br/>17. Listopadu 15, 708 33 Ostrava-Poruba, Czech Republic </td><td>('2467747', 'Radovan Fusek', 'radovan fusek')<br/>('2557877', 'Eduard Sojka', 'eduard sojka')</td><td>{radovan.fusek,eduard.sojka}@vsb.cz @@ -12665,7 +16314,28 @@ <br/><b>aInformation Sciences Institute</b><br/><b>University of Southern California</b><br/>Marina Del Rey, CA <br/><b>b Institute for Robotics and Intelligent Systems</b><br/><b>University of Southern California</b><br/>Los Angeles, California <br/><b>cThe Open University</b><br/>Raanana, Israel -</td><td>('1746738', 'Yue Wu', 'yue wu')<br/>('38696444', 'Stephen Rawls', 'stephen rawls')<br/>('35840854', 'Shai Harel', 'shai harel')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')<br/>('1689391', 'Jongmoo Choi', 'jongmoo choi')<br/>('2955822', 'Jatuporn Toy Leksut', 'jatuporn toy leksut')<br/>('5911467', 'Jungyeon Kim', 'jungyeon kim')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>4e5dc3b397484326a4348ccceb88acf309960e86</td><td>Hindawi Publishing Corporation +</td><td>('1746738', 'Yue Wu', 'yue wu')<br/>('38696444', 'Stephen Rawls', 'stephen rawls')<br/>('35840854', 'Shai Harel', 'shai harel')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')<br/>('1689391', 'Jongmoo Choi', 'jongmoo choi')<br/>('2955822', 'Jatuporn Toy Leksut', 'jatuporn toy leksut')<br/>('5911467', 'Jungyeon Kim', 'jungyeon kim')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>4e30107ee6a2e087f14a7725e7fc5535ec2f5a5f</td><td>Представление новостных сюжетов с помощью +<br/>событийных фотографий +<br/>© М.М. Постников +<br/> © Б.В. Добров +<br/>Московский государственный университет имени М.В. Ломоносова +<br/>факультет вычислительной математики и кибернетики, +<br/>Москва, Россия +<br/>Аннотация. Рассмотрена задача аннотирования новостного сюжета изображениями, +<br/>ассоциированными с конкретными текстами сюжета. Введено понятие «событийной фотографии», +<br/>содержащей конкретную информацию, дополняющую текст сюжета. Для решения задачи применены +<br/>нейронные сети с использованием переноса обучения (Inception v3) для специальной размеченной +<br/>коллекции из 4114 изображений. Средняя точность полученных результатов составила более 94,7%. +<br/>Ключевые слова: событийная фотография, новостные иллюстрации, перенос обучения. +<br/>News Stories Representation Using Event Photos +<br/>© M.M. Postnikov +<br/> © B.V. Dobrov +<br/><b>Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics</b><br/>Moscow, Russia +</td><td></td><td>mihanlg@yandex.ru +<br/> dobrov_bv@mail.ru +<br/>mihanlg@yandex.ru +<br/> dobrov_bv@mail.ru +</td></tr><tr><td>4e5dc3b397484326a4348ccceb88acf309960e86</td><td>Hindawi Publishing Corporation <br/>e Scientific World Journal <br/>Volume 2014, Article ID 219732, 12 pages <br/>http://dx.doi.org/10.1155/2014/219732 @@ -12736,7 +16406,10 @@ </td></tr><tr><td>4e4fa167d772f34dfffc374e021ab3044566afc3</td><td>Learning Low-Rank Representations with Classwise <br/>Block-Diagonal Structure for Robust Face Recognition <br/><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b><br/><b>School of Computer Science, Nanjing University of Science and Technology</b><br/><b>University of Maryland, College Park</b></td><td>('1689181', 'Yong Li', 'yong li')<br/>('38188270', 'Jing Liu', 'jing liu')<br/>('3233021', 'Zechao Li', 'zechao li')<br/>('34868330', 'Yangmuzi Zhang', 'yangmuzi zhang')<br/>('1694235', 'Hanqing Lu', 'hanqing lu')<br/>('38450168', 'Songde Ma', 'songde ma')</td><td>{yong.li,jliu,luhq}@nlpr.ia.ac.cn, zechao.li@gmail.com, ymzhang@umiacs.umd.edu, masd@most.cn -</td></tr><tr><td>4ed54d5093d240cc3644e4212f162a11ae7d1e3b</td><td>Learning Visual Compound Models from Parallel +</td></tr><tr><td>4e32fbb58154e878dd2fd4b06398f85636fd0cf4</td><td>A Hierarchical Matcher using Local Classifier Chains +<br/>L. Zhang and I.A. Kakadiaris +<br/>Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204 +</td><td></td><td></td></tr><tr><td>4ed54d5093d240cc3644e4212f162a11ae7d1e3b</td><td>Learning Visual Compound Models from Parallel <br/>Image-Text Datasets <br/><b>Bielefeld University</b><br/><b>University of Toronto</b></td><td>('2872318', 'Jan Moringen', 'jan moringen')<br/>('1724954', 'Sven Wachsmuth', 'sven wachsmuth')<br/>('1792908', 'Suzanne Stevenson', 'suzanne stevenson')</td><td>{jmoringe,swachsmu}@techfak.uni-bielefeld.de <br/>{sven,suzanne}@cs.toronto.edu @@ -12755,7 +16428,15 @@ </td></tr><tr><td>4e97b53926d997f451139f74ec1601bbef125599</td><td>Discriminative Regularization for Generative Models <br/><b>Montreal Institute for Learning Algorithms, Universit e de Montr eal</b></td><td>('2059369', 'Alex Lamb', 'alex lamb')<br/>('3074927', 'Vincent Dumoulin', 'vincent dumoulin')</td><td>FIRST.LAST@UMONTREAL.CA </td></tr><tr><td>4e8168fbaa615009d1618a9d6552bfad809309e9</td><td>Deep Convolutional Neural Network Features and the Original Image -<br/><b>School of Behavioral and Brain Sciences, The University of Texas at Dallas, USA</b><br/><b>University of Maryland, College Park, USA</b></td><td>('7493834', 'Connor J. Parde', 'connor j. parde')<br/>('3363752', 'Matthew Q. Hill', 'matthew q. hill')<br/>('15929465', 'Y. Ivette Colon', 'y. ivette colon')<br/>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')</td><td></td></tr><tr><td>4ea4116f57c5d5033569690871ba294dc3649ea5</td><td>Multi-View Face Alignment Using 3D Shape Model for +<br/><b>School of Behavioral and Brain Sciences, The University of Texas at Dallas, USA</b><br/><b>University of Maryland, College Park, USA</b></td><td>('7493834', 'Connor J. Parde', 'connor j. parde')<br/>('3363752', 'Matthew Q. Hill', 'matthew q. hill')<br/>('15929465', 'Y. Ivette Colon', 'y. ivette colon')<br/>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')</td><td></td></tr><tr><td>4e0636a1b92503469b44e2807f0bb35cc0d97652</td><td>Adversarial Localization Network +<br/><b>Tsinghua University</b><br/><b>Stanford University</b><br/><b>Stanford University</b></td><td>('2548303', 'Lijie Fan', 'lijie fan')<br/>('3303970', 'Shengjia Zhao', 'shengjia zhao')<br/>('2490652', 'Stefano Ermon', 'stefano ermon')</td><td>flj14@mails.tsinghua.edu.cn +<br/>sjzhao@stanford.edu +<br/>ermon@stanford.edu +</td></tr><tr><td>4e27fec1703408d524d6b7ed805cdb6cba6ca132</td><td>SSD-Sface: Single shot multibox detector for small faces +<br/>C. Thuis +</td><td></td><td></td></tr><tr><td>4e6c9be0b646d60390fe3f72ce5aeb0136222a10</td><td>Long-term Temporal Convolutions +<br/>for Action Recognition +</td><td>('1785596', 'Ivan Laptev', 'ivan laptev')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>4ea4116f57c5d5033569690871ba294dc3649ea5</td><td>Multi-View Face Alignment Using 3D Shape Model for <br/>View Estimation <br/><b>Tsinghua University</b><br/>2Core Technology Center, Omron Corporation </td><td>('1739678', 'Yanchao Su', 'yanchao su')<br/>('1679380', 'Haizhou Ai', 'haizhou ai')<br/>('1710195', 'Shihong Lao', 'shihong lao')</td><td>ahz@mail.tsinghua.edu.cn @@ -12799,6 +16480,73 @@ <br/><b>German Research Center for Arti cial Intelligence (DFKI</b><br/>Tripstaddterstr. 122, 67663 Kaiserslautern, Germany <br/><b>Technical University of Kaiserslautern</b><br/>http://www.av.dfki.de </td><td>('2585383', 'Mohamed Selim', 'mohamed selim')<br/>('1771057', 'Alain Pagani', 'alain pagani')<br/>('1807169', 'Didier Stricker', 'didier stricker')</td><td>{mohamed.selim,alain.pagani,didier.stricker}@dfki.uni-kl.de +</td></tr><tr><td>20b994a78cd1db6ba86ea5aab7211574df5940b3</td><td>Enriched Long-term Recurrent Convolutional Network +<br/>for Facial Micro-Expression Recognition +<br/><b>Faculty of Computing and Informatics, Multimedia University, Malaysia</b><br/><b>Faculty of Engineering, Multimedia University, Malaysia</b><br/><b>Shanghai Jiao Tong University, China</b></td><td>('30470673', 'Huai-Qian Khor', 'huai-qian khor')<br/>('2339975', 'John See', 'john see')<br/>('8131625', 'Weiyao Lin', 'weiyao lin')</td><td>Emails: 1hqkhor95@gmail.com, 2johnsee@mmu.edu.my, 3raphael@mmu.edu.my, 4wylin@sjtu.edu.cn +</td></tr><tr><td>2004afb2276a169cdb1f33b2610c5218a1e47332</td><td>Hindawi +<br/>Computational Intelligence and Neuroscience +<br/>Volume 2018, Article ID 3803627, 11 pages +<br/>https://doi.org/10.1155/2018/3803627 +<br/>Research Article +<br/>Deep Convolutional Neural Network Used in Single Sample per +<br/>Person Face Recognition +<br/><b>School of Information Engineering, Wuyi University, Jiangmen 529020, China</b><br/>Received 27 November 2017; Revised 23 May 2018; Accepted 26 July 2018; Published 23 August 2018 +<br/>Academic Editor: Jos´e Alfredo Hern´andez-P´erez +<br/>which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +<br/>Face recognition (FR) with single sample per person (SSPP) is a challenge in computer vision. Since there is only one sample to be +<br/>trained, it makes facial variation such as pose, illumination, and disguise difficult to be predicted. To overcome this problem, this paper +<br/>proposes a scheme combined traditional and deep learning (TDL) method to process the task. First, it proposes an expanding sample +<br/>method based on traditional approach. Compared with other expanding sample methods, the method can be used easily and +<br/>conveniently. Besides, it can generate samples such as disguise, expression, and mixed variation. Second, it uses transfer learning and +<br/>introduces a well-trained deep convolutional neural network (DCNN) model and then selects some expanding samples to fine-tune the +<br/>DCNN model. 0ird, the fine-tuned model is used to implement experiment. Experimental results on AR face database, Extend Yale B +<br/>face database, FERET face database, and LFW database demonstrate that TDL achieves the state-of-the-art performance in SSPP FR. +<br/>1. Introduction +<br/>As artificial +<br/>intelligence (AI) becomes more and more +<br/>popular, computer vision (CV) also has been proved to be +<br/>a very hot topic in academic such as face recognition [1], +<br/>facial expression recognition [2], and object recognition [3]. +<br/>It is well known that the basic and important foundation in +<br/>CV is that there are an amount of training samples. But in +<br/>actual scenarios such as immigration management, fugitive +<br/>tracing, and video surveillance, there may be only one +<br/>sample, which leads to single sample per person (SSPP) +<br/>problem such as gait recognition [4], face recognition (FR) +<br/>[5, 6], and low-resolution face recognition [7] in CV. +<br/>However, as the widely use of second-generation ID card +<br/>which is convenient to be collected, SSPP FR becomes one of +<br/>the most popular topics no matter in academic or in +<br/>industry. +<br/>Beymer and Poggio [8] proposed one example view +<br/>problem in 1996. In [8], it was researched that how to +<br/>perform face recognition (FR) using one example view. +<br/>Firstly, it exploited prior knowledge to generate multiple +<br/>virtual views. 0en, the example view and these multiple +<br/>virtual views were used as example views in a view-based, +<br/>pose-invariant +<br/>face recognizer. Later, SSPP FR became +<br/>a popular research topic at the beginning of the 21st century. +<br/>Recently, many methods have been proposed. Generally +<br/>speaking, these methods can be summarized in five basic +<br/>methods: direct method, generic learning method, patch- +<br/>based method, expanding sample method, and deep learning +<br/>(DL) method. Direct method does experiment based on the +<br/>SSPP directly by using an algorithm. Generic learning +<br/>method is the way that using an auxiliary dataset to build +<br/>a generic dataset from which some variation information +<br/>can be learned by single sample. Patch-based method par- +<br/>titions single sample into several patches first, then extracts +<br/>features on these patches, respectively, and does classifica- +<br/>tion finally. 0e expanding sample method is with some +<br/>special means such as perturbation-based method [9, 10], +<br/>photometric transforms, and geometric distortion [11] to +<br/>increase sample so that abundant training samples can be +<br/>used to process this task. 0e DL method uses the DL model +<br/>to perform the research. +<br/>Attracted by the good performance of DCNN, inspired +<br/>by [12] and driven by AI, in this paper, a scheme combined +</td><td>('9363278', 'Junying Zeng', 'junying zeng')<br/>('12054657', 'Xiaoxiao Zhao', 'xiaoxiao zhao')<br/>('2926767', 'Junying Gan', 'junying gan')<br/>('40552250', 'Chaoyun Mai', 'chaoyun mai')<br/>('1716453', 'Fan Wang', 'fan wang')<br/>('3003242', 'Yikui Zhai', 'yikui zhai')<br/>('9363278', 'Junying Zeng', 'junying zeng')</td><td>Correspondence should be addressed to Xiaoxiao Zhao; xiaoxiao-zhao@foxmail.com </td></tr><tr><td>20e504782951e0c2979d9aec88c76334f7505393</td><td>Robust LSTM-Autoencoders for Face De-Occlusion <br/>in the Wild </td><td>('37182704', 'Fang Zhao', 'fang zhao')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('39913117', 'Jian Zhao', 'jian zhao')<br/>('1898172', 'Wenhan Yang', 'wenhan yang')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>209324c152fa8fab9f3553ccb62b693b5b10fb4d</td><td>CROWDSOURCED VISUAL KNOWLEDGE REPRESENTATIONS @@ -12813,7 +16561,9 @@ </td><td>('2580593', 'Ranjay Krishna', 'ranjay krishna')</td><td></td></tr><tr><td>2050847bc7a1a0453891f03aeeb4643e360fde7d</td><td>Accio: A Data Set for Face Track Retrieval <br/>in Movies Across Age <br/><b>Istanbul Technical University, Istanbul, Turkey</b><br/><b>Karlsruhe Institute of Technology, Karlsruhe, Germany</b></td><td>('2398366', 'Esam Ghaleb', 'esam ghaleb')<br/>('2103464', 'Makarand Tapaswi', 'makarand tapaswi')<br/>('2256981', 'Ziad Al-Halah', 'ziad al-halah')<br/>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')</td><td>{ghalebe, ekenel}@itu.edu.tr, {tapaswi, ziad.al-halah, rainer.stiefelhagen}@kit.edu -</td></tr><tr><td>202d8d93b7b747cdbd6e24e5a919640f8d16298a</td><td>Face Classification via Sparse Approximation +</td></tr><tr><td>20ade100a320cc761c23971d2734388bfe79f7c5</td><td>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +<br/>Subspace Clustering via Good Neighbors +</td><td>('1755872', 'Jufeng Yang', 'jufeng yang')<br/>('1780418', 'Jie Liang', 'jie liang')<br/>('39329211', 'Kai Wang', 'kai wang')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>202d8d93b7b747cdbd6e24e5a919640f8d16298a</td><td>Face Classification via Sparse Approximation <br/><b>Bilgi University, Dolapdere, Istanbul, TR</b><br/><b>Bo gazici University, Istanbul, TR</b><br/><b>Y ld z Teknik University, Istanbul, TR</b></td><td>('2804969', 'Songul Albayrak', 'songul albayrak')</td><td></td></tr><tr><td>20767ca3b932cbc7b8112db21980d7b9b3ea43a3</td><td></td><td></td><td></td></tr><tr><td>20a16efb03c366fa4180659c2b2a0c5024c679da</td><td>SCREENING RULES FOR OVERLAPPING GROUP LASSO <br/><b>Carnegie Mellon University</b><br/>Recently, to solve large-scale lasso and group lasso problems, <br/>screening rules have been developed, the goal of which is to reduce @@ -12875,7 +16625,10 @@ </td><td></td><td>e-mail: vretos,nikolaid,pitas@aiia.csd.auth.gr </td></tr><tr><td>2098983dd521e78746b3b3fa35a22eb2fa630299</td><td></td><td></td><td></td></tr><tr><td>20b437dc4fc44c17f131713ffcbb4a8bd672ef00</td><td>Head pose tracking from RGBD sensor based on <br/>direct motion estimation -<br/><b>Warsaw University of Technology, Poland</b></td><td>('1899063', 'Adam Strupczewski', 'adam strupczewski')<br/>('2393538', 'Marek Kowalski', 'marek kowalski')<br/>('1930272', 'Jacek Naruniec', 'jacek naruniec')</td><td></td></tr><tr><td>208a2c50edb5271a050fa9f29d3870f891daa4dc</td><td>http://www.journalofvision.org/content/11/13/24 +<br/><b>Warsaw University of Technology, Poland</b></td><td>('1899063', 'Adam Strupczewski', 'adam strupczewski')<br/>('2393538', 'Marek Kowalski', 'marek kowalski')<br/>('1930272', 'Jacek Naruniec', 'jacek naruniec')</td><td></td></tr><tr><td>206e24f7d4b3943b35b069ae2d028143fcbd0704</td><td>Learning Structure and Strength of CNN Filters for Small Sample Size Training +<br/>IIIT-Delhi, India +</td><td>('3390448', 'Rohit Keshari', 'rohit keshari')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('39129417', 'Richa Singh', 'richa singh')</td><td>{rohitk, mayank, rsingh}@iiitd.ac.in +</td></tr><tr><td>208a2c50edb5271a050fa9f29d3870f891daa4dc</td><td>http://www.journalofvision.org/content/11/13/24 <br/>The resolution of facial expressions of emotion <br/>Aleix M. Martinez <br/><b>The Ohio State University, Columbus, OH, USA</b><br/><b>The Ohio State University, Columbus, OH, USA</b><br/><b>Much is known on how facial expressions of emotion are produced, including which individual muscles are most active in</b><br/>each expression. Yet, little is known on how this information is interpreted by the human visual system. This paper presents @@ -12969,10 +16722,36 @@ <br/>Coahuila, Mexico <br/><b>The University of York, Heslington, York YO10 5DD, United Kingdom</b></td><td>('1679753', 'Edwin R. Hancock', 'edwin r. hancock')</td><td>mario.castelan@cinvestav.edu.mx <br/>erh@cs.york.ac.uk -</td></tr><tr><td>2042aed660796b14925db17c0a8b9fbdd7f3ebac</td><td>Saliency in Crowd +</td></tr><tr><td>2059d2fecfa61ddc648be61c0cbc9bc1ad8a9f5b</td><td>TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 23, NO. 4, APRIL 2015 +<br/>Co-Localization of Audio Sources in Images Using +<br/>Binaural Features and Locally-Linear Regression +<br/>∗ INRIA Grenoble Rhˆone-Alpes, Montbonnot Saint-Martin, France +<br/>† Univ. Grenoble Alpes, GIPSA-Lab, France +<br/>‡ Dept. Electrical Eng., Technion-Israel Inst. of Technology, Haifa, Israel +</td><td>('3307172', 'Antoine Deleforge', 'antoine deleforge')</td><td></td></tr><tr><td>206fbe6ab6a83175a0ef6b44837743f8d5f9b7e8</td><td></td><td></td><td></td></tr><tr><td>2042aed660796b14925db17c0a8b9fbdd7f3ebac</td><td>Saliency in Crowd <br/>Department of Electrical and Computer Engineering <br/><b>National University of Singapore, Singapore</b></td><td>('40452812', 'Ming Jiang', 'ming jiang')<br/>('1946538', 'Juan Xu', 'juan xu')<br/>('3243515', 'Qi Zhao', 'qi zhao')</td><td>eleqiz@nus.edu.sg -</td></tr><tr><td>20ebbcb6157efaacf7a1ceb99f2f3e2fdf1384e6</td><td>Appears in the Second International Conference on Audio- and Video-based Biometric Person Authentication, AVBPA’99, Washington D. C. USA, March 22-24, 1999. +</td></tr><tr><td>202dc3c6fda654aeb39aee3e26a89340fb06802a</td><td>Spatio-Temporal Instance Learning: +<br/>Action Tubes from Class Supervision +<br/><b>University of Amsterdam</b></td><td>('2606260', 'Pascal Mettes', 'pascal mettes')</td><td></td></tr><tr><td>20111924fbf616a13d37823cd8712a9c6b458cd6</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 130 – No.11, November2015 +<br/>Linear Regression Line based Partial Face Recognition +<br/>Naveena M. +<br/>Department of Studies in +<br/>Computer Science, +<br/>Manasagagothri, +<br/>Mysore. +<br/>Department of Studies in +<br/>Computer Science, +<br/>Manasagagothri, +<br/>Mysore. +<br/>P. Nagabhushan +<br/>Department of Studies in +<br/>Computer Science, +<br/>Manasagagothri, +<br/>Mysore. +<br/>images. In +</td><td>('33377948', 'G. Hemantha Kumar', 'g. hemantha kumar')</td><td></td></tr><tr><td>20ebbcb6157efaacf7a1ceb99f2f3e2fdf1384e6</td><td>Appears in the Second International Conference on Audio- and Video-based Biometric Person Authentication, AVBPA’99, Washington D. C. USA, March 22-24, 1999. <br/>Comparative Assessment of Independent Component <br/>Analysis (ICA) for Face Recognition <br/><b>George Mason University</b><br/><b>University Drive, Fairfax, VA 22030-4444, USA</b><br/> @@ -12988,7 +16767,13 @@ <br/>Received: 27 June 2007 / Accepted: 6 December 2007 / Published online: 23 January 2008 <br/>© Springer-Verlag 2008 </td><td>('1716880', 'Y. Yang', 'y. yang')</td><td></td></tr><tr><td>20cfb4136c1a984a330a2a9664fcdadc2228b0bc</td><td>Sparse Coding Trees with Application to Emotion Classification -<br/><b>Harvard University, Cambridge, MA</b></td><td>('3144257', 'Hsieh-Chung Chen', 'hsieh-chung chen')<br/>('2512314', 'Marcus Z. Comiter', 'marcus z. comiter')<br/>('1731308', 'H. T. Kung', 'h. t. kung')<br/>('1841852', 'Bradley McDanel', 'bradley mcdanel')</td><td></td></tr><tr><td>2020e8c0be8fa00d773fd99b6da55029a6a83e3d</td><td>An Evaluation of the Invariance Properties +<br/><b>Harvard University, Cambridge, MA</b></td><td>('3144257', 'Hsieh-Chung Chen', 'hsieh-chung chen')<br/>('2512314', 'Marcus Z. Comiter', 'marcus z. comiter')<br/>('1731308', 'H. T. Kung', 'h. t. kung')<br/>('1841852', 'Bradley McDanel', 'bradley mcdanel')</td><td></td></tr><tr><td>20c02e98602f6adf1cebaba075d45cef50de089f</td><td>Video Jigsaw: Unsupervised Learning of Spatiotemporal Context for Video +<br/>Action Recognition +<br/><b>Georgia Institute of Technology</b><br/><b>Carnegie Mellon University</b><br/>Irfan Essa +<br/><b>Georgia Institute of Technology</b></td><td>('2308598', 'Unaiza Ahsan', 'unaiza ahsan')<br/>('37714701', 'Rishi Madhok', 'rishi madhok')</td><td>uahsan3@gatech.edu +<br/>rmadhok@andrew.cmu.edu +<br/>irfan@gatech.edu +</td></tr><tr><td>2020e8c0be8fa00d773fd99b6da55029a6a83e3d</td><td>An Evaluation of the Invariance Properties <br/>of a Biologically-Inspired System <br/>for Unconstrained Face Recognition <br/><b>Massachusetts Institute of Technology, Cambridge, MA 02139, USA</b><br/><b>Rowland Institute at Harvard, Cambridge, MA 02142, USA</b></td><td>('30017846', 'Nicolas Pinto', 'nicolas pinto')</td><td>pinto@mit.edu @@ -13037,15 +16822,47 @@ </td><td>('2720935', 'Jihun Ham', 'jihun ham')<br/>('1732066', 'Daniel D. Lee', 'daniel d. lee')</td><td>jhham@seas.upenn.edu, ddlee@seas.upenn.edu </td></tr><tr><td>18d5b0d421332c9321920b07e0e8ac4a240e5f1f</td><td>Collaborative Representation Classification <br/>Ensemble for Face Recognition -</td><td>('2972883', 'Suah Kim', 'suah kim')<br/>('2434811', 'Run Cui', 'run cui')<br/>('1730037', 'Hyoung Joong Kim', 'hyoung joong kim')</td><td></td></tr><tr><td>18c6c92c39c8a5a2bb8b5673f339d3c26b8dcaae</td><td>Learning invariant representations and applications +</td><td>('2972883', 'Suah Kim', 'suah kim')<br/>('2434811', 'Run Cui', 'run cui')<br/>('1730037', 'Hyoung Joong Kim', 'hyoung joong kim')</td><td></td></tr><tr><td>18d51a366ce2b2068e061721f43cb798177b4bb7</td><td>Cognition and Emotion +<br/>ISSN: 0269-9931 (Print) 1464-0600 (Online) Journal homepage: http://www.tandfonline.com/loi/pcem20 +<br/>Looking into your eyes: observed pupil size +<br/>influences approach-avoidance responses +<br/>eyes: observed pupil size influences approach-avoidance responses, Cognition and Emotion, DOI: +<br/>10.1080/02699931.2018.1472554 +<br/>To link to this article: https://doi.org/10.1080/02699931.2018.1472554 +<br/>View supplementary material +<br/>Published online: 11 May 2018. +<br/>Submit your article to this journal +<br/>View related articles +<br/>View Crossmark data +<br/>Full Terms & Conditions of access and use can be found at +<br/>http://www.tandfonline.com/action/journalInformation?journalCode=pcem20 +</td><td>('47930228', 'Marco Brambilla', 'marco brambilla')<br/>('41074530', 'Marco Biella', 'marco biella')<br/>('47930228', 'Marco Brambilla', 'marco brambilla')<br/>('41074530', 'Marco Biella', 'marco biella')</td><td></td></tr><tr><td>18c6c92c39c8a5a2bb8b5673f339d3c26b8dcaae</td><td>Learning invariant representations and applications <br/>to face verification <br/>Center for Brains, Minds and Machines <br/><b>McGovern Institute for Brain Research</b><br/><b>Massachusetts Institute of Technology</b><br/>Cambridge MA 02139 </td><td>('1694846', 'Qianli Liao', 'qianli liao')</td><td>lql@mit.edu, jzleibo@mit.edu, tp@ai.mit.edu +</td></tr><tr><td>185263189a30986e31566394680d6d16b0089772</td><td>Efficient Annotation of Objects for Video Analysis +<br/>Thesis submitted in partial fulfillment +<br/>of the requirements for the degree of +<br/>MS in Computer Science and Engineering +<br/>by +<br/>Research +<br/>by +<br/>Sirnam Swetha +<br/>201303014 +<br/><b>International Institute of Information Technology</b><br/>Hyderabad - 500 032, INDIA +<br/>June 2018 +</td><td></td><td>sirnam.swetha@research.iiit.ac.in </td></tr><tr><td>1885acea0d24e7b953485f78ec57b2f04e946eaf</td><td>Combining Local and Global Features for 3D Face Tracking <br/>Megvii (face++) Research </td><td>('40448951', 'Pengfei Xiong', 'pengfei xiong')<br/>('1775836', 'Guoqing Li', 'guoqing li')<br/>('3756559', 'Yuhang Sun', 'yuhang sun')</td><td>{xiongpengfei, liguoqing, sunyuhang}@megvii.com -</td></tr><tr><td>184750382fe9b722e78d22a543e852a6290b3f70</td><td></td><td></td><td></td></tr><tr><td>18a849b1f336e3c3b7c0ee311c9ccde582d7214f</td><td>Int J Comput Vis +</td></tr><tr><td>184750382fe9b722e78d22a543e852a6290b3f70</td><td></td><td></td><td></td></tr><tr><td>18b9dc55e5221e704f90eea85a81b41dab51f7da</td><td>Attention-based Temporal Weighted +<br/>Convolutional Neural Network for +<br/>Action Recognition +<br/><b>Xi an Jiaotong University, Xi an, Shannxi 710049, P.R.China</b><br/>2HERE Technologies, Chicago, IL 60606, USA +<br/>3Alibaba Group, Hangzhou, Zhejiang 311121, P.R.China +<br/>4Microsoft Research, Redmond, WA 98052, USA +</td><td>('14800230', 'Jinliang Zang', 'jinliang zang')<br/>('40367806', 'Le Wang', 'le wang')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('1786361', 'Zhenxing Niu', 'zhenxing niu')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('1715389', 'Nanning Zheng', 'nanning zheng')</td><td></td></tr><tr><td>18a849b1f336e3c3b7c0ee311c9ccde582d7214f</td><td>Int J Comput Vis <br/>DOI 10.1007/s11263-012-0564-1 <br/>Efficiently Scaling up Crowdsourced Video Annotation <br/>A Set of Best Practices for High Quality, Economical Video Labeling @@ -13089,13 +16906,20 @@ <br/>1School of Computer Science & Engineering, South China Univ. of Tech., Guangzhou 510006, China <br/>2School of Automation Science & Engineering, South China Univ. of Tech., Guangzhou 510006, China <br/><b>National University of Singapore, Singapore</b></td><td>('2217653', 'Yuhui Quan', 'yuhui quan')<br/>('1725160', 'Yong Xu', 'yong xu')<br/>('2111796', 'Yuping Sun', 'yuping sun')<br/>('34881546', 'Yan Huang', 'yan huang')<br/>('39689301', 'Hui Ji', 'hui ji')</td><td>{csyhquan@scut.edu.cn, yxu@scut.edu.cn, ausyp@scut.edu.cn, matjh@nus.edu.sg} +</td></tr><tr><td>18941b52527e6f15abfdf5b86a0086935706e83b</td><td>DeepGUM: Learning Deep Robust Regression with a +<br/>Gaussian-Uniform Mixture Model +<br/>1 Inria Grenoble Rhˆone-Alpes, Montbonnot-Saint-Martin, France, +<br/><b>University of Granada, Granada, Spain</b><br/><b>University of Trento, Trento, Italy</b></td><td>('2793152', 'Pablo Mesejo', 'pablo mesejo')<br/>('1780201', 'Xavier Alameda-Pineda', 'xavier alameda-pineda')<br/>('1794229', 'Radu Horaud', 'radu horaud')</td><td>firstname.name@inria.fr </td></tr><tr><td>185360fe1d024a3313042805ee201a75eac50131</td><td>299 <br/>Person De-Identification in Videos </td><td>('35624289', 'Prachi Agrawal', 'prachi agrawal')<br/>('1729020', 'P. J. Narayanan', 'p. j. narayanan')</td><td></td></tr><tr><td>1824b1ccace464ba275ccc86619feaa89018c0ad</td><td>One Millisecond Face Alignment with an Ensemble of Regression Trees <br/><b>KTH, Royal Institute of Technology</b><br/>Computer Vision and Active Perception Lab <br/>Teknikringen 14, Stockholm, Sweden </td><td>('2626422', 'Vahid Kazemi', 'vahid kazemi')<br/>('1736906', 'Josephine Sullivan', 'josephine sullivan')</td><td>{vahidk,sullivan}@csc.kth.se -</td></tr><tr><td>18dfc2434a95f149a6cbb583cca69a98c9de9887</td><td></td><td></td><td></td></tr><tr><td>271e2856e332634eccc5e80ba6fa9bbccf61f1be</td><td>3D Spatio-Temporal Face Recognition Using Dynamic Range Model Sequences +</td></tr><tr><td>18dfc2434a95f149a6cbb583cca69a98c9de9887</td><td></td><td></td><td></td></tr><tr><td>27a00f2490284bc0705349352d36e9749dde19ab</td><td>VoxCeleb2: Deep Speaker Recognition +<br/>Visual Geometry Group, Department of Engineering Science, +<br/><b>University of Oxford, UK</b></td><td>('2863890', 'Joon Son Chung', 'joon son chung')<br/>('19263506', 'Arsha Nagrani', 'arsha nagrani')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{joon,arsha,az}@robots.ox.ac.uk +</td></tr><tr><td>271e2856e332634eccc5e80ba6fa9bbccf61f1be</td><td>3D Spatio-Temporal Face Recognition Using Dynamic Range Model Sequences <br/>Department of Computer Science <br/><b>State University of New York at Binghamton, Binghamton, NY</b></td><td>('1681656', 'Yi Sun', 'yi sun')<br/>('8072251', 'Lijun Yin', 'lijun yin')</td><td></td></tr><tr><td>27846b464369095f4909f093d11ed481277c8bba</td><td>Journal of Signal and Information Processing, 2017, 8, 99-112 <br/>http://www.scirp.org/journal/jsip @@ -13159,7 +16983,14 @@ </td><td>('34316743', 'Junsong Yuan', 'junsong yuan')<br/>('40634508', 'Ming Yang', 'ming yang')<br/>('39955137', 'Ying Wu', 'ying wu')</td><td>jsyuan@ntu.edu.sg <br/>myang@sv.nec-labs.com <br/>yingwu@eecs.northwestern.edu -</td></tr><tr><td>27218ff58c3f0e7d7779fba3bb465d746749ed7c</td><td>Active Learning for Image Ranking +</td></tr><tr><td>275b5091c50509cc8861e792e084ce07aa906549</td><td>Institut für Informatik +<br/>der Technischen +<br/>Universität München +<br/>Dissertation +<br/>Leveraging the User’s Face as a Known Object +<br/>in Handheld Augmented Reality +<br/>Sebastian Bernhard Knorr +</td><td></td><td></td></tr><tr><td>27218ff58c3f0e7d7779fba3bb465d746749ed7c</td><td>Active Learning for Image Ranking <br/>Over Relative Visual Attributes <br/>by <br/>Department of Computer Science @@ -13173,7 +17004,29 @@ <br/>image-based 3D <br/>techniques. Then we describe <br/>Received: 21Feburary 2011 / Revised: 20 March 2011 / Accepted: 11 May 2011 -<br/><b>D Research Center, Kwangwoon University and Springer</b></td><td>('1908324', 'Steffen Herbort', 'steffen herbort')</td><td></td></tr><tr><td>27c6cd568d0623d549439edc98f6b92528d39bfe</td><td>Regressive Tree Structured Model for Facial Landmark Localization +<br/><b>D Research Center, Kwangwoon University and Springer</b></td><td>('1908324', 'Steffen Herbort', 'steffen herbort')</td><td></td></tr><tr><td>270733d986a1eb72efda847b4b55bc6ba9686df4</td><td>We are IntechOpen, +<br/>the first native scientific +<br/>publisher of Open Access books +<br/>3,350 +<br/>108,000 +<br/>1.7 M +<br/>Open access books available +<br/>International authors and editors +<br/>Downloads +<br/>Our authors are among the +<br/>151 +<br/>Countries delivered to +<br/>TOP 1% +<br/>12.2% +<br/>most cited scientists +<br/>Contributors from top 500 universities +<br/>Selection of our books indexed in the Book Citation Index +<br/>in Web of Science™ Core Collection (BKCI) +<br/>Interested in publishing with us? +<br/>Numbers displayed above are based on latest data collected. +<br/>For more information visit www.intechopen.com +</td><td></td><td>Contact book.department@intechopen.com +</td></tr><tr><td>27c6cd568d0623d549439edc98f6b92528d39bfe</td><td>Regressive Tree Structured Model for Facial Landmark Localization <br/>Artificial Vision Lab., Dept Mechanical Engineering <br/><b>National Taiwan University of Science and Technology</b></td><td>('2329565', 'Kai-Hsiang Chang', 'kai-hsiang chang')<br/>('2421405', 'Shih-Chieh Huang', 'shih-chieh huang')</td><td>jison@mail.ntust.edu.tw </td></tr><tr><td>273b0511588ab0a81809a9e75ab3bd93d6a0f1e3</td><td>The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-016-3428-9 @@ -13257,7 +17110,7 @@ <br/>surveillance, <br/>access </td><td>('3222448', 'Sikyung Kim', 'sikyung kim')<br/>('2387342', 'Se Jin Park', 'se jin park')</td><td>*Corresponding author. E-mail: mynudding@yahoo.com. -</td></tr><tr><td>27961bc8173ac84fdbecacd01e5ed6f7ed92d4bd</td><td>To Appear in The IEEE 6th International Conference on Biometrics: Theory, Applications and +</td></tr><tr><td>27da432cf2b9129dce256e5bf7f2f18953eef5a5</td><td></td><td></td><td></td></tr><tr><td>27961bc8173ac84fdbecacd01e5ed6f7ed92d4bd</td><td>To Appear in The IEEE 6th International Conference on Biometrics: Theory, Applications and <br/>Systems (BTAS), Sept. 29-Oct. 2, 2013, Washington DC, USA <br/>Automatic Multi-view Face Recognition via 3D Model Based Pose Regularization <br/>Department of Computer Science and Engineering @@ -13272,6 +17125,13 @@ <br/>Erik Learned-Miller <br/><b>University of Massachusetts Amherst</b><br/>Amherst, MA </td><td>('3219900', 'Gary B. Huang', 'gary b. huang')</td><td>{gbhuang,elm}@cs.umass.edu +</td></tr><tr><td>2717b044ae9933f9ab87f16d6c611352f66b2033</td><td>GNAS: A Greedy Neural Architecture Search Method for +<br/>Multi-Attribute Learning +<br/><b>Zhejiang University, 2Southwest Jiaotong University, 3Carnegie Mellon University</b></td><td>('2986516', 'Siyu Huang', 'siyu huang')<br/>('50079147', 'Xi Li', 'xi li')<br/>('1720488', 'Zhongfei Zhang', 'zhongfei zhang')</td><td>{siyuhuang,xilizju,zhongfei}@zju.edu.cn,zhiqicheng@gmail.com,alex@cs.cmu.edu +</td></tr><tr><td>2770b095613d4395045942dc60e6c560e882f887</td><td>GridFace: Face Rectification via Learning Local +<br/>Homography Transformations +<br/>Face++, Megvii Inc. +</td><td>('1848243', 'Erjin Zhou', 'erjin zhou')<br/>('2695115', 'Zhimin Cao', 'zhimin cao')<br/>('40055995', 'Jian Sun', 'jian sun')</td><td>{zej,czm,sunjian}@megvii.com </td></tr><tr><td>27cccf992f54966feb2ab4831fab628334c742d8</td><td>International Journal of Computer Applications (0975 – 8887) <br/>Volume 64– No.18, February 2013 <br/>Facial Expression Recognition by Statistical, Spatial @@ -13599,13 +17459,19 @@ </td><td>('3251767', 'Steve Branson', 'steve branson')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>sbranson@caltech.edu <br/>keh4@hi.is <br/>perona@caltech.edu -</td></tr><tr><td>4bd3de97b256b96556d19a5db71dda519934fd53</td><td>Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face +</td></tr><tr><td>4b61d8490bf034a2ee8aa26601d13c83ad7f843a</td><td>A Modulation Module for Multi-task Learning with +<br/>Applications in Image Retrieval +<br/><b>Northwestern University</b><br/>2 AIBee +<br/>3 Bytedance AI Lab +<br/><b>Carnegie Mellon University</b></td><td>('8343585', 'Xiangyun Zhao', 'xiangyun zhao')</td><td></td></tr><tr><td>4bd3de97b256b96556d19a5db71dda519934fd53</td><td>Latent Factor Guided Convolutional Neural Networks for Age-Invariant Face <br/>Recognition <br/><b>School of Electronic and Information Engineering, South China University of Technology</b><br/><b>Shenzhen Key Lab of Comp. Vis. and Pat. Rec., Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('2512949', 'Yandong Wen', 'yandong wen')<br/>('32787758', 'Zhifeng Li', 'zhifeng li')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td>yd.wen@siat.ac.cn, zhifeng.li@siat.ac.cn, yu.qiao@siat.ac.cn </td></tr><tr><td>4b04247c7f22410681b6aab053d9655cf7f3f888</td><td>Robust Face Recognition by Constrained Part-based <br/>Alignment </td><td>('1692992', 'Yuting Zhang', 'yuting zhang')<br/>('2370507', 'Kui Jia', 'kui jia')<br/>('7135663', 'Yueming Wang', 'yueming wang')<br/>('1734380', 'Gang Pan', 'gang pan')<br/>('1926757', 'Tsung-Han Chan', 'tsung-han chan')<br/>('1700297', 'Yi Ma', 'yi ma')</td><td></td></tr><tr><td>4b60e45b6803e2e155f25a2270a28be9f8bec130</td><td>Attribute Based Object Identification -</td><td>('1686318', 'Yuyin Sun', 'yuyin sun')<br/>('1766509', 'Liefeng Bo', 'liefeng bo')<br/>('1731079', 'Dieter Fox', 'dieter fox')</td><td></td></tr><tr><td>4b5eeea5dd8bd69331bd4bd4c66098b125888dea</td><td>Human Activity Recognition Using Conditional +</td><td>('1686318', 'Yuyin Sun', 'yuyin sun')<br/>('1766509', 'Liefeng Bo', 'liefeng bo')<br/>('1731079', 'Dieter Fox', 'dieter fox')</td><td></td></tr><tr><td>4b48e912a17c79ac95d6a60afed8238c9ab9e553</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>Minimum Margin Loss for Deep Face Recognition +</td><td>('49141822', 'Xin Wei', 'xin wei')<br/>('3552546', 'Hui Wang', 'hui wang')<br/>('2986129', 'Huan Wan', 'huan wan')</td><td></td></tr><tr><td>4b5eeea5dd8bd69331bd4bd4c66098b125888dea</td><td>Human Activity Recognition Using Conditional <br/>Random Fields and Privileged Information <br/>submitted to <br/>the designated by the General Assembly Composition of the @@ -13638,6 +17504,9 @@ <br/><b>Cambridge Research Laboratory</b><br/>Department of Engineering <br/><b>University of Cambridge</b></td><td>('1801052', 'Atsuto Maki', 'atsuto maki')<br/>('1745672', 'Roberto Cipolla', 'roberto cipolla')</td><td>atsuto.maki@crl.toshiba.co.uk <br/>cipolla@cam.ac.uk +</td></tr><tr><td>4bbe460ab1b279a55e3c9d9f488ff79884d01608</td><td>GAGAN: Geometry-Aware Generative Adversarial Networks +<br/>Jean Kossaifi∗ +<br/><b>Middlesex University London</b><br/><b>Imperial College London</b></td><td>('47801605', 'Linh Tran', 'linh tran')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td>{jean.kossaifi;linh.tran;i.panagakis;m.pantic}@imperial.ac.uk </td></tr><tr><td>4b3eaedac75ac419c2609e131ea9377ba8c3d4b8</td><td>FAST NEWTON ACTIVE APPEARANCE MODELS <br/>Jean Kossaifi(cid:63) <br/><b>cid:63) Imperial College London, UK</b><br/><b>University of Lincoln, UK</b><br/><b>University of Twente, The Netherlands</b></td><td>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>4b507a161af8a7dd41e909798b9230f4ac779315</td><td>A Theory of Multiplexed Illumination @@ -13980,6 +17849,8 @@ <br/>Recommendations for the Use of Performance Metrics </td><td>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('1707876', 'Fernando De la Torre', 'fernando de la torre')</td><td>1Carnegie Mellon University, Pittsburgh, PA, laszlo.jeni@ieee.org,ftorre@cs.cmu.edu <br/>2University of Pittsburgh, Pittsburgh, PA, jeffcohn@cs.cmu.edu +</td></tr><tr><td>11691f1e7c9dbcbd6dfd256ba7ac710581552baa</td><td>SoccerNet: A Scalable Dataset for Action Spotting in Soccer Videos +<br/><b>King Abdullah University of Science and Technology (KAUST), Saudi Arabia</b></td><td>('22314218', 'Silvio Giancola', 'silvio giancola')<br/>('41022271', 'Mohieddine Amine', 'mohieddine amine')<br/>('41015552', 'Tarek Dghaily', 'tarek dghaily')<br/>('2931652', 'Bernard Ghanem', 'bernard ghanem')</td><td>silvio.giancola@kaust.edu.sa, maa249@mail.aub.edu, tad05@mail.aub.edu, bernard.ghanem@kaust.edu.sa </td></tr><tr><td>11c04c4f0c234a72f94222efede9b38ba6b2306c</td><td>Real-Time Human Action Recognition by Luminance Field <br/>Trajectory Analysis <br/>Dept of Computing @@ -14030,7 +17901,7 @@ </td><td>('8118823', 'Bala Shankar', 'bala shankar')<br/>('27686729', 'S R Kumar', 's r kumar')</td><td></td></tr><tr><td>11b3877df0213271676fa8aa347046fd4b1a99ad</td><td>Unsupervised Identification of Multiple Objects of <br/>Interest from Multiple Images: dISCOVER <br/><b>Carnegie Mellon University</b></td><td>('1713589', 'Devi Parikh', 'devi parikh')<br/>('1746230', 'Tsuhan Chen', 'tsuhan chen')</td><td>{dparikh,tsuhan}@cmu.edu -</td></tr><tr><td>1130c38e88108cf68b92ecc61a9fc5aeee8557c9</td><td>Dynamically Encoded Actions based on Spacetime Saliency +</td></tr><tr><td>112780a7fe259dc7aff2170d5beda50b2bfa7bda</td><td></td><td></td><td></td></tr><tr><td>1130c38e88108cf68b92ecc61a9fc5aeee8557c9</td><td>Dynamically Encoded Actions based on Spacetime Saliency <br/><b>Institute of Electrical Measurement and Measurement Signal Processing, TU Graz, Austria</b><br/><b>York University, Toronto, Canada</b></td><td>('2322150', 'Christoph Feichtenhofer', 'christoph feichtenhofer')<br/>('1718587', 'Axel Pinz', 'axel pinz')<br/>('1709096', 'Richard P. Wildes', 'richard p. wildes')</td><td>{feichtenhofer, axel.pinz}@tugraz.at <br/>wildes@cse.yorku.ca </td></tr><tr><td>11b89011298e193d9e6a1d99302221c1d8645bda</td><td>Structured Feature Selection @@ -14043,7 +17914,17 @@ <br/>1Advanced Digital Sciences Center, Singapore <br/><b>School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore</b><br/><b>School of ICE, Beijing University of Posts and Telecommunications, Beijing, China</b><br/><b>University of Illinois at Urbana-Champaign, Urbana, IL, USA</b><br/><b>Tsinghua University, Beijing, China</b></td><td>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('22804340', 'Gang Wang', 'gang wang')<br/>('1774956', 'Weihong Deng', 'weihong deng')<br/>('1742248', 'Pierre Moulin', 'pierre moulin')<br/>('39491387', 'Jie Zhou', 'jie zhou')</td><td>jiwen.lu@adsc.com.sg; wanggang@ntu.edu.sg; whdeng@bupt.edu.cn; <br/>moulin@ifp.uiuc.edu; jzhou@tsinghua.edu.cn -</td></tr><tr><td>11ac88aebe0230e743c7ea2c2a76b5d4acbfecd0</td><td>Hybrid Cascade Model for Face Detection in the Wild +</td></tr><tr><td>1190cba0cae3c8bb81bf80d6a0a83ae8c41240bc</td><td>Squared Earth Mover’s Distance Loss for Training +<br/>Deep Neural Networks on Ordered-Classes +<br/>Dept. of Computer Science +<br/><b>Stony Brook University</b><br/>Chen-Ping Yu +<br/><b>Phiar Technologies, Inc</b></td><td>('2321406', 'Le Hou', 'le hou')</td><td></td></tr><tr><td>111d0b588f3abbbea85d50a28c0506f74161e091</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 134 – No.10, January 2016 +<br/>Facial Expression Recognition from Visual Information +<br/>using Curvelet Transform +<br/>Surabhi Group of Institution Bhopal +<br/>systems. Further applications +</td><td>('6837599', 'Pratiksha Singh', 'pratiksha singh')</td><td></td></tr><tr><td>11ac88aebe0230e743c7ea2c2a76b5d4acbfecd0</td><td>Hybrid Cascade Model for Face Detection in the Wild <br/>Based on Normalized Pixel Difference and a Deep <br/>Convolutional Neural Network <br/>Darijan Marčetić[0000-0002-6556-665X], Martin Soldić[0000-0002-4031-0404] @@ -14057,6 +17938,9 @@ <br/>Engineering <br/><b>Chosun University</b><br/>Gwangju, Korea </td><td>('2806903', 'Yun-Hee Han', 'yun-hee han')</td><td>Yhhan1059@gmail.com +</td></tr><tr><td>7d2556d674ad119cf39df1f65aedbe7493970256</td><td>Now You Shake Me: Towards Automatic 4D Cinema +<br/><b>University of Toronto</b><br/><b>Vector Institute</b><br/>http://www.cs.toronto.edu/˜henryzhou/movie4d/ +</td><td>('2481662', 'Yuhao Zhou', 'yuhao zhou')<br/>('37895334', 'Sanja Fidler', 'sanja fidler')</td><td>{henryzhou, makarand, fidler}@cs.toronto.edu </td></tr><tr><td>7d94fd5b0ca25dd23b2e36a2efee93244648a27b</td><td>Convolutional Network for Attribute-driven and Identity-preserving Human Face <br/>Generation <br/><b>The Hong Kong Polytechnic University, Hong Kong</b><br/><b>bSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China</b></td><td>('1701799', 'Mu Li', 'mu li')<br/>('1724520', 'Wangmeng Zuo', 'wangmeng zuo')<br/>('1698371', 'David Zhang', 'david zhang')</td><td></td></tr><tr><td>7d8c2d29deb80ceed3c8568100376195ce0914cb</td><td>Identity-Aware Textual-Visual Matching with Latent Co-attention @@ -14088,7 +17972,10 @@ </td><td>('1714536', 'Erik Learned-Miller', 'erik learned-miller')<br/>('1799600', 'Gary Huang', 'gary huang')<br/>('2895705', 'Aruni RoyChowdhury', 'aruni roychowdhury')<br/>('3131569', 'Haoxiang Li', 'haoxiang li')<br/>('1745420', 'Gang Hua', 'gang hua')</td><td></td></tr><tr><td>7d73adcee255469aadc5e926066f71c93f51a1a5</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE <br/>1283 <br/>ICASSP 2016 -</td><td></td><td></td></tr><tr><td>7d9fe410f24142d2057695ee1d6015fb1d347d4a</td><td>Facial Expression Feature Extraction Based on +</td><td></td><td></td></tr><tr><td>7df4f96138a4e23492ea96cf921794fc5287ba72</td><td>A Jointly Learned Deep Architecture for Facial Attribute Analysis and Face +<br/>Detection in the Wild +<br/><b>Fudan University</b></td><td>('37391748', 'Keke He', 'keke he')<br/>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')</td><td>{kkhe15, yanweifu, xyxue}@fudan.edu.cn +</td></tr><tr><td>7d9fe410f24142d2057695ee1d6015fb1d347d4a</td><td>Facial Expression Feature Extraction Based on <br/>FastLBP <br/><b>Beijing, China</b><br/><b>Beijing, China</b><br/>facial expression </td><td>('1921151', 'Ya Zheng', 'ya zheng')<br/>('2780963', 'Xiuxin Chen', 'xiuxin chen')<br/>('2671173', 'Chongchong Yu', 'chongchong yu')<br/>('39681852', 'Cheng Gao', 'cheng gao')</td><td>Email: zy_lovedabao@163.com @@ -14099,6 +17986,11 @@ </td></tr><tr><td>7dffe7498c67e9451db2d04bb8408f376ae86992</td><td>LEAR-INRIA submission for the THUMOS workshop <br/>LEAR, INRIA, France </td><td>('40465030', 'Heng Wang', 'heng wang')</td><td>firstname.lastname@inria.fr +</td></tr><tr><td>7df268a3f4da7d747b792882dfb0cbdb7cc431bc</td><td>Semi-supervised Adversarial Learning to Generate +<br/>Photorealistic Face Images of New Identities from 3D +<br/>Morphable Model +<br/><b>Imperial College London, UK</b><br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b></td><td>('2151914', 'Baris Gecer', 'baris gecer')<br/>('48467774', 'Binod Bhattarai', 'binod bhattarai')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('1700968', 'Tae-Kyun Kim', 'tae-kyun kim')</td><td>{b.gecer,b.bhattarai,tk.kim}@imperial.ac.uk, +<br/>j.kittler@surrey.ac.uk </td></tr><tr><td>7d3f6dd220bec883a44596ddec9b1f0ed4f6aca2</td><td>2106 <br/>Linear Regression for Face Recognition </td><td>('2095953', 'Imran Naseem', 'imran naseem')<br/>('2444665', 'Roberto Togneri', 'roberto togneri')<br/>('1698675', 'Mohammed Bennamoun', 'mohammed bennamoun')</td><td></td></tr><tr><td>7de386bf2a1b2436c836c0cc1f1f23fccb24aad6</td><td>Finding What the Driver Does @@ -14163,6 +18055,9 @@ <br/>and Sparse Representation <br/><b>Institute of control science and engineering</b><br/><b>University of Science and Technology Beijing</b><br/>1,2,330 Xueyuan Road, Haidian District, Beijing 100083 P. R.China </td><td>('11241192', 'Deng Nan', 'deng nan')<br/>('7814565', 'Zhengguang Xu', 'zhengguang xu')</td><td>1dengnan666666@163.com, 2xzg_1@263.net, 3 xiaobian@ustb.edu.cn +</td></tr><tr><td>2902f62457fdf7e8e8ee77a9155474107a2f423e</td><td>Non-rigid 3D Shape Registration using an +<br/>Adaptive Template +<br/><b>University of York, UK</b></td><td>('1694260', 'Hang Dai', 'hang dai')<br/>('1737428', 'Nick Pears', 'nick pears')<br/>('32131827', 'William Smith', 'william smith')</td><td>{hd816,nick.pears,william.smith}@york.ac.uk </td></tr><tr><td>29d3ed0537e9ef62fd9ccffeeb72c1beb049e1ea</td><td>Parametric Dictionaries and Feature Augmentation for <br/>Continuous Domain Adaptation∗ <br/>Adobe Research @@ -14237,13 +18132,26 @@ <br/>yanrong@cs.cmu.edu <br/>alex+@cs.cmu.edu </td></tr><tr><td>290136947fd44879d914085ee51d8a4f433765fa</td><td>On a Taxonomy of Facial Features -</td><td>('1817623', 'Brendan Klare', 'brendan klare')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>291f527598c589fb0519f890f1beb2749082ddfd</td><td>Seeing People in Social Context: Recognizing +</td><td>('1817623', 'Brendan Klare', 'brendan klare')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>2957715e96a18dbb5ed5c36b92050ec375214aa6</td><td>Improving Face Attribute Detection with Race and Gender Diversity +<br/>InclusiveFaceNet: +</td><td>('3766392', 'Hee Jung Ryu', 'hee jung ryu')</td><td></td></tr><tr><td>291f527598c589fb0519f890f1beb2749082ddfd</td><td>Seeing People in Social Context: Recognizing <br/>People and Social Relationships <br/><b>University of Illinois at Urbana-Champaign, Urbana, IL</b><br/><b>Kodak Research Laboratories, Rochester, NY</b></td><td>('22804340', 'Gang Wang', 'gang wang')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')</td><td></td></tr><tr><td>291265db88023e92bb8c8e6390438e5da148e8f5</td><td>MS-Celeb-1M: A Dataset and Benchmark for <br/>Large-Scale Face Recognition <br/>Microsoft Research </td><td>('3133575', 'Yandong Guo', 'yandong guo')<br/>('1684635', 'Lei Zhang', 'lei zhang')<br/>('1689532', 'Yuxiao Hu', 'yuxiao hu')<br/>('1722627', 'Xiaodong He', 'xiaodong he')<br/>('1800422', 'Jianfeng Gao', 'jianfeng gao')</td><td>{yandong.guo,leizhang,yuxiao.hu,xiaohe,jfgao}@microsoft.com -</td></tr><tr><td>297d3df0cf84d24f7efea44f87c090c7d9be4bed</td><td>Appearance-based 3-D Face Recognition from +</td></tr><tr><td>29c340c83b3bbef9c43b0c50b4d571d5ed037cbd</td><td>Stacked Dense U-Nets with Dual +<br/>Transformers for Robust Face Alignment +<br/>https://github.com/deepinsight/insightface +<br/>https://jiankangdeng.github.io/ +<br/>https://ibug.doc.ic.ac.uk/people/nxue +<br/>Stefanos Zafeiriou2 +<br/>https://wp.doc.ic.ac.uk/szafeiri/ +<br/>1 InsightFace +<br/>Shanghai, China +<br/>2 IBUG +<br/><b>Imperial College London</b><br/>London, UK +</td><td>('3007274', 'Jia Guo', 'jia guo')<br/>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('3007274', 'Jia Guo', 'jia guo')<br/>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('4091869', 'Niannan Xue', 'niannan xue')</td><td></td></tr><tr><td>297d3df0cf84d24f7efea44f87c090c7d9be4bed</td><td>Appearance-based 3-D Face Recognition from <br/>Video <br/><b>University of Maryland, Center for Automation Research</b><br/>A.V. Williams Building <br/><b>College Park, MD</b><br/><b>The Robotics Institute, Carnegie Mellon University</b><br/>5000 Forbes Avenue, Pittsburgh, PA 15213 @@ -14431,6 +18339,14 @@ <br/>Networks <br/>Department of Electronics and Communication Engineering and <br/><b>Computer Vision Group, L. D. College of Engineering, Ahmedabad, India</b></td><td>('23922616', 'Vandit Gajjar', 'vandit gajjar')</td><td> gajjar.vandit.381@ldce.ac.in +</td></tr><tr><td>7c47da191f935811f269f9ba3c59556c48282e80</td><td>Robust Eye Centers Localization +<br/>with Zero–Crossing Encoded Image Projections +<br/>Image Processing and Analysis Laboratory +<br/><b>University Politehnica of Bucharest, Romania, Address Splaiul Independent ei</b><br/>Image Processing and Analysis Laboratory +<br/><b>University Politehnica of Bucharest, Romania, Address Splaiul Independent ei</b><br/>Image Processing and Analysis Laboratory +<br/><b>University Politehnica of Bucharest, Romania, Address Splaiul Independent ei</b></td><td>('2143956', 'Laura Florea', 'laura florea')<br/>('2760434', 'Corneliu Florea', 'corneliu florea')<br/>('2905899', 'Constantin Vertan', 'constantin vertan')</td><td>laura.florea@upb.ro +<br/>corneliu.florea@upb.ro +<br/>constantin.vertan@upb.ro </td></tr><tr><td>7c7ab59a82b766929defd7146fd039b89d67e984</td><td>Improving Multiview Face Detection with <br/>Multi-Task Deep Convolutional Neural Networks <br/>Microsoft Research @@ -14443,11 +18359,35 @@ <br/>Harini Veeraraghavan Stefan Atev Nathaniel Bird Paul Schrater Nikolaos Papanikolopoulos† <br/>Department of Computer Science and Engineering <br/><b>University of Minnesota</b></td><td></td><td>{harini,atev,bird,schrater,npapas}@cs.umn.edu +</td></tr><tr><td>7c1cfab6b60466c13f07fe028e5085a949ec8b30</td><td>Deep Feature Consistent Variational Autoencoder +<br/><b>University of Nottingham, Ningbo China</b><br/><b>Shenzhen University, Shenzhen China</b><br/><b>University of Nottingham, Ningbo China</b><br/><b>University of Nottingham, Ningbo China</b></td><td>('3468964', 'Xianxu Hou', 'xianxu hou')<br/>('1687690', 'Linlin Shen', 'linlin shen')<br/>('39508183', 'Ke Sun', 'ke sun')<br/>('1698461', 'Guoping Qiu', 'guoping qiu')</td><td>xianxu.hou@nottingham.edu.cn +<br/>llshen@szu.edu.cn +<br/>ke.sun@nottingham.edu.cn +<br/>guoping.qiu@nottingham.edu.cn </td></tr><tr><td>7c45b5824645ba6d96beec17ca8ecfb22dfcdd7f</td><td>News image annotation on a large parallel text-image corpus <br/>Universit´e de Rennes 1/IRISA, CNRS/IRISA, INRIA Rennes-Bretagne Atlantique <br/>Campus de Beaulieu <br/>35042 Rennes Cedex, France </td><td>('1694537', 'Pierre Tirilly', 'pierre tirilly')<br/>('1735666', 'Vincent Claveau', 'vincent claveau')<br/>('2436627', 'Patrick Gros', 'patrick gros')</td><td>ptirilly@irisa.fr, vclaveau@irisa.fr, pgros@inria.fr +</td></tr><tr><td>7c17280c9193da3e347416226b8713b99e7825b8</td><td>VideoCapsuleNet: A Simplified Network for Action +<br/>Detection +<br/>Kevin Duarte +<br/>Yogesh S Rawat +<br/>Center for Research in Computer Vision +<br/><b>University of Central Florida</b><br/>Orlando, FL 32816 +</td><td>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>kevin_duarte@knights.ucf.edu +<br/>yogesh@crcv.ucf.edu +<br/>shah@crcv.ucf.edu +</td></tr><tr><td>7cffcb4f24343a924a8317d560202ba9ed26cd0b</td><td>The Unconstrained Ear Recognition Challenge +<br/><b>University of Ljubljana</b><br/>Ljubljana, Slovenia +<br/>IIT Kharagpur +<br/>Kharagpur, India +<br/><b>University of Colorado Colorado Springs</b><br/>Colorado Springs, CO, USA +<br/><b>Islamic Azad University</b><br/>Qazvin, Iran +<br/><b>Imperial College London</b><br/>London, UK +<br/>ITU Department of Computer Engineering +<br/>Istanbul, Turkey +</td><td>('34862665', 'Peter Peer', 'peter peer')<br/>('3110004', 'Anjith George', 'anjith george')<br/>('2173052', 'Adil Ahmad', 'adil ahmad')<br/>('39000630', 'Elshibani Omar', 'elshibani omar')<br/>('1760117', 'Terrance E. Boult', 'terrance e. boult')<br/>('3062107', 'Reza Safdari', 'reza safdari')<br/>('47943220', 'Yuxiang Zhou', 'yuxiang zhou')<br/>('23981209', 'Dogucan Yaman', 'dogucan yaman')</td><td>ziga.emersic@fri.uni-lj.si </td></tr><tr><td>7c0a6824b556696ad7bdc6623d742687655852db</td><td>18th Telecommunications forum TELFOR 2010 <br/>Serbia, Belgrade, November 23-25, 2010. <br/>MPCA+DATER: A Novel Approach for Face @@ -14506,6 +18446,34 @@ <br/><b>University of Massachusetts Amherst</b><br/>Amherst, MA <br/>Erik Learned-Miller </td><td>('3219900', 'Gary B. Huang', 'gary b. huang')<br/>('2246870', 'Vidit Jain', 'vidit jain')</td><td>fgbhuang,vidit,elmg@cs.umass.edu +</td></tr><tr><td>7c825562b3ff4683ed049a372cb6807abb09af2a</td><td>Finding Tiny Faces +<br/>Supplementary Materials +<br/><b>Robotics Institute</b><br/><b>Carnegie Mellon University</b><br/>1. Error analysis +<br/>Quantitative analysis We plot the distribution of error modes among false positives in Fig. 1 and the impact of object +<br/>characteristics on detection performance in Fig. 2 and Fig. 3. +<br/>Qualitative analysis We show top 20 scoring false positives in Fig. 4. +<br/>2. Experimental details +<br/>Multi-scale features Inspired by the way [3] trains “FCN-8s at-once”, we scale the learning rate of predictor built on +<br/>top of each layer by a fixed constant. Specifically, we use a scaling factor of 1 for res4, 0.1 for res3, and 0.01 for res2. +<br/>One more difference between our model and [3] is that: instead of predicting at original resolution, our model predicts +<br/>at the resolution of res3 feature (downsampled by 8X comparing to input resolution). +<br/>Input sampling We first randomly re-scale the input image by 0.5X, 1X, or 2X. Then we randomly crop a 500x500 +<br/>image region out of the re-scaled input. We pad with average RGB value (prior to average subtraction) when cropping +<br/>outside image boundary. +<br/>Border cases Similar to [2], we ignore gradients coming from heatmap locations whose detection windows cross the +<br/>image boundary. The only difference is, we treat padded average pixels (as described in Input sampling) as outside +<br/>image boundary as well. +<br/>Online hard mining and balanced sampling We apply hard mining on both positive and negative examples. Our +<br/>implementation is simpler yet still effective comparing to [4]. We set a small threshold (0.03) on classification loss +<br/>to filter out easy locations. Then we sample at most 128 locations for both positive and negative (respectively) from +<br/>remaining ones whose losses are above the threshold. We compare training with and without hard mining on validation +<br/>performance in Table 1. +<br/>Loss function Our loss function is formulated in the same way as [2]. Note that we also use Huber loss as the loss +<br/>function for bounding box regression. +<br/>Bounding box regression Our bounding box regression is formulated as [2] and trained jointly with classification +<br/>using stochastic gradient descent. We compare between testing with and without regression in terms of performance +<br/>on WIDER FACE validation set. +</td><td>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td>{peiyunh,deva}@cs.cmu.edu </td></tr><tr><td>7c7b0550ec41e97fcfc635feffe2e53624471c59</td><td>1051-4651/14 $31.00 © 2014 IEEE <br/>DOI 10.1109/ICPR.2014.124 <br/>660 @@ -14519,6 +18487,11 @@ <br/><b>Intelligence Computing Research Center</b><br/>HIT Shenzhen Graduate School <br/>Shenzhen, China </td><td>('24233679', 'Languang He', 'languang he')<br/>('1747105', 'Xuan Wang', 'xuan wang')<br/>('10106946', 'Chenglong Yu', 'chenglong yu')<br/>('38700402', 'Kun Wu', 'kun wu')</td><td>{telent, wangxuan, ycl, wukun} @cs.hitsz.edu.cn +</td></tr><tr><td>7ca7255c2e0c86e4adddbbff2ce74f36b1dc522d</td><td>Stereo Matching for Unconstrained Face Recognition +<br/>Ph.D. Proposal +<br/><b>University of Maryland</b><br/>Department of Computer Science +<br/><b>College Park, MD</b><br/>May 10, 2009 +</td><td>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')</td><td>carlos@cs.umd.edu </td></tr><tr><td>7c42371bae54050dbbf7ded1e7a9b4109a23a482</td><td>The International Arab Journal of Information Technology, Vol. 12, No. 2, March 2015 183 <br/>Optimized Features Selection using Hybrid PSO- <br/>GA for Multi-View Gender Classification @@ -14535,23 +18508,138 @@ <br/>School of Electrical, Electronic and Computer Engineering <br/><b>University of Newcastle</b><br/>Newcastle upon Tyne, NE1 7RU <br/>UNITED KINDOM -</td><td>('3156162', 'R. M. MUTELO', 'r. m. mutelo')</td><td></td></tr><tr><td>7c1e1c767f7911a390d49bed4f73952df8445936</td><td>NON-RIGID OBJECT DETECTION WITH LOCAL INTERLEAVED SEQUENTIAL ALIGNMENT (LISA) +</td><td>('3156162', 'R. M. MUTELO', 'r. m. mutelo')</td><td></td></tr><tr><td>7c9a65f18f7feb473e993077d087d4806578214e</td><td>SpringerLink - Zeitschriftenbeitrag +<br/>http://www.springerlink.com/content/93hr862660nl1164/?p=abe5352... +<br/>Deutsch +<br/>Deutsch +<br/>Go +<br/>Vorherige Beitrag Nächste Beitrag +<br/>Beitrag markieren +<br/>In den Warenkorb legen +<br/>Zu gespeicherten Artikeln +<br/>hinzufügen +<br/>Permissions & Reprints +<br/>Diesen Artikel empfehlen +<br/>Ergebnisse +<br/>finden +<br/>Erweiterte Suche +<br/>Go +<br/>im gesamten Inhalt +<br/>in dieser Zeitschrift +<br/>in diesem Heft +<br/>Diesen Beitrag exportieren +<br/>Diesen Beitrag exportieren als RIS +<br/>| Text +<br/>Text +<br/>PDF +<br/>PDF ist das gebräuchliche Format +<br/>für Online Publikationen. Die Größe +<br/>dieses Dokumentes beträgt 564 +<br/>Kilobyte. Je nach Art Ihrer +<br/>Internetverbindung kann der +<br/>Download einige Zeit in Anspruch +<br/>nehmen. +<br/>öffnen: Gesamtdokument +<br/>Publikationsart Subject Collections +<br/>Zurück zu: Journal Issue +<br/>Athens Authentication Point +<br/>Zeitschriftenbeitrag +<br/>Willkommen! +<br/>Um unsere personalisierten +<br/>Angebote nutzen zu können, +<br/>müssen Sie angemeldet sein. +<br/>Login +<br/>Jetzt registrieren +<br/>Zugangsdaten vergessen? +<br/>Hilfe. +<br/>Mein Menü +<br/>Markierte Beiträge +<br/>Alerts +<br/>Meine Bestellungen +<br/>Private emotions versus social interaction: a data-driven approach towards +<br/>analysing emotion in speech +<br/>Zeitschrift +<br/>Verlag +<br/>ISSN +<br/>Heft +<br/>Kategorie +<br/>DOI +<br/>Seiten +<br/>Subject Collection +<br/>SpringerLink Date +<br/>User Modeling and User-Adapted Interaction +<br/>Springer Netherlands +<br/>0924-1868 (Print) 1573-1391 (Online) +<br/>Volume 18, Numbers 1-2 / Februar 2008 +<br/>Original Paper +<br/>10.1007/s11257-007-9039-4 +<br/>175-206 +<br/>Informatik +<br/>Freitag, 12. Oktober 2007 +<br/>Gespeicherte Beiträge +<br/>Alle +<br/>Favoriten +<br/>(1) Lehrstuhl für Mustererkennung, FAU Erlangen – Nürnberg, Martensstr. 3, 91058 Erlangen, +<br/>Germany +<br/>Received: 3 July 2006 Accepted: 14 January 2007 Published online: 12 October 2007 +</td><td>('1745089', 'Anton Batliner', 'anton batliner')<br/>('1732747', 'Stefan Steidl', 'stefan steidl')<br/>('2596771', 'Christian Hacker', 'christian hacker')<br/>('1739326', 'Elmar Nöth', 'elmar nöth')</td><td></td></tr><tr><td>7c1e1c767f7911a390d49bed4f73952df8445936</td><td>NON-RIGID OBJECT DETECTION WITH LOCAL INTERLEAVED SEQUENTIAL ALIGNMENT (LISA) <br/>Non-Rigid Object Detection with Local <br/>Interleaved Sequential Alignment (LISA) <br/>and Tom´aˇs Svoboda, Member, IEEE -</td><td>('35274952', 'Karel Zimmermann', 'karel zimmermann')<br/>('2687885', 'David Hurych', 'david hurych')</td><td></td></tr><tr><td>7c349932a3d083466da58ab1674129600b12b81c</td><td></td><td></td><td></td></tr><tr><td>1648cf24c042122af2f429641ba9599a2187d605</td><td>Boosting Cross-Age Face Verification via Generative Age Normalization +</td><td>('35274952', 'Karel Zimmermann', 'karel zimmermann')<br/>('2687885', 'David Hurych', 'david hurych')</td><td></td></tr><tr><td>7cf579088e0456d04b531da385002825ca6314e2</td><td>Emotion Detection on TV Show Transcripts with +<br/>Sequence-based Convolutional Neural Networks +<br/>Mathematics and Computer Science +<br/>Mathematics and Computer Science +<br/><b>Emory University</b><br/>Atlanta, GA 30322, USA +<br/><b>Emory University</b><br/>Atlanta, GA 30322, USA +</td><td>('10669356', 'Sayyed M. Zahiri', 'sayyed m. zahiri')<br/>('4724587', 'Jinho D. Choi', 'jinho d. choi')</td><td>sayyed.zahiri@emory.edu +<br/>jinho.choi@emory.edu +</td></tr><tr><td>7c80d91db5977649487388588c0c823080c9f4b4</td><td>DocFace: Matching ID Document Photos to Selfies∗ +<br/><b>Michigan State University</b><br/>East Lansing, Michigan, USA +</td><td>('9644181', 'Yichun Shi', 'yichun shi')<br/>('1739705', 'Anil K. Jain', 'anil k. jain')</td><td>shiyichu@msu.edu, jain@cse.msu.edu +</td></tr><tr><td>7c349932a3d083466da58ab1674129600b12b81c</td><td></td><td></td><td></td></tr><tr><td>7c30ea47f5ae1c5abd6981d409740544ed16ed16</td><td>ROITBERG, AL-HALAH, STIEFELHAGEN: NOVELTY DETECTION FOR ACTION RECOGNITION +<br/>Informed Democracy: Voting-based Novelty +<br/>Detection for Action Recognition +<br/><b>Karlsruhe Institute of Technology</b><br/>76131 Karlsruhe, +<br/>Germany +</td><td>('33390229', 'Alina Roitberg', 'alina roitberg')<br/>('2256981', 'Ziad Al-Halah', 'ziad al-halah')<br/>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')</td><td>alina.roitberg@kit.edu +<br/>ziad.al-halah@kit.edu +<br/>rainer.stiefelhagen@kit.edu +</td></tr><tr><td>1648cf24c042122af2f429641ba9599a2187d605</td><td>Boosting Cross-Age Face Verification via Generative Age Normalization <br/>(cid:2) Orange Labs, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France <br/>† Eurecom, 450 route des Chappes, 06410 Biot, France </td><td>('3116433', 'Grigory Antipov', 'grigory antipov')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')<br/>('2341854', 'Moez Baccouche', 'moez baccouche')</td><td>{grigory.antipov,moez.baccouche}@orange.com <br/>jean-luc.dugelay@eurecom.fr -</td></tr><tr><td>160259f98a6ec4ec3e3557de5e6ac5fa7f2e7f2b</td><td>Discriminant Multi-Label Manifold Embedding for Facial Action Unit +</td></tr><tr><td>162403e189d1b8463952fa4f18a291241275c354</td><td>Action Recognition with Spatio-Temporal +<br/>Visual Attention on Skeleton Image Sequences +<br/>With a strong ability of modeling sequential data, Recur- +<br/>rent Neural Networks (RNN) with Long Short-Term Memory +<br/>(LSTM) neurons outperform the previous hand-crafted feature +<br/>based methods [9], [10]. Each skeleton frame is converted into +<br/>a feature vector and the whole sequence is fed into the RNN. +<br/>Despite the strong ability in modeling temporal sequences, +<br/>RNN structures lack the ability to efficiently learn the spatial +<br/>relations between the joints. To better use spatial information, +<br/>a hierarchical structure is proposed in [11], [12] that feeds +<br/>the joints into the network as several pre-defined body part +<br/>groups. However, +<br/>limit +<br/>the effectiveness of representing spatial relations. A spatio- +<br/>temporal 2D LSTM (ST-LSTM) network [13] is proposed +<br/>to learn the spatial and temporal relations simultaneously. +<br/>Furthermore, a two-stream RNN structure [14] is proposed to +<br/>learn the spatio-temporal relations with two RNN branches. +<br/>the pre-defined body regions still +</td><td>('21518096', 'Zhengyuan Yang', 'zhengyuan yang')<br/>('3092578', 'Yuncheng Li', 'yuncheng li')<br/>('1706007', 'Jianchao Yang', 'jianchao yang')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')</td><td></td></tr><tr><td>160259f98a6ec4ec3e3557de5e6ac5fa7f2e7f2b</td><td>Discriminant Multi-Label Manifold Embedding for Facial Action Unit <br/>Detection <br/>Signal Procesing Laboratory (LTS5), ´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland </td><td>('1697965', 'Hua Gao', 'hua gao')<br/>('1710257', 'Jean-Philippe Thiran', 'jean-philippe thiran')</td><td>anil.yuce@epfl.ch, hua.gao@epfl.ch, jean-philippe.thiran@epfl.ch </td></tr><tr><td>16671b2dc89367ce4ed2a9c241246a0cec9ec10e</td><td>2006 <br/>Detecting the Number of Clusters <br/>in n-Way Probabilistic Clustering -</td><td>('1788526', 'Zhaoshui He', 'zhaoshui he')<br/>('1747156', 'Andrzej Cichocki', 'andrzej cichocki')<br/>('1795838', 'Shengli Xie', 'shengli xie')<br/>('1775180', 'Kyuwan Choi', 'kyuwan choi')</td><td></td></tr><tr><td>16bce9f940bb01aa5ec961892cc021d4664eb9e4</td><td>Mutual Component Analysis for Heterogeneous Face Recognition +</td><td>('1788526', 'Zhaoshui He', 'zhaoshui he')<br/>('1747156', 'Andrzej Cichocki', 'andrzej cichocki')<br/>('1795838', 'Shengli Xie', 'shengli xie')<br/>('1775180', 'Kyuwan Choi', 'kyuwan choi')</td><td></td></tr><tr><td>16fdd6d842475e6fbe58fc809beabbed95f0642e</td><td>Learning Temporal Embeddings for Complex Video Analysis +<br/><b>Stanford University, 2Simon Fraser University</b></td><td>('34066479', 'Vignesh Ramanathan', 'vignesh ramanathan')<br/>('10771328', 'Greg Mori', 'greg mori')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td>{vigneshr, kdtang}@cs.stanford.edu, mori@cs.sfu.ca, feifeili@cs.stanford.edu +</td></tr><tr><td>16bce9f940bb01aa5ec961892cc021d4664eb9e4</td><td>Mutual Component Analysis for Heterogeneous Face Recognition <br/>39 <br/>Heterogeneous face recognition, also known as cross-modality face recognition or inter-modality face recogni- <br/>tion, refers to matching two face images from alternative image modalities. Since face images from different @@ -14585,7 +18673,7 @@ <br/>of Technology Sydney, 81 Broadway, Ultimo, NSW 2007, Australia; e-mail: qiang.li-2@student.uts.edu.au, <br/>dacheng.tao@uts.edu.au; X. Li, the Center for OPTical IMagery Analysis and Learning (OPTIMAL), State <br/>nese Academy of Sciences, Xi’an 710119, Shaanxi, China; e-mail: xuelong li@opt.ac.cn. -</td></tr><tr><td>16892074764386b74b6040fe8d6946b67a246a0b</td><td></td><td></td><td></td></tr><tr><td>16395b40e19cbc6d5b82543039ffff2a06363845</td><td>Action Recognition in Video Using Sparse Coding and Relative Features +</td></tr><tr><td>16de1324459fe8fdcdca80bba04c3c30bb789bdf</td><td></td><td></td><td></td></tr><tr><td>16892074764386b74b6040fe8d6946b67a246a0b</td><td></td><td></td><td></td></tr><tr><td>16395b40e19cbc6d5b82543039ffff2a06363845</td><td>Action Recognition in Video Using Sparse Coding and Relative Features <br/>Anal´ı Alfaro <br/>P. Universidad Catolica de Chile <br/>P. Universidad Catolica de Chile @@ -14599,6 +18687,19 @@ </td></tr><tr><td>1677d29a108a1c0f27a6a630e74856e7bddcb70d</td><td>Efficient Misalignment-Robust Representation <br/>for Real-Time Face Recognition <br/><b>The Hong Kong Polytechnic University, Hong Kong</b></td><td>('5828998', 'Meng Yang', 'meng yang')<br/>('36685537', 'Lei Zhang', 'lei zhang')<br/>('1698371', 'David Zhang', 'david zhang')</td><td>{csmyang,cslzhang}@comp.polyu.edu.hk +</td></tr><tr><td>16b9d258547f1eccdb32111c9f45e2e4bbee79af</td><td>2006 Xiyuan Ave. +<br/>Chengdu, Sichuan 611731 +<br/>2006 Xiyuan Ave. +<br/>Chengdu, Sichuan 611731 +<br/><b>University of Electronic Science and Technology of China</b><br/><b>Johns Hopkins University</b><br/>3400 N. Charles St. +<br/>Baltimore, Maryland 21218 +<br/><b>Johns Hopkins University</b><br/>3400 N. Charles St. +<br/>Baltimore, Maryland 21218 +<br/>NormFace: L2 Hypersphere Embedding for Face Verification +<br/><b>University of Electronic Science and Technology of China</b></td><td>('1709439', 'Jian Cheng', 'jian cheng')<br/>('40031188', 'Xiang Xiang', 'xiang xiang')<br/>('1746141', 'Alan L. Yuille', 'alan l. yuille')<br/>('39369840', 'Feng Wang', 'feng wang')</td><td>feng.w(cid:29)@gmail.com +<br/>chengjian@uestc.edu.cn +<br/>xxiang@cs.jhu.edu +<br/>alan.yuille@jhu.edu </td></tr><tr><td>16c884be18016cc07aec0ef7e914622a1a9fb59d</td><td>UNIVERSITÉ DE GRENOBLE <br/>No attribué par la bibliothèque <br/>THÈSE @@ -14651,6 +18752,10 @@ </td><td>('3075941', 'Fengyi Song', 'fengyi song')<br/>('2248421', 'Xiaoyang Tan', 'xiaoyang tan')<br/>('1680768', 'Songcan Chen', 'songcan chen')</td><td>f.song@nuaa.edu.cn <br/>x.tan@nuaa.edu.cn <br/>s.chen@nuaa.edu.cn +</td></tr><tr><td>164b0e2a03a5a402f66c497e6c327edf20f8827b</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Sparse Deep Transfer Learning for +<br/>Convolutional Neural Network +<br/><b>The Chinese University of Hong Kong, Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China</b></td><td>('2335888', 'Jiaming Liu', 'jiaming liu')<br/>('47903936', 'Yali Wang', 'yali wang')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td>jiaming.liu@email.ucr.edu, {yl.wang, yu.qiao}@siat.ac.cn </td></tr><tr><td>16286fb0f14f6a7a1acc10fcd28b3ac43f12f3eb</td><td>J Nonverbal Behav <br/>DOI 10.1007/s10919-008-0059-5 <br/>O R I G I N A L P A P E R @@ -14706,6 +18811,28 @@ <br/>framework. Finally, they analyze the shapes of full facial surfaces. <br/>1249 </td><td>('3282147', 'Xue-Qiao Wang', 'xue-qiao wang')<br/>('2130097', 'Jia-Zheng Yuan', 'jia-zheng yuan')<br/>('1930238', 'Qing Li', 'qing li')</td><td>E-mail: {ldxueqiao; jiazheng; liqing10}@buu.edu.cn +</td></tr><tr><td>166186e551b75c9b5adcc9218f0727b73f5de899</td><td>Volume 4, Issue 2, February 2016 +<br/>International Journal of Advance Research in +<br/>Computer Science and Management Studies +<br/>Research Article / Survey Paper / Case Study +<br/>Available online at: www.ijarcsms.com +<br/>ISSN: 2321-7782 (Online) +<br/>Automatic Age and Gender Recognition in Human Face Image +<br/>Dataset using Convolutional Neural Network System +<br/>Subhani Shaik1 +<br/>Assoc. Prof & Head of the Department +<br/>Department of CSE, +<br/>Associate Professor +<br/>Department of CSE, +<br/>St.Mary’s Group of Institutions Guntur +<br/>St.Mary’s Group of Institutions Guntur +<br/>Chebrolu(V&M),Guntur(Dt), +<br/>Andhra Pradesh - India +<br/>Chebrolu(V&M),Guntur(Dt), +<br/>Andhra Pradesh - India +</td><td>('39885231', 'Anto A. Micheal', 'anto a. micheal')</td><td></td></tr><tr><td>16d6737b50f969247339a6860da2109a8664198a</td><td>Convolutional Neural Networks +<br/>for Age and Gender Classification +<br/><b>Stanford University</b></td><td>('22241470', 'Ari Ekmekji', 'ari ekmekji')</td><td>aekmekji@stanford.edu </td></tr><tr><td>16d9b983796ffcd151bdb8e75fc7eb2e31230809</td><td>EUROGRAPHICS 2018 / D. Gutierrez and A. Sheffer <br/>(Guest Editors) <br/>Volume 37 (2018), Number 2 @@ -14807,7 +18934,11 @@ <br/>Department of Computer Science and Engineering <br/><b>Waseda University, Tokyo, Japan</b></td><td>('3114470', 'Edgar Simo-Serra', 'edgar simo-serra')<br/>('1692113', 'Hiroshi Ishikawa', 'hiroshi ishikawa')</td><td>esimo@aoni.waseda.jp <br/>hfs@waseda.jp -</td></tr><tr><td>42e3dac0df30d754c7c7dab9e1bb94990034a90d</td><td>PANDA: Pose Aligned Networks for Deep Attribute Modeling +</td></tr><tr><td>4209783b0cab1f22341f0600eed4512155b1dee6</td><td>Accurate and Efficient Similarity Search for Large Scale Face Recognition +<br/>BUPT +<br/>BUPT +<br/>BUPT +</td><td>('49712251', 'Ce Qi', 'ce qi')<br/>('35963823', 'Zhizhong Liu', 'zhizhong liu')<br/>('1684263', 'Fei Su', 'fei su')</td><td></td></tr><tr><td>42e3dac0df30d754c7c7dab9e1bb94990034a90d</td><td>PANDA: Pose Aligned Networks for Deep Attribute Modeling <br/>2EECS, UC Berkeley <br/>1Facebook AI Research </td><td>('40565777', 'Ning Zhang', 'ning zhang')<br/>('2210374', 'Manohar Paluri', 'manohar paluri')<br/>('1753210', 'Trevor Darrell', 'trevor darrell')</td><td>{mano, ranzato, lubomir}@fb.com @@ -14870,7 +19001,10 @@ <br/>Modeling for Face Reconstruction <br/><b>School of Computer Science, Tianjin University</b><br/><b>School of Computer Science, Tianjin University</b><br/><b>School of Software, Tianjin University</b></td><td>('1919846', 'Weilong Peng', 'weilong peng')<br/>('1683334', 'Zhiyong Feng', 'zhiyong feng')<br/>('29962190', 'Chao Xu', 'chao xu')</td><td>wlpeng@tju.edu.cn <br/>zyfeng@tju.edu.cn -</td></tr><tr><td>42c9394ca1caaa36f535721fa9a64b2c8d4e0dee</td><td>Label Efficient Learning of Transferable +</td></tr><tr><td>42eda7c20db9dc0f42f72bb997dd191ed8499b10</td><td>Gaze Embeddings for Zero-Shot Image Classification +<br/><b>Max Planck Institute for Informatics</b><br/>Saarland Informatics Campus +<br/>2Amsterdam Machine Learning Lab +<br/><b>University of Amsterdam</b></td><td>('7789181', 'Nour Karessli', 'nour karessli')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td></td></tr><tr><td>42c9394ca1caaa36f535721fa9a64b2c8d4e0dee</td><td>Label Efficient Learning of Transferable <br/>Representations across Domains and Tasks <br/><b>Stanford University</b><br/>Virginia Tech <br/><b>University of California, Berkeley</b></td><td>('3378742', 'Zelun Luo', 'zelun luo')<br/>('8299168', 'Yuliang Zou', 'yuliang zou')<br/>('4742485', 'Judy Hoffman', 'judy hoffman')</td><td>zelunluo@stanford.edu @@ -14887,7 +19021,8 @@ <br/>Computer Science and Artificial Intelligence Laboratory <br/><b>Massachusetts Institute of Technology</b><br/>Cambridge, Massachusetts 02139, USA </td><td>('2852664', 'Dominic Kao', 'dominic kao')<br/>('1709421', 'D. Fox Harrell', 'd. fox harrell')</td><td>{dkao,fox.harrell}@mit.edu -</td></tr><tr><td>42f6f5454dda99d8989f9814989efd50fe807ee8</td><td>Conditional generative adversarial nets for convolutional face generation +</td></tr><tr><td>42ea8a96eea023361721f0ea34264d3d0fc49ebd</td><td>Parameterized Principal Component Analysis +<br/><b>Florida State University, USA</b></td><td>('2109527', 'Ajay Gupta', 'ajay gupta')<br/>('2455529', 'Adrian Barbu', 'adrian barbu')</td><td></td></tr><tr><td>42f6f5454dda99d8989f9814989efd50fe807ee8</td><td>Conditional generative adversarial nets for convolutional face generation <br/>Symbolic Systems Program, Natural Language Processing Group <br/><b>Stanford University</b></td><td>('24339276', 'Jon Gauthier', 'jon gauthier')</td><td>jgauthie@stanford.edu </td></tr><tr><td>429d4848d03d2243cc6a1b03695406a6de1a7abd</td><td>Face Recognition based on Logarithmic Fusion @@ -15054,28 +19189,70 @@ <br/>1Eimad E.A. Abusham, 1Andrew T.B. Jin, 1Wong E. Kiong and 2G. Debashis <br/>1Faculty of Information Science and Technology, <br/><b>Faculty of Engineering and Technology, Multimedia University (Melaka Campus</b><br/>Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia -</td><td></td><td></td></tr><tr><td>89e7d23e0c6a1d636f2da68aaef58efee36b718b</td><td>Lucas-Kanade Scale Invariant Feature Transform for +</td><td></td><td></td></tr><tr><td>89c73b1e7c9b5e126a26ed5b7caccd7cd30ab199</td><td>Application of an Improved Mean Shift Algorithm +<br/>in Real-time Facial Expression Recognition +<br/><b>School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008 china</b><br/><b>School of Electrical and Information Engineering, Hunan University of Technology, Hunan, Zhuzhou, 412008 china</b><br/><b>School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008 china</b><br/>Yan-hui ZHU +<br/><b>School of Computer and Communication, Hunan University of Technology, Hunan, Zhuzhou, 412008 china</b><br/>facial +<br/>real-time +<br/>expression +</td><td>('1719090', 'Zhao-yi Peng', 'zhao-yi peng')<br/>('1696179', 'Yu Zhou', 'yu zhou')<br/>('2276926', 'Zhi-qiang Wen', 'zhi-qiang wen')</td><td>Email:pengzhaoyi@163.com +<br/>Email:zypzy@163.com +<br/>Email: swayhzhu@163.com +<br/>Email: zhqwen20001@163.com +</td></tr><tr><td>89e7d23e0c6a1d636f2da68aaef58efee36b718b</td><td>Lucas-Kanade Scale Invariant Feature Transform for <br/>Uncontrolled Viewpoint Face Recognition <br/>1Division of Computer Science and Engineering, <br/>2Center for Advanced Image and Information Technology -<br/><b>Chonbuk National University, Jeonju 561-756, Korea</b></td><td>('2642847', 'Yongbin Gao', 'yongbin gao')<br/>('4292934', 'Hyo Jong Lee', 'hyo jong lee')</td><td></td></tr><tr><td>89f4bcbfeb29966ab969682eae235066a89fc151</td><td>A Comparison of Photometric Normalisation Algorithms for Face Verification +<br/><b>Chonbuk National University, Jeonju 561-756, Korea</b></td><td>('2642847', 'Yongbin Gao', 'yongbin gao')<br/>('4292934', 'Hyo Jong Lee', 'hyo jong lee')</td><td></td></tr><tr><td>893239f17dc2d17183410d8a98b0440d98fa2679</td><td>UvA-DARE (Digital Academic Repository) +<br/>Expression-Invariant Age Estimation +<br/>Published in: +<br/>Proceedings of the British Machine Vision Conference 2014 +<br/>DOI: +<br/>10.5244/C.28.14 +<br/>Link to publication +<br/>Citation for published version (APA): +<br/>French, & T. Pridmore (Eds.), Proceedings of the British Machine Vision Conference 2014 (pp. 14.1-14.11). +<br/>BMVA Press. DOI: 10.5244/C.28.14 +<br/>General rights +<br/>It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), +<br/>other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). +<br/>Disclaimer/Complaints regulations +<br/>If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating +<br/>your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask +<br/><b>the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam</b><br/>The Netherlands. You will be contacted as soon as possible. +<br/>Download date: 04 Aug 2017 +<br/><b>UvA-DARE is a service provided by the library of the University of Amsterdam (http://dare.uva.nl</b></td><td>('49776777', 'Alvarez Lopez', 'alvarez lopez')</td><td></td></tr><tr><td>89f4bcbfeb29966ab969682eae235066a89fc151</td><td>A Comparison of Photometric Normalisation Algorithms for Face Verification <br/>Centre for Vision, Speech and Signal Processing <br/><b>University of Surrey</b><br/>Guildford, Surrey, GU2 7XH, UK </td><td>('39213687', 'James Short', 'james short')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('2173900', 'Kieron Messer', 'kieron messer')</td><td>(cid:0)j.short,j.kittler,k.messer(cid:1)@eim.surrey.ac.uk +</td></tr><tr><td>892c911ca68f5b4bad59cde7eeb6c738ec6c4586</td><td>RESEARCH ARTICLE +<br/>The Ryerson Audio-Visual Database of +<br/>Emotional Speech and Song (RAVDESS): A +<br/>dynamic, multimodal set of facial and vocal +<br/>expressions in North American English +<br/><b>Ryerson University, Toronto, Canada</b><br/><b>Information Systems, University of Wisconsin-River Falls, Wisconsin, WI, United States of America</b></td><td>('2940438', 'Frank A. Russo', 'frank a. russo')</td><td>* steven.livingstone@uwrf.edu </td></tr><tr><td>8913a5b7ed91c5f6dec95349fbc6919deee4fc75</td><td>BigBIRD: A Large-Scale 3D Database of Object Instances -</td><td>('37248999', 'Arjun Singh', 'arjun singh')<br/>('1905626', 'James Sha', 'james sha')<br/>('39537097', 'Karthik S. Narayan', 'karthik s. narayan')<br/>('2461427', 'Tudor Achim', 'tudor achim')<br/>('1689992', 'Pieter Abbeel', 'pieter abbeel')</td><td></td></tr><tr><td>89cabb60aa369486a1ebe586dbe09e3557615ef8</td><td>Bayesian Networks as Generative +</td><td>('37248999', 'Arjun Singh', 'arjun singh')<br/>('1905626', 'James Sha', 'james sha')<br/>('39537097', 'Karthik S. Narayan', 'karthik s. narayan')<br/>('2461427', 'Tudor Achim', 'tudor achim')<br/>('1689992', 'Pieter Abbeel', 'pieter abbeel')</td><td></td></tr><tr><td>8986585975c0090e9ad97bec2ba6c4b437419dae</td><td>Unsupervised Hard Example Mining from +<br/>Videos for Improved Object Detection +<br/><b>College of Information and Computer Sciences, University of Massachusetts, Amherst</b><br/>{souyoungjin,arunirc,hzjiang,ashishsingh, +</td><td>('24525313', 'SouYoung Jin', 'souyoung jin')<br/>('2895705', 'Aruni RoyChowdhury', 'aruni roychowdhury')<br/>('40175280', 'Huaizu Jiang', 'huaizu jiang')<br/>('1785936', 'Ashish Singh', 'ashish singh')<br/>('39087749', 'Aditya Prasad', 'aditya prasad')<br/>('32315404', 'Deep Chakraborty', 'deep chakraborty')</td><td>aprasad,dchakraborty,elm}@cs.umass.edu +</td></tr><tr><td>89cabb60aa369486a1ebe586dbe09e3557615ef8</td><td>Bayesian Networks as Generative <br/>Models for Face Recognition <br/><b>IDIAP RESEARCH INSTITUTE</b><br/>´ECOLE POLYTECHNIQUE F´ED´ERALE DE LAUSANNE <br/>supervised by: <br/>Dr. S. Marcel <br/>Prof. H. Bourlard <br/>2009 -</td><td>('16602458', 'Guillaume Heusch', 'guillaume heusch')</td><td></td></tr><tr><td>8983485996d5d9d162e70d66399047c5d01ac451</td><td>Deep Feature-based Face Detection on Mobile Devices +</td><td>('16602458', 'Guillaume Heusch', 'guillaume heusch')</td><td></td></tr><tr><td>89d3a57f663976a9ac5e9cdad01267c1fc1a7e06</td><td>Neural Class-Specific Regression for face +<br/>verification +</td><td>('38813382', 'Guanqun Cao', 'guanqun cao')<br/>('9219875', 'Moncef Gabbouj', 'moncef gabbouj')</td><td></td></tr><tr><td>8983485996d5d9d162e70d66399047c5d01ac451</td><td>Deep Feature-based Face Detection on Mobile Devices <br/><b>Center for Automation Research, University of Maryland, College Park, MD</b><br/><b>Rutgers University, Piscataway, NJ</b></td><td>('40599829', 'Sayantan Sarkar', 'sayantan sarkar')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{ssarkar2, rama}@umiacs.umd.edu <br/>vishal.m.patel@rutgers.edu </td></tr><tr><td>89bc311df99ad0127383a9149d1684dfd8a5aa34</td><td>Towards ontology driven learning of <br/>visual concept detectors -<br/><b>Dextro Robotics, Inc. 101 Avenue of the Americas, New York, USA</b></td><td>('3407640', 'Sanchit Arora', 'sanchit arora')<br/>('21781318', 'Chuck Cho', 'chuck cho')<br/>('1810102', 'Paul Fitzpatrick', 'paul fitzpatrick')</td><td></td></tr><tr><td>898a66979c7e8b53a10fd58ac51fbfdb6e6e6e7c</td><td>Dynamic vs. Static Recognition of Facial +<br/><b>Dextro Robotics, Inc. 101 Avenue of the Americas, New York, USA</b></td><td>('3407640', 'Sanchit Arora', 'sanchit arora')<br/>('21781318', 'Chuck Cho', 'chuck cho')<br/>('1810102', 'Paul Fitzpatrick', 'paul fitzpatrick')</td><td></td></tr><tr><td>8981be3a69cd522b4e57e9914bf19f034d4b530c</td><td>Fast Automatic Video Retrieval using Web Images +<br/><b>Center For Automation Research, University of Maryland, College Park</b></td><td>('2257769', 'Xintong Han', 'xintong han')<br/>('47679939', 'Bharat Singh', 'bharat singh')<br/>('2852035', 'Vlad I. Morariu', 'vlad i. morariu')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td>{xintong,bharat,morariu,lsd}@umiacs.umd.edu +</td></tr><tr><td>898a66979c7e8b53a10fd58ac51fbfdb6e6e6e7c</td><td>Dynamic vs. Static Recognition of Facial <br/>Expressions <br/>No Author Given <br/><b>No Institute Given</b></td><td></td><td></td></tr><tr><td>89d7cc9bbcd2fdc4f4434d153ecb83764242227b</td><td>(IJERA) ISSN: 2248-9622 www.ijera.com @@ -15085,7 +19262,16 @@ <br/><b>VelTech HighTech Dr. Rangarajan Dr.Sakunthala Engineering College</b><br/><b>Final Year Student, M.Tech IT, Vel Tech Dr. RR andDr. SR Technical University, Chennai</b><br/>Chennai.) </td><td></td><td></td></tr><tr><td>896f4d87257abd0f628c1ffbbfdac38c86a56f50</td><td>Action and Gesture Temporal Spotting with <br/>Super Vector Representation -<br/><b>Southwest Jiaotong University, Chengdu, China</b><br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Key Lab of CVPR, Shenzhen Institutes of Advanced Technology, CAS</b></td><td>('1766837', 'Xiaojiang Peng', 'xiaojiang peng')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('2985266', 'Zhuowei Cai', 'zhuowei cai')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>45c340c8e79077a5340387cfff8ed7615efa20fd</td><td></td><td></td><td></td></tr><tr><td>455204fa201e9936b42756d362f62700597874c4</td><td>A REGION BASED METHODOLOGY FOR FACIAL +<br/><b>Southwest Jiaotong University, Chengdu, China</b><br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Key Lab of CVPR, Shenzhen Institutes of Advanced Technology, CAS</b></td><td>('1766837', 'Xiaojiang Peng', 'xiaojiang peng')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('2985266', 'Zhuowei Cai', 'zhuowei cai')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>891b10c4b3b92ca30c9b93170ec9abd71f6099c4</td><td>Facial landmark detection using structured output deep +<br/>neural networks +<br/>Soufiane Belharbi ∗1, Cl´ement Chatelain∗1, Romain H´erault∗1, and S´ebastien +<br/>1LITIS EA 4108, INSA de Rouen, Saint ´Etienne du Rouvray 76800, France +<br/>2LITIS EA 4108, UFR des Sciences, Universit´e de Rouen, France. +<br/>September 24, 2015 +</td><td>('49529671', 'Adam', 'adam')</td><td></td></tr><tr><td>451b6409565a5ad18ea49b063561a2645fa4281b</td><td>Action Sets: Weakly Supervised Action Segmentation without Ordering +<br/>Constraints +<br/><b>University of Bonn, Germany</b></td><td>('32774629', 'Alexander Richard', 'alexander richard')<br/>('51267303', 'Hilde Kuehne', 'hilde kuehne')<br/>('2946643', 'Juergen Gall', 'juergen gall')</td><td>{richard,kuehne,gall}@iai.uni-bonn.de +</td></tr><tr><td>45c340c8e79077a5340387cfff8ed7615efa20fd</td><td></td><td></td><td></td></tr><tr><td>455204fa201e9936b42756d362f62700597874c4</td><td>A REGION BASED METHODOLOGY FOR FACIAL <br/>EXPRESSION RECOGNITION <br/><b>Medical School, University of Ioannina, Ioannina, Greece</b><br/>Unit of Medical Technology and Intelligent Information Systems, Dept. of Computer Science <br/><b>University of Ioannina, Ioannina, Greece</b><br/>Keywords: @@ -15124,13 +19310,19 @@ <br/># 2006 Psychology Press, an imprint of the Taylor & Francis Group, an informa business <br/>DOI: 10.1080/13576500600832758 </td><td>('1689241', 'Yanxi Liu', 'yanxi liu')</td><td>Pittsburgh, 121 University Place, Pittsburgh PA 15217, USA. E-mail: kschmidt@pitt.edu -</td></tr><tr><td>459960be65dd04317dd325af5b7cbb883d822ee4</td><td>The Meme Quiz: A Facial Expression Game Combining +</td></tr><tr><td>4552f4d46a2cc67ccc4dd8568e5c95aa2eedb4ec</td><td>Disentangling Features in 3D Face Shapes +<br/>for Joint Face Reconstruction and Recognition∗ +<br/><b>College of Computer Science, Sichuan University</b><br/><b>Michigan State University</b></td><td>('1734409', 'Feng Liu', 'feng liu')<br/>('1778454', 'Ronghang Zhu', 'ronghang zhu')<br/>('39422721', 'Dan Zeng', 'dan zeng')<br/>('7345195', 'Qijun Zhao', 'qijun zhao')<br/>('38284381', 'Xiaoming Liu', 'xiaoming liu')</td><td></td></tr><tr><td>459960be65dd04317dd325af5b7cbb883d822ee4</td><td>The Meme Quiz: A Facial Expression Game Combining <br/>Human Agency and Machine Involvement <br/>Department of Computer Science and Engineering <br/><b>University of Washington</b></td><td>('3059933', 'Kathleen Tuite', 'kathleen tuite')</td><td>{ktuite,kemelmi}@cs.washington.edu </td></tr><tr><td>45f858f9e8d7713f60f52618e54089ba68dfcd6d</td><td>What Actions are Needed for Understanding Human Actions in Videos? <br/><b>Carnegie Mellon University</b><br/>github.com/gsig/actions-for-actions -</td><td>('34280810', 'Gunnar A. Sigurdsson', 'gunnar a. sigurdsson')</td><td></td></tr><tr><td>45215e330a4251801877070c85c81f42c2da60fb</td><td>Domain Adaptive Dictionary Learning +</td><td>('34280810', 'Gunnar A. Sigurdsson', 'gunnar a. sigurdsson')</td><td></td></tr><tr><td>45e7ddd5248977ba8ec61be111db912a4387d62f</td><td>CHEN ET AL.: ADVERSARIAL POSENET +<br/>Adversarial Learning of Structure-Aware Fully +<br/>Convolutional Networks for Landmark +<br/>Localization +</td><td>('50579509', 'Yu Chen', 'yu chen')<br/>('1780381', 'Chunhua Shen', 'chunhua shen')<br/>('2126047', 'Xiu-Shen Wei', 'xiu-shen wei')<br/>('2161037', 'Lingqiao Liu', 'lingqiao liu')<br/>('49499405', 'Jian Yang', 'jian yang')</td><td></td></tr><tr><td>45215e330a4251801877070c85c81f42c2da60fb</td><td>Domain Adaptive Dictionary Learning <br/><b>Center for Automation Research, UMIACS, University of Maryland, College Park</b><br/><b>Arts Media and Engineering, Arizona State University</b></td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>qiu@cs.umd.edu, {pvishalm, rama}@umiacs.umd.edu, pturaga@asu.edu </td></tr><tr><td>457cf73263d80a1a1338dc750ce9a50313745d1d</td><td>Published as a conference paper at ICLR 2017 <br/>DECOMPOSING MOTION AND CONTENT FOR @@ -15150,7 +19342,12 @@ <br/>{zlei,szli}@nlpr.ia.ac.cn </td></tr><tr><td>45efd6c2dd4ca19eed38ceeb7c2c5568231451e1</td><td>Comparative Analysis of Statistical Approach <br/>for Face Recognition -<br/><b>CMR Institute of Technology, Hyderabad, (India</b></td><td>('39463904', 'M.Janga Reddy', 'm.janga reddy')</td><td></td></tr><tr><td>45f3bf505f1ce9cc600c867b1fb2aa5edd5feed8</td><td></td><td></td><td></td></tr><tr><td>4571626d4d71c0d11928eb99a3c8b10955a74afe</td><td>Geometry Guided Adversarial Facial Expression Synthesis +<br/><b>CMR Institute of Technology, Hyderabad, (India</b></td><td>('39463904', 'M.Janga Reddy', 'm.janga reddy')</td><td></td></tr><tr><td>45f3bf505f1ce9cc600c867b1fb2aa5edd5feed8</td><td></td><td></td><td></td></tr><tr><td>4560491820e0ee49736aea9b81d57c3939a69e12</td><td>Investigating the Impact of Data Volume and +<br/>Domain Similarity on Transfer Learning +<br/>Applications +<br/>State Farm Insurance, Bloomington IL 61710, USA, +</td><td>('30492517', 'Michael Bernico', 'michael bernico')<br/>('50024782', 'Yuntao Li', 'yuntao li')<br/>('41092475', 'Dingchao Zhang', 'dingchao zhang')</td><td>michael.bernico.qepz@statefarm.com +</td></tr><tr><td>4571626d4d71c0d11928eb99a3c8b10955a74afe</td><td>Geometry Guided Adversarial Facial Expression Synthesis <br/>1National Laboratory of Pattern Recognition, CASIA <br/>2Center for Research on Intelligent Perception and Computing, CASIA <br/>3Center for Excellence in Brain Science and Intelligence Technology, CAS @@ -15195,15 +19392,43 @@ <br/>https://webspace.utexas.edu/yl3663/~ylee/ <br/>http://www.cs.utexas.edu/~grauman/ <br/><b>University of Texas at Austin</b><br/>Austin, TX, USA -</td><td>('1883898', 'Yong Jae Lee', 'yong jae lee')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td></td></tr><tr><td>458677de7910a5455283a2be99f776a834449f61</td><td>Face Image Retrieval Using Facial Attributes By +</td><td>('1883898', 'Yong Jae Lee', 'yong jae lee')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td></td></tr><tr><td>45e459462a80af03e1bb51a178648c10c4250925</td><td>LCrowdV: Generating Labeled Videos for +<br/>Simulation-based Crowd Behavior Learning +<br/><b>The University of North Carolina at Chapel Hill</b></td><td>('3422427', 'Ernest Cheung', 'ernest cheung')<br/>('3422442', 'Tsan Kwong Wong', 'tsan kwong wong')<br/>('2718563', 'Aniket Bera', 'aniket bera')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1699159', 'Dinesh Manocha', 'dinesh manocha')</td><td></td></tr><tr><td>458677de7910a5455283a2be99f776a834449f61</td><td>Face Image Retrieval Using Facial Attributes By <br/>K-Means <br/>[1]I.Sudha, [2]V.Saradha, [3]M.Tamilselvi, [4]D.Vennila <br/>[1]AP, Department of CSE ,[2][3][4] B.Tech(CSE) <br/><b>Achariya college of Engineering Technology</b><br/>Puducherry -</td><td></td><td></td></tr><tr><td>1f9b2f70c24a567207752989c5bd4907442a9d0f</td><td>Deep Representations to Model User ‘Likes’ +</td><td></td><td></td></tr><tr><td>45a6333fc701d14aab19f9e2efd59fe7b0e89fec</td><td>HAND POSTURE DATASET CREATION FOR GESTURE +<br/>RECOGNITION +<br/>Luis Anton-Canalis +<br/>Instituto de Sistemas Inteligentes y Aplicaciones Numericas en Ingenieria +<br/>Campus Universitario de Tafira, 35017 Gran Canaria, Spain +<br/>Elena Sanchez-Nielsen +<br/>Departamento de E.I.O. y Computacion +<br/>38271 Universidad de La Laguna, Spain +<br/>Keywords: +<br/>Image understanding, Gesture recognition, Hand dataset. +</td><td></td><td></td></tr><tr><td>450c6a57f19f5aa45626bb08d7d5d6acdb863b4b</td><td>Towards Interpretable Face Recognition +<br/><b>Michigan State University</b><br/>2 Adobe Inc. +<br/>3 Aibee +</td><td>('32032812', 'Bangjie Yin', 'bangjie yin')<br/>('1849929', 'Luan Tran', 'luan tran')<br/>('3131569', 'Haoxiang Li', 'haoxiang li')<br/>('1720987', 'Xiaohui Shen', 'xiaohui shen')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>{yinbangj, tranluan, liuxm}@msu.edu, xshen@adobe.com, lhxustcer@gmail.com +</td></tr><tr><td>1f9b2f70c24a567207752989c5bd4907442a9d0f</td><td>Deep Representations to Model User ‘Likes’ <br/><b>School of Computer Engineering, Nanyang Technological University, Singapore</b><br/><b>Institute for Infocomm Research, Singapore</b><br/><b>QCIS, University of Technology, Sydney</b></td><td>('2731733', 'Sharath Chandra Guntuku', 'sharath chandra guntuku')<br/>('10638646', 'Joey Tianyi Zhou', 'joey tianyi zhou')<br/>('1872875', 'Sujoy Roy', 'sujoy roy')<br/>('1807998', 'Ivor W. Tsang', 'ivor w. tsang')</td><td>sharathc001@e.ntu.edu.sg, tzhou1@ntu.edu.sg, wslin@ntu.edu.sg <br/>sujoy@i2r.a-star.edu.sg <br/>ivor.tsang@uts.edu.au +</td></tr><tr><td>1fe1bd6b760e3059fff73d53a57ce3a6079adea1</td><td>SINGH ET AL.: SCALING BAG-OF-VISUAL-WORDS GENERATION +<br/>Fast-BoW: Scaling Bag-of-Visual-Words +<br/>Generation +<br/>Visual Learning & Intelligence Group +<br/>Department of Computer Science and +<br/>Engineering +<br/><b>Indian Institute of Technology</b><br/>Hyderabad +<br/>Kandi, Sangareddy, Telangana, India +</td><td>('40624178', 'Dinesh Singh', 'dinesh singh')<br/>('51292354', 'Abhijeet Bhure', 'abhijeet bhure')<br/>('51305895', 'Sumit Mamtani', 'sumit mamtani')<br/>('34358756', 'C. Krishna Mohan', 'c. krishna mohan')</td><td>cs14resch11003@iith.ac.in +<br/>cs15btech11001@iith.ac.in +<br/>cs15btech11022@iith.ac.in +<br/>ckm@iith.ac.in </td></tr><tr><td>1f05473c587e2a3b587f51eb808695a1c10bc153</td><td>Towards Good Practices for Very Deep Two-Stream ConvNets <br/><b>The Chinese University of Hong Kong, Hong Kong</b><br/><b>Shenzhen key lab of Comp. Vis. and Pat. Rec., Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('1915826', 'Zhe Wang', 'zhe wang')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td>{07wanglimin,bitxiong,buptwangzhe2012}@gmail.com, yu.qiao@siat.ac.cn </td></tr><tr><td>1fa3948af1c338f9ae200038c45adadd2b39a3e4</td><td>Computational Explorations of Split Architecture in Modeling Face and Object @@ -15213,7 +19438,9 @@ </td><td></td><td>Janet Hui-wen Hsiao (jhsiao@cs.ucsd.edu) <br/>Garrison W. Cottrell (gary@ucsd.edu) <br/>Danke Shieh (danke@ucsd.edu) -</td></tr><tr><td>1f8304f4b51033d2671147b33bb4e51b9a1e16fe</td><td>Noname manuscript No. +</td></tr><tr><td>1ffe20eb32dbc4fa85ac7844178937bba97f4bf0</td><td>Face Clustering: Representation and Pairwise +<br/>Constraints +</td><td>('9644181', 'Yichun Shi', 'yichun shi')<br/>('40653304', 'Charles Otto', 'charles otto')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>1f8304f4b51033d2671147b33bb4e51b9a1e16fe</td><td>Noname manuscript No. <br/>(will be inserted by the editor) <br/>Beyond Trees: <br/>MAP Inference in MRFs via Outer-Planar Decomposition @@ -15271,7 +19498,9 @@ </td></tr><tr><td>1fefb2f8dd1efcdb57d5c2966d81f9ab22c1c58d</td><td>vExplorer: A Search Method to Find Relevant YouTube Videos for Health <br/>Researchers <br/>IBM Research, Cambridge, MA, USA -</td><td>('1764750', 'Hillol Sarker', 'hillol sarker')<br/>('3456866', 'Murtaza Dhuliawala', 'murtaza dhuliawala')<br/>('31633051', 'Nicholas Fay', 'nicholas fay')<br/>('15793829', 'Amar Das', 'amar das')</td><td></td></tr><tr><td>1f8e44593eb335c2253d0f22f7f9dc1025af8c0d</td><td>Fine-tuning regression forests votes for object alignment in the wild. +</td><td>('1764750', 'Hillol Sarker', 'hillol sarker')<br/>('3456866', 'Murtaza Dhuliawala', 'murtaza dhuliawala')<br/>('31633051', 'Nicholas Fay', 'nicholas fay')<br/>('15793829', 'Amar Das', 'amar das')</td><td></td></tr><tr><td>1fdeba9c4064b449231eac95e610f3288801fd3e</td><td>Fine-Grained Head Pose Estimation Without Keypoints +<br/><b>Georgia Institute of Technology</b></td><td>('31601235', 'Nataniel Ruiz', 'nataniel ruiz')<br/>('39832600', 'Eunji Chong', 'eunji chong')<br/>('1692956', 'James M. Rehg', 'james m. rehg')</td><td>{nataniel.ruiz, eunjichong, rehg}@gatech.edu +</td></tr><tr><td>1f8e44593eb335c2253d0f22f7f9dc1025af8c0d</td><td>Fine-tuning regression forests votes for object alignment in the wild. <br/>Yang, H; Patras, I <br/>© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be <br/><b>obtained for all other uses, in any current or future media, including reprinting/republishing</b><br/>this material for advertising or promotional purposes, creating new collective works, for resale @@ -15304,6 +19533,8 @@ </td><td>('38996894', 'Marie-Lena Eckert', 'marie-lena eckert')<br/>('1862703', 'Neslihan Kose', 'neslihan kose')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td>1 marie-lena.eckert@mytum.de <br/>2 kose@eurecom.fr <br/>3 jld@eurecom.fr +</td></tr><tr><td>1fff309330f85146134e49e0022ac61ac60506a9</td><td>Data-Driven Sparse Sensor Placement for Reconstruction +</td><td>('37119658', 'Krithika Manohar', 'krithika manohar')<br/>('1824880', 'Bingni W. Brunton', 'bingni w. brunton')<br/>('1937069', 'J. Nathan Kutz', 'j. nathan kutz')<br/>('3083169', 'Steven L. Brunton', 'steven l. brunton')</td><td>∗Corresponding author: kmanohar@uw.edu </td></tr><tr><td>1fd3dbb6e910708fa85c8a86e17ba0b6fef5617c</td><td><b>ARISTOTLE UNIVERSITY OF THESSALONIKI</b><br/>FACULTY OF SCIENCES <br/>DEPARTMENT OF INFORMATICS <br/>POSTGRADUATE STUDIES PROGRAMME @@ -15357,15 +19588,45 @@ <br/>Communicated by Chung-Lin Huang. <br/>1711 </td><td>('2078993', 'Xiaochao Zhao', 'xiaochao zhao')<br/>('2138422', 'Yaping Lin', 'yaping lin')<br/>('2431083', 'Bo Ou', 'bo ou')<br/>('1824216', 'Junfeng Yang', 'junfeng yang')</td><td>E-mail: {s12103017; yplin; oubo; B12100031}@hnu.edu.cn -</td></tr><tr><td>73f467b4358ac1cafb57f58e902c1cab5b15c590</td><td> ISSN 0976 3724 47 +</td></tr><tr><td>1feeab271621128fe864e4c64bab9b2e2d0ed1f1</td><td>Article +<br/>Perception-Link Behavior Model: Supporting +<br/>a Novel Operator Interface for a Customizable +<br/>Anthropomorphic Telepresence Robot +<br/><b>BeingTogether Centre, Institute for Media Innovation, Singapore 637553, Singapore</b><br/><b>Robotic Research Centre, Nanyang Technological University, Singapore 639798, Singapore</b><br/>Received: 15 May 2017; Accepted: 15 July 2017; Published: 20 July 2017 +</td><td>('1768723', 'William Gu', 'william gu')<br/>('9216152', 'Gerald Seet', 'gerald seet')<br/>('1695679', 'Nadia Magnenat-Thalmann', 'nadia magnenat-thalmann')</td><td>mglseet@ntu.edu.sg (G.S.); NADIATHALMANN@ntu.edu.sg (N.M.-T.) +<br/>* Correspondence: GUYU0007@e.ntu.edu.sg +</td></tr><tr><td>73b90573d272887a6d835ace89bfaf717747c59b</td><td>Feature Disentangling Machine - A Novel +<br/>Approach of Feature Selection and Disentangling +<br/>in Facial Expression Analysis +<br/><b>University of South Carolina, USA</b><br/><b>Center for Computational Intelligence, Nanyang Technology University, Singapore</b><br/>3 Center for Quantum Computation and Intelligent Systems, +<br/><b>University of Technology, Australia</b></td><td>('40205868', 'Ping Liu', 'ping liu')<br/>('10638646', 'Joey Tianyi Zhou', 'joey tianyi zhou')<br/>('3091647', 'Zibo Meng', 'zibo meng')<br/>('49107074', 'Shizhong Han', 'shizhong han')<br/>('1686235', 'Yan Tong', 'yan tong')</td><td></td></tr><tr><td>73f467b4358ac1cafb57f58e902c1cab5b15c590</td><td> ISSN 0976 3724 47 <br/>Combination of Dimensionality Reduction Techniques for Face <br/>Image Retrieval: A Review <br/><b>M.Tech Scholar, MES College of Engineering, Kuttippuram</b><br/>Kerala <br/><b>MES College of Engineering, Kuttippuram</b><br/>Kerala </td><td></td><td>fousisadath@gmail.com <br/>Jahfar.ali@gmail.com -</td></tr><tr><td>732e8d8f5717f8802426e1b9debc18a8361c1782</td><td>Unimodal Probability Distributions for Deep Ordinal Classification -</td><td>('12757989', 'Christopher Beckham', 'christopher beckham')</td><td></td></tr><tr><td>739d400cb6fb730b894182b29171faaae79e3f01</td><td>A New Regularized Orthogonal Local Fisher Discriminant Analysis for Image +</td></tr><tr><td>7323b594d3a8508f809e276aa2d224c4e7ec5a80</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>An Experimental Evaluation of Covariates +<br/>Effects on Unconstrained Face Verification +</td><td>('2927406', 'Boyu Lu', 'boyu lu')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>732e8d8f5717f8802426e1b9debc18a8361c1782</td><td>Unimodal Probability Distributions for Deep Ordinal Classification +</td><td>('12757989', 'Christopher Beckham', 'christopher beckham')</td><td></td></tr><tr><td>73ed64803d6f2c49f01cffef8e6be8fc9b5273b8</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Cooking in the kitchen: Recognizing and Segmenting Human +<br/>Activities in Videos +<br/>Received: date / Accepted: date +</td><td>('51267303', 'Hilde Kuehne', 'hilde kuehne')</td><td></td></tr><tr><td>7306d42ca158d40436cc5167e651d7ebfa6b89c1</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Transductive Zero-Shot Action Recognition by +<br/>Word-Vector Embedding +<br/>Received: date / Accepted: date +</td><td>('47158489', 'Xun Xu', 'xun xu')</td><td></td></tr><tr><td>734cdda4a4de2a635404e4c6b61f1b2edb3f501d</td><td>Tie and Guan EURASIP Journal on Image and Video Processing 2013, 2013:8 +<br/>http://jivp.eurasipjournals.com/content/2013/1/8 +<br/>R ES EAR CH +<br/>Open Access +<br/>Automatic landmark point detection and tracking +<br/>for human facial expressions +</td><td>('1721867', 'Ling Guan', 'ling guan')</td><td></td></tr><tr><td>739d400cb6fb730b894182b29171faaae79e3f01</td><td>A New Regularized Orthogonal Local Fisher Discriminant Analysis for Image <br/>Feature Extraction <br/>dept. name of organization, name of organization, City, Country <br/><b>School of Management Engineering, Henan Institute of Engineering, Zhengzhou 451191, P.R. China</b><br/><b>Institute of Information Science, Beijing Jiaotong University, Beijing 100044, P.R. China</b></td><td>('2539310', 'ZHONGFENG WANG', 'zhongfeng wang')<br/>('2539310', 'ZHONGFENG WANG', 'zhongfeng wang')<br/>('1718667', 'Zhan WANG', 'zhan wang')</td><td></td></tr><tr><td>732e4016225280b485c557a119ec50cffb8fee98</td><td>Are all training examples equally valuable? @@ -15437,11 +19698,28 @@ </td><td>('1687579', 'Vo Dinh Minh Nhat', 'vo dinh minh nhat')<br/>('1700806', 'Sungyoung Lee', 'sungyoung lee')<br/>('1718666', 'Hee Yong Youn', 'hee yong youn')</td><td>vdmnhat@oslab.khu.ac.kr <br/>sylee@oslab.khu.ac.kr <br/>youn@ece.skku.ac.kr -</td></tr><tr><td>877100f430b72c5d60de199603ab5c65f611ce17</td><td>Within-person variability in men’s facial +</td></tr><tr><td>73c9cbbf3f9cea1bc7dce98fce429bf0616a1a8c</td><td></td><td></td><td></td></tr><tr><td>877100f430b72c5d60de199603ab5c65f611ce17</td><td>Within-person variability in men’s facial <br/>width-to-height ratio <br/><b>University of York, York, United Kingdom</b></td><td>('40598264', 'Robin S.S. Kramer', 'robin s.s. kramer')</td><td></td></tr><tr><td>870433ba89d8cab1656e57ac78f1c26f4998edfb</td><td>Regressing Robust and Discriminative 3D Morphable Models <br/>with a very Deep Neural Network -<br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b></td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')</td><td></td></tr><tr><td>8796f2d54afb0e5c924101f54d469a1d54d5775d</td><td>Journal of Signal and Information Processing, 2012, 3, 45-50 +<br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b></td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')</td><td></td></tr><tr><td>872dfdeccf99bbbed7c8f1ea08afb2d713ebe085</td><td>L2-constrained Softmax Loss for Discriminative Face Verification +<br/><b>Center for Automation Research, UMIACS, University of Maryland, College Park, MD</b></td><td>('48467498', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{rranjan1,carlos,rama}@umiacs.umd.edu +</td></tr><tr><td>87e6cb090aecfc6f03a3b00650a5c5f475dfebe1</td><td>KIM, BALTRUŠAITIS et al.: HOLISTICALLY CONSTRAINED LOCAL MODEL +<br/>Holistically Constrained Local Model: +<br/>Going Beyond Frontal Poses for Facial +<br/>Landmark Detection +<br/>Tadas Baltrušaitis2 +<br/>Amir Zadeh2 +<br/>Gérard Medioni1 +<br/><b>Institute for Robotics and Intelligent</b><br/>Systems +<br/><b>University of Southern California</b><br/>Los Angeles, CA, USA +<br/><b>Language Technologies Institute</b><br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA, USA +</td><td>('2792633', 'KangGeon Kim', 'kanggeon kim')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')</td><td>kanggeon.kim@usc.edu +<br/>tbaltrus@cs.cmu.edu +<br/>abagherz@cs.cmu.edu +<br/>morency@cs.cmu.edu +<br/>medioni@usc.edu +</td></tr><tr><td>8796f2d54afb0e5c924101f54d469a1d54d5775d</td><td>Journal of Signal and Information Processing, 2012, 3, 45-50 <br/>http://dx.doi.org/10.4236/jsip.2012.31007 Published Online February 2012 (http://www.SciRP.org/journal/jsip) <br/>45 <br/>Illumination Invariant Face Recognition Using Fuzzy LDA @@ -15463,12 +19741,26 @@ <br/>2 ESAT - PSI / IBBT, K.U. Leuven, Belgium </td><td>('2173683', 'Rasmus Rothe', 'rasmus rothe')<br/>('2113583', 'Marko Ristin', 'marko ristin')<br/>('1727791', 'Matthias Dantone', 'matthias dantone')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>{rrothe,ristin,mdantone,vangool}@vision.ee.ethz.ch <br/>luc.vangool@esat.kuleuven.be +</td></tr><tr><td>8724fc4d6b91eebb79057a7ce3e9dfffd3b1426f</td><td>Ordered Pooling of Optical Flow Sequences for Action Recognition +<br/>1Data61/CSIRO, 2 Australian Center for Robotic Vision +<br/><b>Australian National University, Canberra, Australia</b><br/>Fatih Porikli1,2,3 +</td><td>('48094509', 'Jue Wang', 'jue wang')<br/>('2691929', 'Anoop Cherian', 'anoop cherian')</td><td>jue.wang@anu.edu.au +<br/>anoop.cherian@anu.edu.au +<br/>fatih.porikli@anu.edu.au </td></tr><tr><td>87bee0e68dfc86b714f0107860d600fffdaf7996</td><td>Automated 3D Face Reconstruction from Multiple Images <br/>using Quality Measures <br/><b>Institute for Vision and Graphics, University of Siegen, Germany</b></td><td>('2712313', 'Marcel Piotraschke', 'marcel piotraschke')<br/>('2880906', 'Volker Blanz', 'volker blanz')</td><td>piotraschke@nt.uni-siegen.de, blanz@informatik.uni-siegen.de </td></tr><tr><td>87309bdb2b9d1fb8916303e3866eca6e3452c27d</td><td>Kernel Coding: General Formulation and Special Cases <br/><b>Australian National University, Canberra, ACT 0200, Australia</b><br/>NICTA(cid:63), Locked Bag 8001, Canberra, ACT 2601, Australia -</td><td>('2862871', 'Mathieu Salzmann', 'mathieu salzmann')</td><td></td></tr><tr><td>87147418f863e3d8ff8c97db0b42695a1c28195b</td><td>Attributes for Improved Attributes: A +</td><td>('2862871', 'Mathieu Salzmann', 'mathieu salzmann')</td><td></td></tr><tr><td>878169be6e2c87df2d8a1266e9e37de63b524ae7</td><td>CBMM Memo No. 089 +<br/>May 10, 2018 +<br/>Image interpretation above and below the object level +</td><td>('2507298', 'Guy Ben-Yosef', 'guy ben-yosef')<br/>('1743045', 'Shimon Ullman', 'shimon ullman')</td><td></td></tr><tr><td>878301453e3d5cb1a1f7828002ea00f59cbeab06</td><td>Faceness-Net: Face Detection through +<br/>Deep Facial Part Responses +</td><td>('1692609', 'Shuo Yang', 'shuo yang')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>87e592ee1a7e2d34e6b115da08700a1ae02e9355</td><td>Deep Pictorial Gaze Estimation +<br/>AIT Lab, Department of Computer Science, ETH Zurich +</td><td>('20466488', 'Seonwook Park', 'seonwook park')<br/>('21195502', 'Adrian Spurr', 'adrian spurr')<br/>('2531379', 'Otmar Hilliges', 'otmar hilliges')</td><td>{firstname.lastname}@inf.ethz.ch +</td></tr><tr><td>87147418f863e3d8ff8c97db0b42695a1c28195b</td><td>Attributes for Improved Attributes: A <br/>Multi-Task Network for Attribute Classification <br/><b>University of Maryland, College Park</b></td><td>('3351637', 'Emily M. Hand', 'emily m. hand')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>87dd3fd36bccbe1d5f1484ac05f1848b51c6eab5</td><td>SPATIO-TEMPORAL MAXIMUM AVERAGE CORRELATION <br/>HEIGHT TEMPLATES IN ACTION RECOGNITION AND VIDEO @@ -15482,7 +19774,7 @@ <br/>2010 <br/>Major Professor: Mubarak Shah </td><td>('35188194', 'MIKEL RODRIGUEZ', 'mikel rodriguez')</td><td></td></tr><tr><td>87bb183d8be0c2b4cfceb9ee158fee4bbf3e19fd</td><td>Craniofacial Image Analysis -</td><td>('1935115', 'Ezgi Mercan', 'ezgi mercan')<br/>('1771661', 'Indriyati Atmosukarto', 'indriyati atmosukarto')<br/>('10423763', 'Jia Wu', 'jia wu')<br/>('1744684', 'Shu Liang', 'shu liang')<br/>('1809809', 'Linda G. Shapiro', 'linda g. shapiro')</td><td></td></tr><tr><td>80193dd633513c2d756c3f568ffa0ebc1bb5213e</td><td></td><td></td><td></td></tr><tr><td>808b685d09912cbef4a009e74e10476304b4cccf</td><td>From Understanding to Controlling Privacy +</td><td>('1935115', 'Ezgi Mercan', 'ezgi mercan')<br/>('1771661', 'Indriyati Atmosukarto', 'indriyati atmosukarto')<br/>('10423763', 'Jia Wu', 'jia wu')<br/>('1744684', 'Shu Liang', 'shu liang')<br/>('1809809', 'Linda G. Shapiro', 'linda g. shapiro')</td><td></td></tr><tr><td>8006219efb6ab76754616b0e8b7778dcfb46603d</td><td>CONTRIBUTIONSTOLARGE-SCALELEARNINGFORIMAGECLASSIFICATIONZeynepAkataPhDThesisl’´EcoleDoctoraleMath´ematiques,SciencesetTechnologiesdel’Information,InformatiquedeGrenoble </td><td></td><td></td></tr><tr><td>80193dd633513c2d756c3f568ffa0ebc1bb5213e</td><td></td><td></td><td></td></tr><tr><td>808b685d09912cbef4a009e74e10476304b4cccf</td><td>From Understanding to Controlling Privacy <br/>against Automatic Person Recognition in Social Media <br/><b>Max Planck Institute for Informatics, Germany</b></td><td>('2390510', 'Seong Joon Oh', 'seong joon oh')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')<br/>('1739548', 'Mario Fritz', 'mario fritz')</td><td>{joon,mfritz,schiele}@mpi-inf.mpg.de </td></tr><tr><td>804b4c1b553d9d7bae70d55bf8767c603c1a09e3</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE @@ -15499,7 +19791,8 @@ <br/>Master of Science <br/>Graduate Program in Computer Engineering <br/><b>Bo gazi ci University</b><br/>2015 -</td><td></td><td></td></tr><tr><td>80277fb3a8a981933533cf478245f262652a33b5</td><td>Synergy-based Learning of Facial Identity +</td><td></td><td></td></tr><tr><td>803c92a3f0815dbf97e30c4ee9450fd005586e1a</td><td>Max-Mahalanobis Linear Discriminant Analysis Networks +</td><td>('19201674', 'Tianyu Pang', 'tianyu pang')</td><td></td></tr><tr><td>80277fb3a8a981933533cf478245f262652a33b5</td><td>Synergy-based Learning of Facial Identity <br/><b>Institute for Computer Graphics and Vision</b><br/><b>Graz University of Technology, Austria</b></td><td>('1791182', 'Peter M. Roth', 'peter m. roth')<br/>('3628150', 'Horst Bischof', 'horst bischof')</td><td>{koestinger,pmroth,bischof}@icg.tugraz.at </td></tr><tr><td>80840df0802399838fe5725cce829e1b417d7a2e</td><td>Fast Approximate L∞ Minimization: Speeding Up Robust Regression <br/><b>School of Computer Science and Technology, Nanjing University of Science and Technology, China</b><br/><b>School of Computer Science, The University of Adelaide, Australia</b></td><td>('2731972', 'Fumin Shen', 'fumin shen')<br/>('1780381', 'Chunhua Shen', 'chunhua shen')<br/>('26065407', 'Rhys Hill', 'rhys hill')<br/>('5546141', 'Anton van den Hengel', 'anton van den hengel')<br/>('3195119', 'Zhenmin Tang', 'zhenmin tang')</td><td></td></tr><tr><td>80c8d143e7f61761f39baec5b6dfb8faeb814be9</td><td>Local Directional Pattern based Fuzzy Co- @@ -15513,7 +19806,11 @@ </td><td>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('3007274', 'Jia Guo', 'jia guo')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td>j.deng16@imperial.ac.uk <br/>guojia@gmail.com <br/>s.zafeiriou@imperial.ac.uk -</td></tr><tr><td>80a6bb337b8fdc17bffb8038f3b1467d01204375</td><td>Proceedings of the International Conference on Computer and Information Science and Technology +</td></tr><tr><td>80345fbb6bb6bcc5ab1a7adcc7979a0262b8a923</td><td>Research Article +<br/>Soft Biometrics for a Socially Assistive Robotic +<br/>Platform +<br/>Open Access +</td><td>('2104853', 'Pierluigi Carcagnì', 'pierluigi carcagnì')<br/>('2417460', 'Dario Cazzato', 'dario cazzato')<br/>('33097940', 'Marco Del Coco', 'marco del coco')<br/>('35438199', 'Pier Luigi Mazzeo', 'pier luigi mazzeo')<br/>('4730472', 'Marco Leo', 'marco leo')<br/>('1741861', 'Cosimo Distante', 'cosimo distante')</td><td></td></tr><tr><td>80a6bb337b8fdc17bffb8038f3b1467d01204375</td><td>Proceedings of the International Conference on Computer and Information Science and Technology <br/>Ottawa, Ontario, Canada, May 11 – 12, 2015 <br/>Paper No. 126 <br/>Subspace LDA Methods for Solving the Small Sample Size @@ -15525,7 +19822,9 @@ <br/>1 Advanced Digital Sciences Center, Singapore <br/><b>Nanyang Technological University, Singapore</b><br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b><br/><b>University of Illinois at Urbana-Champaign, IL USA</b></td><td>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('39209795', 'Gang Wang', 'gang wang')</td><td></td></tr><tr><td>8000c4f278e9af4d087c0d0895fff7012c5e3d78</td><td>Multi-Task Warped Gaussian Process for Personalized Age Estimation <br/><b>Hong Kong University of Science and Technology</b></td><td>('36233573', 'Yu Zhang', 'yu zhang')</td><td>{zhangyu,dyyeung}@cse.ust.hk -</td></tr><tr><td>80bd795930837330e3ced199f5b9b75398336b87</td><td>Relative Forest for Attribute Prediction +</td></tr><tr><td>80097a879fceff2a9a955bf7613b0d3bfa68dc23</td><td>Active Self-Paced Learning for Cost-Effective and +<br/>Progressive Face Identification +</td><td>('1737218', 'Liang Lin', 'liang lin')<br/>('3170394', 'Keze Wang', 'keze wang')<br/>('1803714', 'Deyu Meng', 'deyu meng')<br/>('1724520', 'Wangmeng Zuo', 'wangmeng zuo')<br/>('36685537', 'Lei Zhang', 'lei zhang')</td><td></td></tr><tr><td>80bd795930837330e3ced199f5b9b75398336b87</td><td>Relative Forest for Attribute Prediction <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences <br/><b>CAS), Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>Graduate University of Chinese Academy of Sciences, Beijing 100049, China</b></td><td>('1688086', 'Shaoxin Li', 'shaoxin li')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>{shaoxin.li, shiguang.shan, xilin.chen}@vipl.ict.ac.cn </td></tr><tr><td>74de03923a069ffc0fb79e492ee447299401001f</td><td>On Film Character Retrieval in Feature-Length Films @@ -15612,9 +19911,37 @@ <br/>features, which is robust to face image variation of <br/>is </td><td>('5828998', 'Meng Yang', 'meng yang')<br/>('36685537', 'Lei Zhang', 'lei zhang')<br/>('40613710', 'Lin Zhang', 'lin zhang')<br/>('1698371', 'David Zhang', 'david zhang')</td><td>E-mail: {csmyang, cslzhang, cslinzhang, csdzhang}@comp.polyu.edu.hk +</td></tr><tr><td>74ce7e5e677a4925489897665c152a352c49d0a2</td><td>SONG ET AL.: SEGMENTATION-GUIDED IMAGE INPAINTING +<br/>SPG-Net: Segmentation Prediction and +<br/>Guidance Network for Image Inpainting +<br/><b>University of Southern California</b><br/>3740 McClintock Ave +<br/>Los Angeles, USA +<br/>2 Baidu Research +<br/>1195 Bordeaux Dr., +<br/>Sunnyvale, USA +</td><td>('3383051', 'Yuhang Song', 'yuhang song')<br/>('1683340', 'Chao Yang', 'chao yang')<br/>('8035191', 'Yeji Shen', 'yeji shen')<br/>('1722767', 'Peng Wang', 'peng wang')<br/>('38592052', 'Qin Huang', 'qin huang')<br/>('9363144', 'C.-C. Jay Kuo', 'c.-c. jay kuo')</td><td>yuhangso@usc.edu +<br/>chaoy@usc.edu +<br/>yejishen@usc.edu +<br/>wangpeng54@baidu.com +<br/>qinhuang@usc.edu +<br/>cckuo@sipi.usc.edu </td></tr><tr><td>74408cfd748ad5553cba8ab64e5f83da14875ae8</td><td>Facial Expressions Tracking and Recognition: Database Protocols for Systems Validation <br/>and Evaluation -</td><td></td><td></td></tr><tr><td>747d5fe667519acea1bee3df5cf94d9d6f874f20</td><td></td><td></td><td></td></tr><tr><td>740e095a65524d569244947f6eea3aefa3cca526</td><td>Towards Human-like Performance Face Detection: A +</td><td></td><td></td></tr><tr><td>747d5fe667519acea1bee3df5cf94d9d6f874f20</td><td></td><td></td><td></td></tr><tr><td>74dbe6e0486e417a108923295c80551b6d759dbe</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 45– No.11, May 2012 +<br/>An HMM based Model for Prediction of Emotional +<br/>Composition of a Facial Expression using both +<br/>Significant and Insignificant Action Units and +<br/>Associated Gender Differences +<br/>Department of Management and Information +<br/>Department of Management and Information +<br/>Systems Science +<br/>1603-1 Kamitomioka, Nagaoka +<br/>Niigata, Japan +<br/>Systems Science +<br/>1603-1 Kamitomioka, Nagaoka +<br/>Niigata, Japan +</td><td>('2931637', 'Suvashis Das', 'suvashis das')<br/>('1808643', 'Koichi Yamada', 'koichi yamada')</td><td></td></tr><tr><td>740e095a65524d569244947f6eea3aefa3cca526</td><td>Towards Human-like Performance Face Detection: A <br/>Convolutional Neural Network Approach <br/><b>University of Twente</b><br/>P.O. Box 217, 7500AE Enschede <br/>The Netherlands @@ -15632,9 +19959,37 @@ <br/>Martial Hebert, Co-Chair <br/>Alexei A. Efros, Co-Chair <br/>Takeo Kanade -<br/><b>Deva Ramanan, University of California at Irvine</b></td><td>('2038685', 'Santosh K. Divvala', 'santosh k. divvala')<br/>('2038685', 'Santosh K. Divvala', 'santosh k. divvala')</td><td></td></tr><tr><td>741485741734a99e933dd0302f457158c6842adf</td><td> A Novel Automatic Facial Expression +<br/><b>Deva Ramanan, University of California at Irvine</b></td><td>('2038685', 'Santosh K. Divvala', 'santosh k. divvala')<br/>('2038685', 'Santosh K. Divvala', 'santosh k. divvala')</td><td></td></tr><tr><td>747c25bff37b96def96dc039cc13f8a7f42dbbc7</td><td>EmoNets: Multimodal deep learning approaches for emotion +<br/>recognition in video +</td><td>('3127597', 'Samira Ebrahimi Kahou', 'samira ebrahimi kahou')<br/>('1748421', 'Vincent Michalski', 'vincent michalski')<br/>('2488222', 'Nicolas Boulanger-Lewandowski', 'nicolas boulanger-lewandowski')<br/>('1923596', 'David Warde-Farley', 'david warde-farley')<br/>('1751762', 'Yoshua Bengio', 'yoshua bengio')</td><td></td></tr><tr><td>741485741734a99e933dd0302f457158c6842adf</td><td> A Novel Automatic Facial Expression <br/>Recognition Method Based on AAM <br/><b>State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, China</b></td><td>('1703431', 'Li Wang', 'li wang')<br/>('2677485', 'Ruifeng Li', 'ruifeng li')<br/>('1751643', 'Ke Wang', 'ke wang')</td><td>Email: wangli-hb@163.com, lrf100@ hit.edu.cn, wangke@ hit.edu.cn +</td></tr><tr><td>744fa8062d0ae1a11b79592f0cd3fef133807a03</td><td>Aalborg Universitet +<br/>Deep Pain +<br/>Rodriguez, Pau; Cucurull, Guillem; Gonzàlez, Jordi; M. Gonfaus, Josep ; Nasrollahi, Kamal; +<br/>Moeslund, Thomas B.; Xavier Roca, F. +<br/>Published in: +<br/>I E E E Transactions on Cybernetics +<br/>DOI (link to publication from Publisher): +<br/>10.1109/TCYB.2017.2662199 +<br/>Publication date: +<br/>2017 +<br/>Document Version +<br/>Accepted author manuscript, peer reviewed version +<br/><b>Link to publication from Aalborg University</b><br/>Citation for published version (APA): +<br/>Rodriguez, P., Cucurull, G., Gonzàlez, J., M. Gonfaus, J., Nasrollahi, K., Moeslund, T. B., & Xavier Roca, F. +<br/>(2017). Deep Pain: Exploiting Long Short-Term Memory Networks for Facial Expression Classification. I E E E +<br/>Transactions on Cybernetics, 1-11. DOI: 10.1109/TCYB.2017.2662199 +<br/>General rights +<br/>Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners +<br/>and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. +<br/> ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. +<br/> ? You may not further distribute the material or use it for any profit-making activity or commercial gain +<br/> ? You may freely distribute the URL identifying the publication in the public portal ? +<br/>Take down policy +<br/>the work immediately and investigate your claim. +<br/>Downloaded from vbn.aau.dk on: marts 22, 2018 +<br/> </td><td></td><td>If you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access to </td></tr><tr><td>743e582c3e70c6ec07094887ce8dae7248b970ad</td><td>International Journal of Signal Processing, Image Processing and Pattern Recognition <br/>Vol.8, No.10 (2015), pp.29-38 <br/>http://dx.doi.org/10.14257/ijsip.2015.8.10.04 @@ -15647,11 +20002,18 @@ <br/>Recognition <br/><b>MIRACL-FSEG, University of Sfax</b><br/>3018 Sfax, Tunisia <br/><b>MIRACL-FS, University of Sfax</b><br/>3018 Sfax, Tunisia -</td><td>('2049116', 'Hazar Mliki', 'hazar mliki')<br/>('1749733', 'Mohamed Hammami', 'mohamed hammami')</td><td></td></tr><tr><td>745b42050a68a294e9300228e09b5748d2d20b81</td><td></td><td></td><td></td></tr><tr><td>749382d19bfe9fb8d0c5e94d0c9b0a63ab531cb7</td><td>A Modular Framework to Detect and Analyze Faces for +</td><td>('2049116', 'Hazar Mliki', 'hazar mliki')<br/>('1749733', 'Mohamed Hammami', 'mohamed hammami')</td><td></td></tr><tr><td>745b42050a68a294e9300228e09b5748d2d20b81</td><td></td><td></td><td></td></tr><tr><td>749d605dd12a4af58de1fae6f5ef5e65eb06540e</td><td>Multi-Task Video Captioning with Video and Entailment Generation +<br/>UNC Chapel Hill +</td><td>('10721120', 'Ramakanth Pasunuru', 'ramakanth pasunuru')<br/>('7736730', 'Mohit Bansal', 'mohit bansal')</td><td>{ram, mbansal}@cs.unc.edu +</td></tr><tr><td>749382d19bfe9fb8d0c5e94d0c9b0a63ab531cb7</td><td>A Modular Framework to Detect and Analyze Faces for <br/>Audience Measurement Systems <br/><b>Fraunhofer Institute for Integrated Circuits IIS</b><br/>Department Electronic Imaging <br/>Am Wolfsmantel 33, 91058 Erlangen, Germany </td><td>('33046373', 'Andreas Ernst', 'andreas ernst')<br/>('27421829', 'Tobias Ruf', 'tobias ruf')</td><td>{andreas.ernst, tobias.ruf, christian.kueblbeck}@iis.fraunhofer.de +</td></tr><tr><td>74c19438c78a136677a7cb9004c53684a4ae56ff</td><td>RESOUND: Towards Action Recognition +<br/>without Representation Bias +<br/>UC San Diego +</td><td>('48513320', 'Yingwei Li', 'yingwei li')<br/>('47002970', 'Yi Li', 'yi li')<br/>('1699559', 'Nuno Vasconcelos', 'nuno vasconcelos')</td><td>{yil325,yil898,nvasconcelos}@ucsd.edu </td></tr><tr><td>74618fb4ce8ce0209db85cc6069fe64b1f268ff4</td><td>Rendering and Animating Expressive <br/>Caricatures <br/>Mukundan @@ -15800,7 +20162,27 @@ <br/>J. Paone, D. Bolme, R. Ferrell, Member, IEEE, D. Aykac, and <br/>T. Karnowski, Member, IEEE <br/>Oak Ridge National Laboratory, Oak Ridge, TN -</td><td></td><td></td></tr><tr><td>1a46d3a9bc1e4aff0ccac6403b49a13c8a89fc1d</td><td>Online Robust Image Alignment via Iterative Convex Optimization +</td><td></td><td></td></tr><tr><td>1a849b694f2d68c3536ed849ed78c82e979d64d5</td><td>This is a repository copy of Symmetric Shape Morphing for 3D Face and Head Modelling. +<br/>White Rose Research Online URL for this paper: +<br/>http://eprints.whiterose.ac.uk/131760/ +<br/>Version: Accepted Version +<br/>Proceedings Paper: +<br/>Dai, Hang, Pears, Nicholas Edwin orcid.org/0000-0001-9513-5634, Smith, William Alfred +<br/>Peter orcid.org/0000-0002-6047-0413 et al. (1 more author) (2018) Symmetric Shape +<br/>Morphing for 3D Face and Head Modelling. In: The 13th IEEE Conference on Automatic +<br/>Face and Gesture Recognition. IEEE . +<br/>Reuse +<br/>Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless +<br/>indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by +<br/>national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of +<br/>the full text version. This is indicated by the licence information on the White Rose Research Online record +<br/>for the item. +<br/>Takedown +<br/>If you consider content in White Rose Research Online to be in breach of UK law, please notify us by +<br/>https://eprints.whiterose.ac.uk/ +</td><td></td><td>emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. +<br/>eprints@whiterose.ac.uk +</td></tr><tr><td>1a46d3a9bc1e4aff0ccac6403b49a13c8a89fc1d</td><td>Online Robust Image Alignment via Iterative Convex Optimization <br/>Center for Data Analytics & Biomedical Informatics, Computer & Information Science Department, <br/><b>Temple University, Philadelphia, PA 19122, USA</b><br/><b>School of Information and Control Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China</b><br/><b>Purdue University, West Lafayette, IN 47907, USA</b></td><td>('36578908', 'Yi Wu', 'yi wu')<br/>('39274045', 'Bin Shen', 'bin shen')<br/>('1805398', 'Haibin Ling', 'haibin ling')</td><td>fwuyi,hblingg@temple.edu, bshen@purdue.edu </td></tr><tr><td>1a878e4667fe55170252e3f41d38ddf85c87fcaf</td><td>Discriminative Machine Learning with Structure @@ -16123,7 +20505,13 @@ <br/>bgirod@stanford.edu </td></tr><tr><td>28b5b5f20ad584e560cd9fb4d81b0a22279b2e7b</td><td>A New Fuzzy Stacked Generalization Technique <br/>and Analysis of its Performance -</td><td>('2159942', 'Mete Ozay', 'mete ozay')<br/>('7158165', 'Fatos T. Yarman Vural', 'fatos t. yarman vural')</td><td></td></tr><tr><td>28bc378a6b76142df8762cd3f80f737ca2b79208</td><td>Understanding Objects in Detail with Fine-grained Attributes +</td><td>('2159942', 'Mete Ozay', 'mete ozay')<br/>('7158165', 'Fatos T. Yarman Vural', 'fatos t. yarman vural')</td><td></td></tr><tr><td>281486d172cf0c78d348ce7d977a82ff763efccd</td><td>Mining a Deep And-OR Object Semantics from Web Images via Cost-Sensitive +<br/>Question-Answer-Based Active Annotations +<br/><b>Shanghai Jiao Tong University</b><br/><b>University of California, Los Angeles</b><br/><b>cid:107)Chongqing University of Posts and Telecommunications</b></td><td>('22063226', 'Quanshi Zhang', 'quanshi zhang')<br/>('39092098', 'Ying Nian Wu', 'ying nian wu')<br/>('3133970', 'Song-Chun Zhu', 'song-chun zhu')</td><td></td></tr><tr><td>288964068cd87d97a98b8bc927d6e0d2349458a2</td><td>Mean-Variance Loss for Deep Age Estimation from a Face +<br/>1Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), +<br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, 100049, China</b><br/>3CAS Center for Excellence in Brain Science and Intelligence Technology +</td><td>('34393045', 'Hu Han', 'hu han')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>hongyu.pan@vipl.ict.ac.cn, {hanhu,sgshan,xlchen}@ict.ac.cn +</td></tr><tr><td>28bc378a6b76142df8762cd3f80f737ca2b79208</td><td>Understanding Objects in Detail with Fine-grained Attributes <br/>Ross Girshick5 <br/>David Weiss7 </td><td>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')<br/>('2585200', 'Siddharth Mahendran', 'siddharth mahendran')<br/>('2381485', 'Stavros Tsogkas', 'stavros tsogkas')<br/>('35208858', 'Subhransu Maji', 'subhransu maji')<br/>('1776374', 'Juho Kannala', 'juho kannala')<br/>('2827962', 'Esa Rahtu', 'esa rahtu')<br/>('1758219', 'Matthew B. Blaschko', 'matthew b. blaschko')<br/>('1685978', 'Ben Taskar', 'ben taskar')<br/>('2362960', 'Naomi Saphra', 'naomi saphra')<br/>('2920190', 'Sammy Mohamed', 'sammy mohamed')<br/>('2010660', 'Iasonas Kokkinos', 'iasonas kokkinos')<br/>('34838386', 'Karen Simonyan', 'karen simonyan')</td><td></td></tr><tr><td>287900f41dd880802aa57f602e4094a8a9e5ae56</td><td></td><td></td><td></td></tr><tr><td>28c0cb56e7f97046d6f3463378d084e9ea90a89a</td><td>Automatic Face Recognition for Film Character Retrieval in Feature-Length @@ -16409,6 +20797,13 @@ <br/>Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted <br/>use, provided the original author and source are credited. </td><td></td><td>e-mail: q.atkinson@auckland.ac.nz +</td></tr><tr><td>28d4e027c7e90b51b7d8908fce68128d1964668a</td><td></td><td></td><td></td></tr><tr><td>2866cbeb25551257683cf28f33d829932be651fe</td><td>In Proceedings of the 2018 IEEE International Conference on Image Processing (ICIP) +<br/>The final publication is available at: http://dx.doi.org/10.1109/ICIP.2018.8451026 +<br/>A TWO-STEP LEARNING METHOD FOR DETECTING LANDMARKS +<br/>ON FACES FROM DIFFERENT DOMAINS +<br/>Erickson R. Nascimento +<br/>Universidade Federal de Minas Gerais (UFMG), Brazil +</td><td>('2749017', 'Bruna Vieira Frade', 'bruna vieira frade')</td><td>{brunafrade, erickson}@dcc.ufmg.br </td></tr><tr><td>28d99dc2d673d62118658f8375b414e5192eac6f</td><td>Using Ranking-CNN for Age Estimation <br/>1Department of Computer Science <br/>2Department of Mathematics @@ -16522,7 +20917,21 @@ </td></tr><tr><td>17cf838720f7892dbe567129dcf3f7a982e0b56e</td><td>Global-Local Face Upsampling Network <br/><b>Mitsubishi Electric Research Labs (MERL), Cambridge, MA, USA</b></td><td>('2577513', 'Oncel Tuzel', 'oncel tuzel')<br/>('2066068', 'Yuichi Taguchi', 'yuichi taguchi')<br/>('2387467', 'John R. Hershey', 'john r. hershey')</td><td></td></tr><tr><td>17035089959a14fe644ab1d3b160586c67327db2</td><td></td><td></td><td></td></tr><tr><td>17370f848801871deeed22af152489e39b6e1454</td><td>UNDERSAMPLED FACE RECOGNITION WITH ONE-PASS DICTIONARY LEARNING <br/><b>Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan</b></td><td>('2017922', 'Chia-Po Wei', 'chia-po wei')<br/>('2733735', 'Yu-Chiang Frank Wang', 'yu-chiang frank wang')</td><td>{cpwei, ycwang}@citi.sinica.edu.tw -</td></tr><tr><td>17fa1c2a24ba8f731c8b21f1244463bc4b465681</td><td>Published as a conference paper at ICLR 2016 +</td></tr><tr><td>178a82e3a0541fa75c6a11350be5bded133a59fd</td><td>Techset Composition Ltd, Salisbury +<br/>Doc: +<br/>{IEE}BMT/Articles/Pagination/BMT20140045.3d +<br/>www.ietdl.org +<br/>Received on 15th July 2014 +<br/>Revised on 17th September 2014 +<br/>Accepted on 23rd September 2014 +<br/>doi: 10.1049/iet-bmt.2014.0045 +<br/>ISSN 2047-4938 +<br/>BioHDD: a dataset for studying biometric +<br/>identification on heavily degraded data +<br/><b>IT Instituto de Telecomunica es, University of Beira Interior, Covilh , Portugal</b><br/><b>Remote Sensing Unit Optics, Optometry and Vision Sciences Group, University of Beira Interior</b><br/>Covilhã, Portugal +</td><td>('1712429', 'Hugo Proença', 'hugo proença')</td><td>E-mail: gmelfe@ubi.pt +</td></tr><tr><td>17479e015a2dcf15d40190e06419a135b66da4e0</td><td>Predicting First Impressions with Deep Learning +<br/><b>University of Notre Dame</b><br/><b>Harvard University 3Perceptive Automata, Inc</b></td><td>('7215627', 'Mel McCurrie', 'mel mccurrie')<br/>('51174355', 'Fernando Beletti', 'fernando beletti')<br/>('51176594', 'Lucas Parzianello', 'lucas parzianello')<br/>('51176974', 'Allen Westendorp', 'allen westendorp')<br/>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')</td><td></td></tr><tr><td>17fa1c2a24ba8f731c8b21f1244463bc4b465681</td><td>Published as a conference paper at ICLR 2016 <br/>DEEP MULTI-SCALE VIDEO PREDICTION BEYOND <br/>MEAN SQUARE ERROR <br/><b>New York University</b><br/>2Facebook Artificial Intelligence Research @@ -16542,7 +20951,10 @@ <br/>melih.aslan@wayne.edu <br/>kunlei.zhang@wayne.edu <br/>t-huang1@illinois.edu -</td></tr><tr><td>17aa78bd4331ef490f24bdd4d4cd21d22a18c09c</td><td></td><td></td><td></td></tr><tr><td>170a5f5da9ac9187f1c88f21a88d35db38b4111a</td><td>Online Real-time Multiple Spatiotemporal Action Localisation and Prediction +</td></tr><tr><td>17a995680482183f3463d2e01dd4c113ebb31608</td><td>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. Y, MONTH Z +<br/>Structured Label Inference for +<br/>Visual Understanding +</td><td>('3079079', 'Nelson Nauata', 'nelson nauata')<br/>('2804000', 'Hexiang Hu', 'hexiang hu')<br/>('2057809', 'Guang-Tong Zhou', 'guang-tong zhou')<br/>('47640964', 'Zhiwei Deng', 'zhiwei deng')<br/>('2928799', 'Zicheng Liao', 'zicheng liao')<br/>('10771328', 'Greg Mori', 'greg mori')</td><td></td></tr><tr><td>17aa78bd4331ef490f24bdd4d4cd21d22a18c09c</td><td></td><td></td><td></td></tr><tr><td>170a5f5da9ac9187f1c88f21a88d35db38b4111a</td><td>Online Real-time Multiple Spatiotemporal Action Localisation and Prediction <br/>Philip Torr2 <br/><b>Oxford Brookes University</b><br/><b>Oxford University</b><br/>Figure 1: Online spatiotemporal action localisation in a test ‘fencing’ video from UCF-101 [39]. (a) to (c): A 3D volumetric view of <br/>the video showing detection boxes and selected frames. At any given time, a certain portion (%) of the entire video is observed by the @@ -16552,7 +20964,9 @@ <br/>at frame 114, and initiating a new tube (03) at frame 146. </td><td>('1931660', 'Gurkirt Singh', 'gurkirt singh')<br/>('3017538', 'Suman Saha', 'suman saha')<br/>('3019396', 'Michael Sapienza', 'michael sapienza')<br/>('1754181', 'Fabio Cuzzolin', 'fabio cuzzolin')</td><td>{gurkirt.singh-2015,suman.saha-2014,fabio.cuzzolin}@brookes.ac.uk <br/>{michael.sapienza,philip.torr}@eng.ox.ac.uk -</td></tr><tr><td>1742ffea0e1051b37f22773613f10f69d2e4ed2c</td><td></td><td></td><td></td></tr><tr><td>1791f790b99471fc48b7e9ec361dc505955ea8b1</td><td></td><td></td><td></td></tr><tr><td>171d8a39b9e3d21231004f7008397d5056ff23af</td><td>Simultaneous Facial Landmark Detection, Pose and Deformation Estimation +</td></tr><tr><td>17c0d99171efc957b88c31a465c59485ab033234</td><td></td><td></td><td></td></tr><tr><td>1742ffea0e1051b37f22773613f10f69d2e4ed2c</td><td></td><td></td><td></td></tr><tr><td>1791f790b99471fc48b7e9ec361dc505955ea8b1</td><td></td><td></td><td></td></tr><tr><td>17a8d1b1b4c23a630b051f35e47663fc04dcf043</td><td>Differential Angular Imaging for Material Recognition +<br/><b>Rutgers University, Piscataway, NJ</b><br/><b>Drexel University, Philadelphia, PA</b></td><td>('48181328', 'Jia Xue', 'jia xue')</td><td>{jia.xue,zhang.hang}@rutgers.edu, kdana@ece.rutgers.edu, kon@drexel.edu +</td></tr><tr><td>171d8a39b9e3d21231004f7008397d5056ff23af</td><td>Simultaneous Facial Landmark Detection, Pose and Deformation Estimation <br/>under Facial Occlusion <br/>ECSE Department <br/><b>Institute of Automation</b><br/>ECSE Department @@ -16592,7 +21006,13 @@ <br/>Department of Electrical and Computer Engineering <br/><b>The University of Tennessee, Knoxville</b><br/>AUTOMATIC FACE REGION TRACKING FOR HIGHLY ACCURATE FACE <br/>RECOGNITION IN UNCONSTRAINED ENVIRONMENTS -</td><td>('2243148', 'Young-Ouk Kim', 'young-ouk kim')<br/>('1684329', 'Joonki Paik', 'joonki paik')<br/>('39533703', 'Jingu Heo', 'jingu heo')</td><td></td></tr><tr><td>174f46eccb5852c1f979d8c386e3805f7942bace</td><td>The Shape-Time Random Field for Semantic Video Labeling +</td><td>('2243148', 'Young-Ouk Kim', 'young-ouk kim')<br/>('1684329', 'Joonki Paik', 'joonki paik')<br/>('39533703', 'Jingu Heo', 'jingu heo')</td><td></td></tr><tr><td>173657da03e3249f4e47457d360ab83b3cefbe63</td><td>HKU-Face: A Large Scale Dataset for +<br/>Deep Face Recognition +<br/>Final Report +<br/>3035140108 +<br/>COMP4801 Final Year Project +<br/>Project Code: 17007 +</td><td>('3347561', 'Haicheng Wang', 'haicheng wang')</td><td></td></tr><tr><td>174f46eccb5852c1f979d8c386e3805f7942bace</td><td>The Shape-Time Random Field for Semantic Video Labeling <br/>School of Computer Science <br/><b>University of Massachusetts, Amherst MA, USA</b></td><td>('2177037', 'Andrew Kae', 'andrew kae')</td><td>{akae,marlin,elm}@cs.umass.edu </td></tr><tr><td>17670b60dcfb5cbf8fdae0b266e18cf995f6014c</td><td>Longitudinal Face Modeling via @@ -16616,7 +21036,15 @@ <br/><b>The Chinese University of Hong Kong</b><br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b></td><td>('1681656', 'Yi Sun', 'yi sun')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>sy011@ie.cuhk.edu.hk <br/>xgwang@ee.cuhk.edu.hk <br/>xtang@ie.cuhk.edu.hk -</td></tr><tr><td>7ba0bf9323c2d79300f1a433ff8b4fe0a00ad889</td><td></td><td></td><td></td></tr><tr><td>7b63ed54345d8c06523f6b03c41a09b5c8f227e2</td><td>Facial Expression Recognition Based on +</td></tr><tr><td>7ba0bf9323c2d79300f1a433ff8b4fe0a00ad889</td><td></td><td></td><td></td></tr><tr><td>7bbaa09c9e318da4370a83b126bcdb214e7f8428</td><td>FaaSter, Better, Cheaper: The Prospect of +<br/>Serverless Scientific Computing and HPC +<br/><b>Zurich University of Applied Sciences, School of Engineering</b><br/>Service Prototyping Lab (blog.zhaw.ch/icclab/), 8401 Winterthur, Switzerland +<br/><b>ISISTAN Research Institute - CONICET - UNICEN</b><br/>Campus Universitario, Paraje Arroyo Seco, Tandil (7000), Buenos Aires, Argentina +<br/><b>ITIC Research Institute, National University of Cuyo</b><br/>Padre Jorge Contreras 1300, M5502JMA Mendoza, Argentina +</td><td>('1765470', 'Josef Spillner', 'josef spillner')<br/>('2891834', 'Cristian Mateos', 'cristian mateos')<br/>('34889755', 'David A. Monge', 'david a. monge')</td><td>josef.spillner@zhaw.ch +<br/>cristian.mateos@isistan.unicen.edu.ar +<br/>dmonge@uncu.edu.ar +</td></tr><tr><td>7b63ed54345d8c06523f6b03c41a09b5c8f227e2</td><td>Facial Expression Recognition Based on <br/>Combination of Spatio-temporal and Spectral <br/>Features in Local Facial Regions <br/>Department of Electrical Engineering, @@ -16649,6 +21077,16 @@ <br/>for Video-Based Facial Expression Recognition <br/><b>VISLab, EBUII-216, University of California Riverside</b><br/>Riverside, California, USA, 92521-0425 </td><td>('1707159', 'Bir Bhanu', 'bir bhanu')<br/>('1803478', 'Songfan Yang', 'songfan yang')</td><td>{acruz, bhanu, syang}@ee.ucr.edu +</td></tr><tr><td>7b0f1fc93fb24630eb598330e13f7b839fb46cce</td><td>Learning to Find Eye Region Landmarks for Remote Gaze +<br/>Estimation in Unconstrained Settings +<br/>ETH Zurich +<br/>MPI for Informatics +<br/>MPI for Informatics +<br/>ETH Zurich +</td><td>('20466488', 'Seonwook Park', 'seonwook park')<br/>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')<br/>('2531379', 'Otmar Hilliges', 'otmar hilliges')</td><td>spark@inf.ethz.ch +<br/>xczhang@mpi-inf.mpg.de +<br/>bulling@mpi-inf.mpg.de +<br/>otmarh@inf.ethz.ch </td></tr><tr><td>7be60f8c34a16f30735518d240a01972f3530e00</td><td>Facial Expression Recognition with Temporal Modeling of Shapes <br/><b></b><br/><b>The University of Texas at Austin</b></td><td>('18692590', 'Suyog Jain', 'suyog jain')<br/>('1713065', 'Changbo Hu', 'changbo hu')</td><td>suyog@cs.utexas.edu, changbo.hu@gmail.com, aggarwaljk@mail.utexas.edu </td></tr><tr><td>7bdcd85efd1e3ce14b7934ff642b76f017419751</td><td>289 @@ -16677,13 +21115,53 @@ <br/>erikmc@google.com <br/>sycheng@hrl.com <br/>mtrivedi@ucsd.edu -</td></tr><tr><td>8f3e120b030e6c1d035cb7bd9c22f6cc75782025</td><td>Bayesian Networks and the Imprecise Dirichlet +</td></tr><tr><td>8fe38962c24300129391f6d7ac24d7783e0fddd0</td><td><b>Center for Research in Computer Vision, University of Central Florida</b></td><td>('33209161', 'Amir Mazaheri', 'amir mazaheri')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>amirmazaheri@knights.ucf.edu +<br/>shah@crcv.ucf.edu +</td></tr><tr><td>8f6d05b8f9860c33c7b1a5d704694ed628db66c7</td><td>Non-linear dimensionality reduction and sparse +<br/>representation models for facial analysis +<br/>To cite this version: +<br/>Medical Imaging. INSA de Lyon, 2014. English. <NNT : 2014ISAL0019>. <tel-01127217> +<br/>HAL Id: tel-01127217 +<br/>https://tel.archives-ouvertes.fr/tel-01127217 +<br/>Submitted on 7 Mar 2015 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('35061362', 'Yuyao Zhang', 'yuyao zhang')<br/>('35061362', 'Yuyao Zhang', 'yuyao zhang')</td><td></td></tr><tr><td>8f772d9ce324b2ef5857d6e0b2a420bc93961196</td><td>MAHPOD et al.: CFDRNN +<br/>Facial Landmark Point Localization using +<br/>Coarse-to-Fine Deep Recurrent Neural Network +</td><td>('2748312', 'Shahar Mahpod', 'shahar mahpod')<br/>('3001038', 'Rig Das', 'rig das')<br/>('1767715', 'Emanuele Maiorana', 'emanuele maiorana')<br/>('1926432', 'Yosi Keller', 'yosi keller')<br/>('1682433', 'Patrizio Campisi', 'patrizio campisi')</td><td></td></tr><tr><td>8f3e120b030e6c1d035cb7bd9c22f6cc75782025</td><td>Bayesian Networks and the Imprecise Dirichlet <br/>Model applied to Recognition Problems <br/><b>Dalle Molle Institute for Arti cial Intelligence</b><br/>Galleria 2, Manno-Lugano, Switzerland <br/><b>Rensselaer Polytechnic Institute</b><br/>110 Eighth St., Troy, NY, USA </td><td>('1726583', 'Qiang Ji', 'qiang ji')</td><td>cassio@idsia.ch, jiq@rpi.edu -</td></tr><tr><td>8fb611aca3bd8a3a0527ac0f38561a5a9a5b8483</td><td></td><td></td><td></td></tr><tr><td>8fa3478aaf8e1f94e849d7ffbd12146946badaba</td><td>Attributes for Classifier Feedback -<br/><b>Indraprastha Institute of Information Technology (Delhi, India</b><br/><b>Toyota Technological Institute (Chicago, US</b></td><td>('2076800', 'Amar Parkash', 'amar parkash')<br/>('1713589', 'Devi Parikh', 'devi parikh')</td><td></td></tr><tr><td>8f8c0243816f16a21dea1c20b5c81bc223088594</td><td></td><td></td><td></td></tr><tr><td>8f08b2101d43b1c0829678d6a824f0f045d57da5</td><td>Supplementary Material for: Active Pictorial Structures +</td></tr><tr><td>8fb611aca3bd8a3a0527ac0f38561a5a9a5b8483</td><td></td><td></td><td></td></tr><tr><td>8fda2f6b85c7e34d3e23927e501a4b4f7fc15b2a</td><td>Feature Selection with Annealing for Big Data +<br/>Learning +</td><td>('2455529', 'Adrian Barbu', 'adrian barbu')<br/>('34680388', 'Yiyuan She', 'yiyuan she')<br/>('2139735', 'Liangjing Ding', 'liangjing ding')<br/>('3019469', 'Gary Gramajo', 'gary gramajo')</td><td></td></tr><tr><td>8fed5ea3b69ea441a8b02f61473eafee25fb2374</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Two-Dimensional PCA with F-Norm Minimization +<br/><b>State Key Laboratory of ISN, Xidian University</b><br/><b>State Key Laboratory of ISN, Xidian University</b><br/>Xi’an China +<br/>Xi’an China +</td><td>('38469552', 'Quanxue Gao', 'quanxue gao')<br/>('40326660', 'Qianqian Wang', 'qianqian wang')</td><td></td></tr><tr><td>8fa3478aaf8e1f94e849d7ffbd12146946badaba</td><td>Attributes for Classifier Feedback +<br/><b>Indraprastha Institute of Information Technology (Delhi, India</b><br/><b>Toyota Technological Institute (Chicago, US</b></td><td>('2076800', 'Amar Parkash', 'amar parkash')<br/>('1713589', 'Devi Parikh', 'devi parikh')</td><td></td></tr><tr><td>8f3da45ff0c3e1777c3a7830f79c10f5896bcc21</td><td>Situation Recognition with Graph Neural Networks +<br/><b>The Chinese University of Hong Kong, 2University of Toronto, 3Youtu Lab, Tencent</b><br/><b>Uber Advanced Technologies Group, 5Vector Institute</b></td><td>('8139953', 'Ruiyu Li', 'ruiyu li')<br/>('2103464', 'Makarand Tapaswi', 'makarand tapaswi')<br/>('2246396', 'Renjie Liao', 'renjie liao')<br/>('1729056', 'Jiaya Jia', 'jiaya jia')<br/>('2422559', 'Raquel Urtasun', 'raquel urtasun')<br/>('37895334', 'Sanja Fidler', 'sanja fidler')</td><td>ryli@cse.cuhk.edu.hk, {makarand,rjliao,urtasun,fidler}@cs.toronto.edu, leojia9@gmail.com +</td></tr><tr><td>8ff8c64288a2f7e4e8bf8fda865820b04ab3dbe8</td><td>Age Estimation Using Expectation of Label Distribution Learning ∗ +<br/><b>National Key Laboratory for Novel Software Technology, Nanjing University, China</b><br/><b>MOE Key Laboratory of Computer Network and Information Integration, Southeast University, China</b></td><td>('2226422', 'Bin-Bin Gao', 'bin-bin gao')<br/>('7678704', 'Hong-Yu Zhou', 'hong-yu zhou')<br/>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('1735299', 'Xin Geng', 'xin geng')</td><td>{gaobb,zhouhy,wujx}@lamda.nju.edu.cn, xgeng@seu.edu.cn +</td></tr><tr><td>8f9c37f351a91ed416baa8b6cdb4022b231b9085</td><td>Generative Adversarial Style Transfer Networks for Face Aging +<br/>Sveinn Palsson +<br/>D-ITET, ETH Zurich +<br/>Eirikur Agustsson +<br/>D-ITET, ETH Zurich +</td><td></td><td>spalsson@ethz.ch +<br/>aeirikur@ethz.ch +</td></tr><tr><td>8f8c0243816f16a21dea1c20b5c81bc223088594</td><td></td><td></td><td></td></tr><tr><td>8f08b2101d43b1c0829678d6a824f0f045d57da5</td><td>Supplementary Material for: Active Pictorial Structures <br/><b>Imperial College London</b><br/>180 Queens Gate, SW7 2AZ, London, U.K. <br/>In the following sections, we provide additional material for the paper “Active Pictorial Structures”. Section 1 explains in <br/>more detail the differences between the proposed Active Pictorial Structures (APS) and Pictorial Structures (PS). Section 2 @@ -16809,6 +21287,21 @@ <br/><b>Hankuk University of Foreign Studies, South Korea</b><br/>M. Abdullah-Al-Wadud </td><td>('39036762', 'Mohammad Ibrahim', 'mohammad ibrahim')<br/>('31210416', 'Humayun Kayesh', 'humayun kayesh')<br/>('13193999', 'Shah', 'shah')<br/>('2233124', 'Mohammad Shoyaib', 'mohammad shoyaib')</td><td>ibrahim iit@yahoo.com, iftekhar.efat@gmail.com, hkayesh@gmail.com, khaled@univdhaka.edu, shoyaib@du.ac.bd <br/>wadud@hufs.ac.kr +</td></tr><tr><td>8acdc4be8274e5d189fb67b841c25debf5223840</td><td>Gultepe and Makrehchi +<br/>Hum. Cent. Comput. Inf. Sci. (2018) 8:25 +<br/>https://doi.org/10.1186/s13673-018-0148-3 +<br/>RESEARCH +<br/>Improving clustering performance +<br/>using independent component analysis +<br/>and unsupervised feature learning +<br/>Open Access +<br/>*Correspondence: +<br/>Department of Electrical +<br/>and Computer Engineering, +<br/><b>University of Ontario Institute</b><br/>of Technology, 2000 Simcoe +<br/>St N, Oshawa, ON L1H 7K4, +<br/>Canada +</td><td>('2729102', 'Eren Gultepe', 'eren gultepe')<br/>('3183840', 'Masoud Makrehchi', 'masoud makrehchi')</td><td>eren.gultepe@uoit.net </td></tr><tr><td>8a1ed5e23231e86216c9bdd62419c3b05f1e0b4d</td><td>Facial Keypoint Detection <br/><b>Stanford University</b><br/>March 13, 2016 </td><td>('29909347', 'Shayne Longpre', 'shayne longpre')<br/>('9928926', 'Ajay Sohmshetty', 'ajay sohmshetty')</td><td>slongpre@stanford.edu, ajay14@stanford.edu @@ -16834,18 +21327,37 @@ <br/>émanant des établissements d’enseignement et de <br/>recherche français ou étrangers, des laboratoires <br/>publics ou privés. -</td><td>('34678433', 'Filippo Mazza', 'filippo mazza')<br/>('40130265', 'Matthieu Perreira Da Silva', 'matthieu perreira da silva')<br/>('7591543', 'Patrick Le Callet', 'patrick le callet')<br/>('34678433', 'Filippo Mazza', 'filippo mazza')<br/>('40130265', 'Matthieu Perreira Da Silva', 'matthieu perreira da silva')<br/>('7591543', 'Patrick Le Callet', 'patrick le callet')<br/>('1728396', 'Ingrid Heynderickx', 'ingrid heynderickx')</td><td></td></tr><tr><td>8aae23847e1beb4a6d51881750ce36822ca7ed0b</td><td>Comparison Between Geometry-Based and Gabor-Wavelets-Based +</td><td>('34678433', 'Filippo Mazza', 'filippo mazza')<br/>('40130265', 'Matthieu Perreira Da Silva', 'matthieu perreira da silva')<br/>('7591543', 'Patrick Le Callet', 'patrick le callet')<br/>('34678433', 'Filippo Mazza', 'filippo mazza')<br/>('40130265', 'Matthieu Perreira Da Silva', 'matthieu perreira da silva')<br/>('7591543', 'Patrick Le Callet', 'patrick le callet')<br/>('1728396', 'Ingrid Heynderickx', 'ingrid heynderickx')</td><td></td></tr><tr><td>8a8861ad6caedc3993e31d46e7de6c251a8cda22</td><td>StreetStyle: Exploring world-wide clothing styles from millions of photos +<br/><b>Cornell University</b><br/>Figure 1: Extracting and measuring clothing style from Internet photos at scale. (a) We apply deep learning methods to learn to extract +<br/>fashion attributes from images and create a visual embedding of clothing style. We use this embedding to analyze millions of Instagram photos +<br/>of people sampled worldwide, in order to study spatio-temporal trends in clothing around the globe. (b) Further, using our embedding, we +<br/>can cluster images to produce a global set of representative styles, from which we can (c) use temporal and geo-spatial statistics to generate +<br/>concise visual depictions of what makes clothing unique in each city versus the rest. +</td><td>('40353974', 'Kevin Matzen', 'kevin matzen')<br/>('1791337', 'Kavita Bala', 'kavita bala')<br/>('1830653', 'Noah Snavely', 'noah snavely')</td><td></td></tr><tr><td>8aae23847e1beb4a6d51881750ce36822ca7ed0b</td><td>Comparison Between Geometry-Based and Gabor-Wavelets-Based <br/>Facial Expression Recognition Using Multi-Layer Perceptron <br/><b>ATR Human Information Processing Research Laboratories</b><br/><b>ATR Interpreting Telecommunications Research Laboratories</b><br/>2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-02, Japan <br/>INRIA, 2004 route des Lucioles, BP 93, F-06902 Sophia-Antipolis Cedex, France </td><td>('1809184', 'Zhengyou Zhang', 'zhengyou zhang')<br/>('34801422', 'Shigeru Akamatsu', 'shigeru akamatsu')<br/>('36206997', 'Michael Schuster', 'michael schuster')</td><td>e-mail: zzhang@sophia.inria.fr, zzhang@hip.atr.co.jp +</td></tr><tr><td>8a866bc0d925dfd8bb10769b8b87d7d0ff01774d</td><td>WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art +<br/>National Research Council Canada +</td><td>('2886725', 'Svetlana Kiritchenko', 'svetlana kiritchenko')</td><td>{saif.mohammad,svetlana.kiritchenko}@nrc-cnrc.gc.ca </td></tr><tr><td>8a40b6c75dd6392ee0d3af73cdfc46f59337efa9</td><td></td><td></td><td></td></tr><tr><td>8a3bb63925ac2cdf7f9ecf43f71d65e210416e17</td><td>ShearFace: Efficient Extraction of Anisotropic <br/>Features for Face Recognition <br/>1Research Groups on Intelligent Machines, <br/><b>University of Sfax</b><br/> Sfax 3038, Tunisia <br/>and anisotropic </td><td>('2791150', 'Mohamed Anouar Borgi', 'mohamed anouar borgi')<br/>('8847309', 'Demetrio Labate', 'demetrio labate')</td><td>{anoir.borgi@ieee.org; dlabate@math.uh.edu} -</td></tr><tr><td>8ad0d8cf4bcb5c7eccf09f23c8b7d25439c4ae2b</td><td>Predicting the Future with Transformational +</td></tr><tr><td>8a0159919ee4e1a9f4cbfb652a1be212bf0554fd</td><td><b>University of Surrey</b><br/>Faculty of Engineering and Physical Sciences +<br/>Department of Computer Science +<br/>PhD Thesis +<br/>Application of Power Laws to +<br/>Biometrics, Forensics and +<br/>Network Traffic Analysis +<br/>by +<br/>Supervisor: Prof. A.T.S. Ho +<br/>Co-supervisors: Dr. N. Poh, Dr. S. Li +<br/>November, 2016 +</td><td>('2909991', 'Aamo Iorliam', 'aamo iorliam')</td><td></td></tr><tr><td>8ad0d8cf4bcb5c7eccf09f23c8b7d25439c4ae2b</td><td>Predicting the Future with Transformational <br/>States <br/><b>University of Pennsylvania, 2Ryerson University</b></td><td>('2689633', 'Andrew Jaegle', 'andrew jaegle')<br/>('40805511', 'Oleh Rybkin', 'oleh rybkin')<br/>('3150825', 'Konstantinos G. Derpanis', 'konstantinos g. derpanis')<br/>('1751586', 'Kostas Daniilidis', 'kostas daniilidis')</td><td>ajaegle@upenn.edu, oleh@cis.upenn.edu, <br/>kosta@scs.ryerson.ca, kostas@cis.upenn.edu @@ -16874,7 +21386,15 @@ <br/>Detecting Visually Observable Disease <br/>Symptoms from Faces <br/>Open Access -</td><td>('2207567', 'Kuan Wang', 'kuan wang')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')</td><td></td></tr><tr><td>7e8016bef2c180238f00eecc6a50eac473f3f138</td><td>TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN +</td><td>('2207567', 'Kuan Wang', 'kuan wang')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')</td><td></td></tr><tr><td>7e600faee0ba11467d3f7aed57258b0db0448a72</td><td></td><td></td><td></td></tr><tr><td>7ed3b79248d92b255450c7becd32b9e5c834a31e</td><td>L1-regularized Logistic Regression Stacking and Transductive CRF Smoothing +<br/>for Action Recognition in Video +<br/><b>University of Florence</b><br/>Lorenzo Seidenari +<br/><b>University of Florence</b><br/>Andrew D. Bagdanov +<br/><b>University of Florence</b><br/><b>University of Florence</b></td><td>('2602265', 'Svebor Karaman', 'svebor karaman')<br/>('8196487', 'Alberto Del Bimbo', 'alberto del bimbo')</td><td>svebor.karaman@unifi.it +<br/>lorenzo.seidenari@unifi.it +<br/>bagdanov@dsi.unifi.it +<br/>alberto.delbimbo@unifi.it +</td></tr><tr><td>7e8016bef2c180238f00eecc6a50eac473f3f138</td><td>TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN <br/>Lehrstuhl f¨ur Mensch-Maschine-Kommunikation <br/>Immersive Interactive Data Mining and Machine <br/>Learning Algorithms for Big Data Visualization @@ -16927,6 +21447,15 @@ <br/>aFor a comprehensive review of object recognition methods and deformable templates in particular, <br/>see Refs. 1–4. </td><td>('1797883', 'Vasileios Zografos', 'vasileios zografos')<br/>('31557997', 'Bernard F. Buxton', 'bernard f. buxton')</td><td>{v.zografos,b.buxton}@cs.ucl.ac.uk +</td></tr><tr><td>7eaa97be59019f0d36aa7dac27407b004cad5e93</td><td>Sampling Generative Networks +<br/>School of Design +<br/><b>Victoria University of Wellington</b><br/>Wellington, New Zealand +</td><td>('40603980', 'Tom White', 'tom white')</td><td>tom.white@vuw.ac.nz +</td></tr><tr><td>7eb895e7de883d113b75eda54389460c61d63f67</td><td>Can you tell a face from a HEVC bitstream? +<br/><b>School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada</b></td><td>('3393216', 'Saeed Ranjbar Alvar', 'saeed ranjbar alvar')<br/>('3320198', 'Hyomin Choi', 'hyomin choi')</td><td>Email: {saeedr,chyomin, ibajic}@sfu.ca +</td></tr><tr><td>7e467e686f9468b826133275484e0a1ec0f5bde6</td><td>Efficient On-the-fly Category Retrieval +<br/>using ConvNets and GPUs +<br/><b>Visual Geometry Group, University of Oxford</b></td><td>('34838386', 'Karen Simonyan', 'karen simonyan')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{ken,karen,az}@robots.ox.ac.uk </td></tr><tr><td>7e3367b9b97f291835cfd0385f45c75ff84f4dc5</td><td>Improved Local Binary Pattern Based Action Unit Detection Using <br/>Morphological and Bilateral Filters <br/>1Signal Processing Laboratory (LTS5) @@ -16936,10 +21465,37 @@ <br/>Lausanne, Switzerland </td><td>('2916630', 'Matteo Sorci', 'matteo sorci')<br/>('1710257', 'Jean-Philippe Thiran', 'jean-philippe thiran')</td><td>{anil.yuce;jean-philippe.thiran}@epfl.ch <br/>matteo.sorci@nviso.ch -</td></tr><tr><td>7e00fb79576fe213853aeea39a6bc51df9fdca16</td><td>Online Multi-Face Detection and Tracking +</td></tr><tr><td>7ef0cc4f3f7566f96f168123bac1e07053a939b2</td><td>Triangular Similarity Metric Learning: a Siamese +<br/>Architecture Approach +<br/>To cite this version: +<br/>puter Science [cs]. UNIVERSITE DE LYON, 2016. English. <NNT : 2016LYSEI045>. <tel- +<br/>01314392> +<br/>HAL Id: tel-01314392 +<br/>https://hal.archives-ouvertes.fr/tel-01314392 +<br/>Submitted on 11 May 2016 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destin´ee au d´epˆot et `a la diffusion de documents +<br/>scientifiques de niveau recherche, publi´es ou non, +<br/>´emanant des ´etablissements d’enseignement et de +<br/>recherche fran¸cais ou ´etrangers, des laboratoires +<br/>publics ou priv´es. +</td><td>('37848497', 'Lilei Zheng', 'lilei zheng')<br/>('37848497', 'Lilei Zheng', 'lilei zheng')</td><td></td></tr><tr><td>7e00fb79576fe213853aeea39a6bc51df9fdca16</td><td>Online Multi-Face Detection and Tracking <br/>using Detector Confidence and Structured SVMs <br/><b>Eindhoven University of Technology, The Netherlands</b><br/>2TNO Embedded Systems Innovation, Eindhoven, The Netherlands </td><td>('3199035', 'Francesco Comaschi', 'francesco comaschi')<br/>('1679431', 'Sander Stuijk', 'sander stuijk')<br/>('1708289', 'Twan Basten', 'twan basten')<br/>('1684335', 'Henk Corporaal', 'henk corporaal')</td><td>{f.comaschi, s.stuijk, a.a.basten, h.corporaal}@tue.nl +</td></tr><tr><td>7e2cfbfd43045fbd6aabd9a45090a5716fc4e179</td><td>Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False Positive Rate +<br/>Global Norm-Aware Pooling for Pose-Robust Face Recognition at Low False +<br/>Positive Rate +<br/><b>a School of Computer and Information Technology, Beijing Jiaotong University, Beijing</b><br/>China +<br/><b>b Research Institute, Watchdata Inc., Beijing, China</b><br/>c DeepInSight, China +</td><td>('39326372', 'Sheng Chen', 'sheng chen')<br/>('3007274', 'Jia Guo', 'jia guo')<br/>('1681842', 'Yang Liu', 'yang liu')<br/>('46757550', 'Xiang Gao', 'xiang gao')<br/>('2765914', 'Zhen Han', 'zhen han')</td><td>{shengchen, zhan}@bjtu.edu.cn +<br/>{yang.liu.yj, xiang.gao}@watchdata.com +<br/>guojia@gmail.com </td></tr><tr><td>7ee53d931668fbed1021839db4210a06e4f33190</td><td>What if we do not have multiple videos of the same action? — <br/>Video Action Localization Using Web Images <br/><b>Center for Research in Computer Vision (CRCV), University of Central Florida (UCF</b></td><td>('3195774', 'Waqas Sultani', 'waqas sultani')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>waqassultani@knights.ucf.edu, shah@crcv.ucf.edu @@ -17023,13 +21579,124 @@ <br/><b>Nanyang Technological University, 2University of California San Diego</b></td><td>('36375772', 'Supriya Sathyanarayana', 'supriya sathyanarayana')<br/>('1710219', 'Ravi Kumar Satzoda', 'ravi kumar satzoda')<br/>('1924458', 'Suchitra Sathyanarayana', 'suchitra sathyanarayana')</td><td>supriya001@e.ntu.edu.sg, rsatzoda@eng.ucsd.edu, ssathyanarayana@ucsd.edu, astsrikan@ntu.edu.sg </td></tr><tr><td>7ed6ff077422f156932fde320e6b3bd66f8ffbcb</td><td>State of 3D Face Biometrics for Homeland Security Applications <br/>Chaudhari4 -</td><td>('2925401', 'Anshuman Razdan', 'anshuman razdan')<br/>('1693971', 'Gerald Farin', 'gerald farin')</td><td></td></tr><tr><td>7e0c75ce731131e613544e1a85ae0f2c28ee4c1f</td><td><b>Imperial College London</b><br/>Department of Computing +</td><td>('2925401', 'Anshuman Razdan', 'anshuman razdan')<br/>('1693971', 'Gerald Farin', 'gerald farin')</td><td></td></tr><tr><td>7ebb153704706e457ab57b432793d2b6e5d12592</td><td>ZHONG, ARANDJELOVI ´C, ZISSERMAN: FACES IN PLACES +<br/>Faces In Places: compound query retrieval +<br/>Relja Arandjelovi´c2 +<br/>1 Visual Geometry Group +<br/>Department of Engineering Science +<br/><b>University of Oxford, UK</b><br/>2 WILLOW project +<br/>Departement d’Informatique de l’École +<br/>Normale Supérieure +<br/>ENS/INRIA/CNRS UMR 8548 +</td><td>('6730372', 'Yujie Zhong', 'yujie zhong')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>yujie@robots.ox.ac.uk +<br/>relja.arandjelovic@inria.fr +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>7ec7163ec1bc237c4c2f2841c386f2dbfd0cc922</td><td>ORIGINAL RESEARCH +<br/>published: 20 June 2018 +<br/>doi: 10.3389/fpsyg.2018.00971 +<br/>Skiing and Thinking About It: +<br/>Moment-to-Moment and +<br/>Retrospective Analysis of Emotions +<br/>in an Extreme Sport +<br/>and Tove Irene Dahl +<br/><b>UiT The Arctic University of Norway, Troms , Norway</b><br/>Happiness is typically reported as an important reason for participating in challenging +<br/>activities like extreme sport. While in the middle of the activity, however, participants +<br/>do not seem particularly happy. So where does the happiness come from? The +<br/>article proposes some answers from a study of facially expressed emotions measured +<br/>moment-by-moment during a backcountry skiing event. Self-reported emotions were +<br/>also assessed immediately after the skiing. Participants expressed lower levels of +<br/>happiness while skiing, compared to when stopping for a break. Moment-to-moment +<br/>and self-reported measures of emotions were largely unrelated. These findings are +<br/>explained with reference to the Functional Wellbeing Approach (Vittersø, 2013), which +<br/>argues that some moment-to-moment feelings are non-evaluative in the sense of being +<br/>generated directly by the difficulty of an activity. By contrast, retrospective emotional +<br/>feelings are more complex as they include an evaluation of the overall goals and values +<br/>associated with the activity as a whole. +<br/>Keywords: emotions, facial expression, moment-to-moment, functional wellbeing approach, extreme sport, +<br/>backcountry skiing +<br/>INTRODUCTION +<br/>We engage in recreational activities in order to feel good. This pursuit is not restricted to +<br/>leisure activities like sunbathing at the beach or enjoying a fine meal with friends and family. +<br/>Mountaineers, BASE jumpers, and other extreme athletes also claim that the importance of their +<br/>favorite activities is the experience of positive feelings (Brymer, 2005; Willig, 2008; Brown and +<br/>Fraser, 2009; Hetland and Vittersø, 2012). But what exactly is it that feels so good about these +<br/>vigorous and exhausting activities, often referred to as extreme sport? To explore this question, +<br/>we developed a new way of measuring emotions in real time during the activity. We equipped +<br/>the participants with a camera that captured their facially expressed emotion while skiing. These +<br/>films were then analyzed with software for automatic coding of facial expressions and compared +<br/>the participants self-reported emotions assessed in retrospect. This approach enabled us to explore +<br/>long standing questions as to how such positive experiences are created. Are they a result of a series +<br/>of online positive feelings? Or is it the impact of a few central features like intensity peaks, rapid +<br/>emotional changes, and happy endings that create them? Is it the experience of flow? Or is it the +<br/>feeling of mastery that kicks in only after the activity has been successfully accomplished? +<br/>Edited by: +<br/>Eric Brymer, +<br/><b>Leeds Beckett University</b><br/>United Kingdom +<br/>Reviewed by: +<br/>Michael Banissy, +<br/><b>Goldsmiths, University of London</b><br/>United Kingdom +<br/>Ralf Christopher Buckley, +<br/><b>Grif th University, Australia</b><br/>*Correspondence: +<br/>Specialty section: +<br/>This article was submitted to +<br/>Movement Science and Sport +<br/>Psychology, +<br/>a section of the journal +<br/>Frontiers in Psychology +<br/>Received: 26 September 2017 +<br/>Accepted: 25 May 2018 +<br/>Published: 20 June 2018 +<br/>Citation: +<br/>Hetland A, Vittersø J, Wie SOB, +<br/>Kjelstrup E, Mittner M and Dahl TI +<br/>(2018) Skiing and Thinking About It: +<br/>Moment-to-Moment +<br/>and Retrospective Analysis +<br/>of Emotions in an Extreme Sport. +<br/>Front. Psychol. 9:971. +<br/>doi: 10.3389/fpsyg.2018.00971 +<br/>Frontiers in Psychology | www.frontiersin.org +<br/>June 2018 | Volume 9 | Article 971 +</td><td>('50814786', 'Audun Hetland', 'audun hetland')<br/>('2956586', 'Joar Vittersø', 'joar vittersø')<br/>('50823709', 'Simen Oscar Bø Wie', 'simen oscar bø wie')<br/>('50829546', 'Eirik Kjelstrup', 'eirik kjelstrup')<br/>('4281140', 'Matthias Mittner', 'matthias mittner')<br/>('50814786', 'Audun Hetland', 'audun hetland')</td><td>audun.hetland@uit.no +</td></tr><tr><td>7e0c75ce731131e613544e1a85ae0f2c28ee4c1f</td><td><b>Imperial College London</b><br/>Department of Computing <br/>Regression-based Estimation of Pain and <br/>Facial Expression Intensity <br/>June, 2015 <br/>Submitted in part fulfilment of the requirements for the degree of PhD in Computing and <br/><b>the Diploma of Imperial College London. This thesis is entirely my own work, and, except</b><br/>where otherwise indicated, describes my own research. -</td><td>('3291812', 'Sebastian Kaltwang', 'sebastian kaltwang')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>7e1ea2679a110241ed0dd38ff45cd4dfeb7a8e83</td><td>Extensions of Hierarchical Slow Feature +</td><td>('3291812', 'Sebastian Kaltwang', 'sebastian kaltwang')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>7ef44b7c2b5533d00001ae81f9293bdb592f1146</td><td>No d’ordre : 227-2013 +<br/>Anne 2013 +<br/>THESE DE L’UNIVERSITE DE LYON +<br/>Dlivre par +<br/>L’UNIVERSITE CLAUDE BERNARD - LYON 1 +<br/>Ecole Doctorale Informatique et Mathmatiques +<br/>P H D T H E S I S +<br/>D´etection des ´emotions `a partir de vid´eos dans un +<br/>environnement non contrˆol´e +<br/>Detection of emotions from video in non-controlled environment +<br/>Soutenue publiquement (Public defense) le 14/11/2013 +<br/>Composition du jury (Dissertation committee): +<br/>Rapporteurs +<br/>Mr. Renaud SEGUIER +<br/>Mr. Jean-Claude MARTIN +<br/>Examinateurs +<br/>Mr. Thomas MOESLUND +<br/>Mr. Patrick LAMBERT +<br/>Mr. Samir GARBAYA +<br/>Directeur +<br/>Mme. Saida BOUAKAZ +<br/>Co-encadrant +<br/>Mr. Alexandre MEYER +<br/>Mr. Hubert KONIK +<br/>Professor, Supelec, CNRS UMR 6164, Rennes, France +<br/>Professor, LIMSI-CNRS, Universit´e Paris-Sud, France +<br/>Professor, Department of Architecture, Design and Media Technology, +<br/><b>Aalborg University, Denmark</b><br/>Professor, LISTIC - Polytech Annecy-Chambery, France +<br/>Associate Professor, Le2i, ENSAM, Chalon sur Saone, France +<br/>Professor, LIRIS-CNRS, Universit´e Claude Bernard Lyon 1, France +<br/>Associate Professor, LIRIS, Universit´e Claude Bernard Lyon 1, France +<br/>Associate Professor, LaHC, Universit´e Jean Monnet, Saint-Etienne, France +</td><td>('1943666', 'Rizwan Ahmed Khan', 'rizwan ahmed khan')</td><td></td></tr><tr><td>7e1ea2679a110241ed0dd38ff45cd4dfeb7a8e83</td><td>Extensions of Hierarchical Slow Feature <br/>Analysis for Efficient Classification and <br/>Regression on High-Dimensional Data <br/>Dissertation @@ -17070,7 +21737,9 @@ <br/>‡Department of Electrical Engineering <br/><b>California Institute of Technology</b></td><td>('2367820', 'Catherine Wah', 'catherine wah')<br/>('3251767', 'Steve Branson', 'steve branson')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>{cwah,sbranson,sjb}@cs.ucsd.edu <br/>perona@caltech.edu -</td></tr><tr><td>10ab1b48b2a55ec9e2920a5397febd84906a7769</td><td></td><td></td><td></td></tr><tr><td>10ce3a4724557d47df8f768670bfdd5cd5738f95</td><td>Fihe igh Fie +</td></tr><tr><td>10ab1b48b2a55ec9e2920a5397febd84906a7769</td><td></td><td></td><td></td></tr><tr><td>10af69f11301679b6fbb23855bf10f6af1f3d2e6</td><td>Beyond Gaussian Pyramid: Multi-skip Feature Stacking for Action Recognition +<br/><b>School of Computer Science, Carnegie Mellon University</b></td><td>('46329993', 'Ming Lin', 'ming lin')<br/>('2314980', 'Xuanchong Li', 'xuanchong li')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')<br/>('1681921', 'Bhiksha Raj', 'bhiksha raj')</td><td>lanzhzh, minglin, xcli, alex, bhiksha@cs.cmu.edu +</td></tr><tr><td>10ce3a4724557d47df8f768670bfdd5cd5738f95</td><td>Fihe igh Fie <br/>Ac e ad <br/>Ra <br/>The Rbic i e Caegie e @@ -17126,7 +21795,13 @@ </td></tr><tr><td>102b968d836177f9c436141e382915a4f8549276</td><td>Affective Multimodal Human-Computer Interaction <br/><b>Faculty of EEMCS, Delft University of Technology, The Netherlands</b><br/><b>Faculty of Science, University of Amsterdam, The Netherlands</b><br/><b>Psychology and Psychiatry, University of Pittsburgh, USA</b><br/><b>Beckman Institute, University of Illinois at Urbana-Champaign, USA</b></td><td>('1694605', 'Maja Pantic', 'maja pantic')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td>mpantic@ieee.org, nicu@science.uva.nl, jeffcohn@pitt.edu, huang@ifp.uiuc.edu </td></tr><tr><td>100641ed8a5472536dde53c1f50fa2dd2d4e9be9</td><td>Visual Attributes for Enhanced Human-Machine Communication* -</td><td>('1713589', 'Devi Parikh', 'devi parikh')</td><td></td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td></td><td></td><td></td></tr><tr><td>10e704c82616fb5d9c48e0e68ee86d4f83789d96</td><td></td><td></td><td></td></tr><tr><td>106732a010b1baf13c61d0994552aee8336f8c85</td><td>Expanded Parts Model for Semantic Description +</td><td>('1713589', 'Devi Parikh', 'devi parikh')</td><td></td></tr><tr><td>10195a163ab6348eef37213a46f60a3d87f289c5</td><td></td><td></td><td></td></tr><tr><td>10e704c82616fb5d9c48e0e68ee86d4f83789d96</td><td></td><td></td><td></td></tr><tr><td>101569eeef2cecc576578bd6500f1c2dcc0274e2</td><td>Multiaccuracy: Black-Box Post-Processing for Fairness in +<br/>Classification +<br/>James Zou +</td><td>('40102677', 'Michael P. Kim', 'michael p. kim')<br/>('27316199', 'Amirata Ghorbani', 'amirata ghorbani')</td><td>mpk@cs.stanford.edu +<br/>amiratag@stanford.edu +<br/>jamesz@stanford.edu +</td></tr><tr><td>106732a010b1baf13c61d0994552aee8336f8c85</td><td>Expanded Parts Model for Semantic Description <br/>of Humans in Still Images </td><td>('2515597', 'Gaurav Sharma', 'gaurav sharma')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>10e70a34d56258d10f468f8252a7762950830d2b</td><td></td><td></td><td></td></tr><tr><td>102b27922e9bd56667303f986404f0e1243b68ab</td><td>Wang et al. Appl Inform (2017) 4:13 <br/>DOI 10.1186/s40535-017-0042-5 @@ -17148,10 +21823,22 @@ <br/>*Faculty of Computer Science & Information Systems, Universiti Teknologi Malaysia (UTM) , 81310 <br/>Skudai, Johor, Malaysia. </td><td>('1731121', 'Dzulkifli Mohamad', 'dzulkifli mohamad')<br/>('1921146', 'M. Othman', 'm. othman')</td><td> 1dzul@fsksm.utm.my, faisal@gmm.fsksm.utm.my, razib@fsksm.utm.my -</td></tr><tr><td>108b2581e07c6b7ca235717c749d45a1fa15bb24</td><td>Using Stereo Matching with General Epipolar +</td></tr><tr><td>101d4cfbd6f8a7a10bd33505e2b183183f1d8770</td><td>The 2013 SESAME Multimedia Event Detection and +<br/>Recounting System +<br/>SRI International (SRI) +<br/><b>University of Amsterdam (UvA</b><br/><b>University of Southern California</b><br/>(USC) +<br/>Cees G.M. Snoek +<br/>Remi Trichet +</td><td>('1764443', 'Robert C. Bolles', 'robert c. bolles')<br/>('40560201', 'J. Brian Burns', 'j. brian burns')<br/>('48804780', 'James A. Herson', 'james a. herson')<br/>('31693932', 'Gregory K. Myers', 'gregory k. myers')<br/>('2594026', 'Stephanie Pancoast', 'stephanie pancoast')<br/>('1746492', 'Julien van Hout', 'julien van hout')<br/>('49966591', 'Julie Wong', 'julie wong')<br/>('3000952', 'AmirHossein Habibian', 'amirhossein habibian')<br/>('1769315', 'Dennis C. Koelma', 'dennis c. koelma')<br/>('3245057', 'Zhenyang Li', 'zhenyang li')<br/>('2690389', 'Masoud Mazloom', 'masoud mazloom')<br/>('37806314', 'Silvia-Laura Pintea', 'silvia-laura pintea')<br/>('1964898', 'Sung Chun Lee', 'sung chun lee')<br/>('1858100', 'Pramod Sharma', 'pramod sharma')<br/>('40559421', 'Chen Sun', 'chen sun')</td><td></td></tr><tr><td>108b2581e07c6b7ca235717c749d45a1fa15bb24</td><td>Using Stereo Matching with General Epipolar <br/>Geometry for 2D Face Recognition <br/>across Pose -</td><td>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('34734622', 'David W. Jacobs', 'david w. jacobs')</td><td></td></tr><tr><td>10d334a98c1e2a9e96c6c3713aadd42a557abb8b</td><td>Scene Text Recognition using Part-based Tree-structured Character Detection +</td><td>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('34734622', 'David W. Jacobs', 'david w. jacobs')</td><td></td></tr><tr><td>106092fafb53e36077eba88f06feecd07b9e78e7</td><td>Attend and Interact: Higher-Order Object Interactions for Video Understanding +<br/><b>Georgia Institute of Technology, 2NEC Laboratories America, 3Georgia Tech Research Institute</b></td><td>('7437104', 'Chih-Yao Ma', 'chih-yao ma')<br/>('2293919', 'Asim Kadav', 'asim kadav')<br/>('50162780', 'Iain Melvin', 'iain melvin')<br/>('1746245', 'Zsolt Kira', 'zsolt kira')<br/>('1775043', 'Hans Peter Graf', 'hans peter graf')</td><td></td></tr><tr><td>103c8eaca2a2176babab2cc6e9b25d48870d6928</td><td>FINDING RELEVANT SEMANTIC CONTENT FOR GROUNDED LANGUAGE LEARNING +<br/>PANNING FOR GOLD: +<br/><b>The University of Texas at Austin</b><br/>Department of Computer Science +<br/>Austin, TX 78712, USA +</td><td>('47514115', 'David L. Chen', 'david l. chen')<br/>('1797655', 'Raymond J. Mooney', 'raymond j. mooney')</td><td>dlcc@cs.utexas.edu and mooney@cs.utexas.edu +</td></tr><tr><td>10d334a98c1e2a9e96c6c3713aadd42a557abb8b</td><td>Scene Text Recognition using Part-based Tree-structured Character Detection <br/>State Key Laboratory of Management and Control for Complex Systems, CASIA, Beijing, China </td><td>('1959339', 'Cunzhao Shi', 'cunzhao shi')<br/>('1683416', 'Chunheng Wang', 'chunheng wang')<br/>('2658590', 'Baihua Xiao', 'baihua xiao')<br/>('1698138', 'Yang Zhang', 'yang zhang')<br/>('39001252', 'Song Gao', 'song gao')<br/>('34539206', 'Zhong Zhang', 'zhong zhang')</td><td>{cunzhao.shi,chunheng.wang,baihua.xiao,yang.zhang,song.gao,zhong.zhang}@ia.ac.cn </td></tr><tr><td>10f66f6550d74b817a3fdcef7fdeba13ccdba51c</td><td>Benchmarking Face Alignment @@ -17286,6 +21973,12 @@ </td><td>('1764724', 'Guoxu Zhou', 'guoxu zhou')<br/>('1747156', 'Andrzej Cichocki', 'andrzej cichocki')<br/>('38741479', 'Yu Zhang', 'yu zhang')</td><td></td></tr><tr><td>198b6beb53e0e61357825d57938719f614685f75</td><td>Vaulted Verification: A Scheme for Revocable Face <br/>Recognition <br/><b>University of Colorado, Colorado Springs</b></td><td>('3035230', 'Michael Wilber', 'michael wilber')</td><td>mwilber@uccs.edu +</td></tr><tr><td>1921795408345751791b44b379f51b7dd54ebfa2</td><td>From Face Recognition to Models of Identity: +<br/>A Bayesian Approach to Learning about +<br/>Unknown Identities from Unsupervised Data +<br/><b>Imperial College London, UK</b><br/>2 Microsoft Research, Cambridge, UK +</td><td>('2388416', 'Sebastian Nowozin', 'sebastian nowozin')</td><td>dc315@imperial.ac.uk +<br/>Sebastian.Nowozin@microsoft.com </td></tr><tr><td>190b3caa2e1a229aa68fd6b1a360afba6f50fde4</td><td></td><td></td><td></td></tr><tr><td>19e0cc41b9f89492b6b8c2a8a58d01b8242ce00b</td><td>W. ZHANG ET AL.: IMPROVING HFR WITH CGAN <br/>Improving Heterogeneous Face Recognition <br/>with Conditional Adversarial Networks @@ -17369,9 +22062,21 @@ </td><td>('3302320', 'Florian Schroff', 'florian schroff')<br/>('2741985', 'Dmitry Kalenichenko', 'dmitry kalenichenko')<br/>('2276542', 'James Philbin', 'james philbin')</td><td>fschroff@google.com <br/>dkalenichenko@google.com <br/>jphilbin@google.com -</td></tr><tr><td>19a9f658ea14701502d169dc086651b1d9b2a8ea</td><td>Structural Models for Face Detection +</td></tr><tr><td>1910f5f7ac81d4fcc30284e88dee3537887acdf3</td><td> Volume 6, Issue 5, May 2016 ISSN: 2277 128X +<br/>International Journal of Advanced Research in +<br/> Computer Science and Software Engineering +<br/> Research Paper +<br/> Available online at: www.ijarcsse.com +<br/>Semantic Based Hypergraph Reranking Model for Web +<br/>Image Search +<br/>1, 2, 3, 4 B. E. Dept of CSE, 5 Asst. Prof. Dept of CSE +<br/><b>Dr.D.Y.Patil College of Engineering, Pune, Maharashtra, India</b></td><td></td><td></td></tr><tr><td>19a9f658ea14701502d169dc086651b1d9b2a8ea</td><td>Structural Models for Face Detection <br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition <br/><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>('1721677', 'Junjie Yan', 'junjie yan')<br/>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1716143', 'Dong Yi', 'dong yi')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{jjyan,xczhang,zlei,dyi,szli}@nlpr.ia.ac.cn +</td></tr><tr><td>197c64c36e8a9d624a05ee98b740d87f94b4040c</td><td>Regularized Greedy Column Subset Selection +<br/>aDepartment of Computer Systems, Universidad Polit´ecnica de Madrid +<br/>bDepartment of Applied Mathematics, Universidad Polit´ecnica de Madrid +</td><td>('1858768', 'Alberto Mozo', 'alberto mozo')</td><td>*bruno.ordozgoiti@upm.es </td></tr><tr><td>19d4855f064f0d53cb851e9342025bd8503922e2</td><td>Learning SURF Cascade for Fast and Accurate Object Detection <br/>Intel Labs China </td><td>('35423937', 'Jianguo Li', 'jianguo li')<br/>('2470865', 'Yimin Zhang', 'yimin zhang')</td><td></td></tr><tr><td>19d3b02185ad36fb0b792f2a15a027c58ac91e8e</td><td>Im2Text: Describing Images Using 1 Million @@ -17475,7 +22180,7 @@ </td></tr><tr><td>4c87aafa779747828054cffee3125fcea332364d</td><td>View-Constrained Latent Variable Model <br/>for Multi-view Facial Expression Classification <br/><b>Imperial College London, UK</b><br/><b>EEMCS, University of Twente, The Netherlands</b></td><td>('2308430', 'Stefanos Eleftheriadis', 'stefanos eleftheriadis')<br/>('1729713', 'Ognjen Rudovic', 'ognjen rudovic')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td>{s.eleftheriadis,o.rudovic,m.pantic}@imperial.ac.uk -</td></tr><tr><td>4cdae53cebaeeebc3d07cf6cd36fecb2946f3e56</td><td>Photorealistic Facial Texture Inference Using Deep Neural Networks +</td></tr><tr><td>4c29e1f31660ba33e46d7e4ffdebb9b8c6bd5adc</td><td></td><td></td><td></td></tr><tr><td>4cdae53cebaeeebc3d07cf6cd36fecb2946f3e56</td><td>Photorealistic Facial Texture Inference Using Deep Neural Networks <br/>*Pinscreen <br/><b>University of Southern California</b><br/><b>USC Institute for Creative Technologies</b><br/>Figure 1: We present an inference framework based on deep neural networks for synthesizing photorealistic facial texture <br/>along with 3D geometry from a single unconstrained image. We can successfully digitize historic figures that are no longer @@ -17499,7 +22204,19 @@ </td><td>('2121584', 'Wangjiang Zhu', 'wangjiang zhu')<br/>('1748341', 'Jie Hu', 'jie hu')<br/>('1687740', 'Gang Sun', 'gang sun')<br/>('2032273', 'Xudong Cao', 'xudong cao')<br/>('40612284', 'Yu Qiao', 'yu qiao')</td><td></td></tr><tr><td>4c815f367213cc0fb8c61773cd04a5ca8be2c959</td><td>978-1-4244-4296-6/10/$25.00 ©2010 IEEE <br/>2470 <br/>ICASSP 2010 -</td><td></td><td></td></tr><tr><td>4c6233765b5f83333f6c675d3389bbbf503805e3</td><td>Real-time High Performance Deformable Model for Face Detection in the Wild +</td><td></td><td></td></tr><tr><td>4ccf64fc1c9ca71d6aefdf912caf8fea048fb211</td><td>Light-weight Head Pose Invariant Gaze Tracking +<br/><b>University of Maryland</b><br/>NVIDIA +<br/>NVIDIA +</td><td>('48467498', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('24817039', 'Shalini De Mello', 'shalini de mello')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td>rranjan1@umiacs.umd.edu +<br/>shalinig@nvidia.com +<br/>jkautz@nvidia.com +</td></tr><tr><td>4cdb6144d56098b819076a8572a664a2c2d27f72</td><td>Face Synthesis for Eyeglass-Robust Face +<br/>Recognition +<br/><b>CBSRandNLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('46220439', 'Jianzhu Guo', 'jianzhu guo')<br/>('8362374', 'Xiangyu Zhu', 'xiangyu zhu')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{jianzhu.guo,xiangyu.zhu,zlei,szli}@nlpr.ia.ac.cn +</td></tr><tr><td>4c4e49033737467e28aa2bb32f6c21000deda2ef</td><td>Improving Landmark Localization with Semi-Supervised Learning +<br/><b>MILA-University of Montreal, 2NVIDIA, 3Ecole Polytechnique of Montreal, 4CIFAR, 5Facebook AI Research</b></td><td>('25056820', 'Sina Honari', 'sina honari')<br/>('2824500', 'Pavlo Molchanov', 'pavlo molchanov')<br/>('2342481', 'Stephen Tyree', 'stephen tyree')<br/>('1707326', 'Pascal Vincent', 'pascal vincent')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td>1{honaris, vincentp}@iro.umontreal.ca, +<br/>2{pmolchanov, styree, jkautz}@nvidia.com, 3christopher.pal@polymtl.ca +</td></tr><tr><td>4c6233765b5f83333f6c675d3389bbbf503805e3</td><td>Real-time High Performance Deformable Model for Face Detection in the Wild <br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition <br/><b>Institute of Automation, Chinese Academy of Sciences, China</b></td><td>('1721677', 'Junjie Yan', 'junjie yan')<br/>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{jjyan,xczhang,zlei,szli}@nlpr.ia.ac.cn </td></tr><tr><td>4c078c2919c7bdc26ca2238fa1a79e0331898b56</td><td>Unconstrained Facial Landmark Localization with Backbone-Branches @@ -17564,12 +22281,33 @@ <br/>IIIT-Delhi, India </td><td>('2559473', 'Himanshu S. Bhatt', 'himanshu s. bhatt')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td></td></tr><tr><td>264a84f4d27cd4bca94270620907cffcb889075c</td><td>Deep Motion Features for Visual Tracking <br/><b>Computer Vision Laboratory, Link oping University, Sweden</b></td><td>('8161428', 'Susanna Gladh', 'susanna gladh')<br/>('2488938', 'Martin Danelljan', 'martin danelljan')<br/>('2358803', 'Fahad Shahbaz Khan', 'fahad shahbaz khan')<br/>('2228323', 'Michael Felsberg', 'michael felsberg')</td><td></td></tr><tr><td>26d407b911d1234e8e3601e586b49316f0818c95</td><td>[POSTER] Feasibility of Corneal Imaging for Handheld Augmented Reality -<br/><b>Coburg University</b></td><td>('37101400', 'Daniel Schneider', 'daniel schneider')<br/>('2708269', 'Jens Grubert', 'jens grubert')</td><td></td></tr><tr><td>26a72e9dd444d2861298d9df9df9f7d147186bcd</td><td>DOI 10.1007/s00138-016-0768-4 +<br/><b>Coburg University</b></td><td>('37101400', 'Daniel Schneider', 'daniel schneider')<br/>('2708269', 'Jens Grubert', 'jens grubert')</td><td></td></tr><tr><td>26a44feb7a64db7986473ca801c251aa88748477</td><td>Journal of Machine Learning Research 1 () +<br/>Submitted ; Published +<br/>Unsupervised Learning of Gaussian Mixture Models with a +<br/>Uniform Background Component +<br/>Department of Statistics +<br/><b>Florida State University</b><br/>Tallahassee, FL 32306-4330, USA +<br/>Department of Statistics +<br/><b>Florida State University</b><br/>Tallahassee, FL 32306-4330, USA +<br/>Editor: +</td><td>('2761870', 'Sida Liu', 'sida liu')<br/>('2455529', 'Adrian Barbu', 'adrian barbu')</td><td>sida.liu@stat.fsu.edu +<br/>abarbu@stat.fsu.edu +</td></tr><tr><td>264f7ab36ff2e23a1514577a6404229d7fe1242b</td><td>Facial Expression Recognition by De-expression Residue Learning +<br/>Department of Computer Science +<br/><b>State University of New York at Binghamton, USA</b></td><td>('2671017', 'Huiyuan Yang', 'huiyuan yang')<br/>('8072251', 'Lijun Yin', 'lijun yin')</td><td>{hyang51, uciftci}@binghamton.edu; lijun@cs.binghamton.edu +</td></tr><tr><td>26a72e9dd444d2861298d9df9df9f7d147186bcd</td><td>DOI 10.1007/s00138-016-0768-4 <br/>ORIGINAL PAPER <br/>Collecting and annotating the large continuous action dataset <br/>Received: 18 June 2015 / Revised: 18 April 2016 / Accepted: 22 April 2016 / Published online: 21 May 2016 <br/>© The Author(s) 2016. This article is published with open access at Springerlink.com -</td><td>('2089428', 'Daniel Paul Barrett', 'daniel paul barrett')</td><td></td></tr><tr><td>265af79627a3d7ccf64e9fe51c10e5268fee2aae</td><td>1817 +</td><td>('2089428', 'Daniel Paul Barrett', 'daniel paul barrett')</td><td></td></tr><tr><td>266766818dbc5a4ca1161ae2bc14c9e269ddc490</td><td>Article +<br/>Boosting a Low-Cost Smart Home Environment with +<br/>Usage and Access Control Rules +<br/><b>Institute of Information Science and Technologies of CNR (CNR-ISTI)-Italy, 56124 Pisa, Italy</b><br/>Received: 27 April 2018; Accepted: 31 May 2018; Published: 8 June 2018 +</td><td>('1773887', 'Paolo Barsocchi', 'paolo barsocchi')<br/>('38567341', 'Antonello Calabrò', 'antonello calabrò')<br/>('1693901', 'Erina Ferro', 'erina ferro')<br/>('2209975', 'Claudio Gennaro', 'claudio gennaro')<br/>('1709783', 'Eda Marchetti', 'eda marchetti')<br/>('2508924', 'Claudio Vairo', 'claudio vairo')</td><td>antonello.calabro@isti.cnr.it (A.C.); erina.ferro@isti.cnr.it (E.F.); claudio.gennaro@isti.cnr.it (C.G.); +<br/>eda.marchetti@isti.cnr.it (E.M.); claudio.vairo@isti.cnr.it (C.V.) +<br/>* Correspondence: paolo.barsocchi@isti.cnr.it; Tel.: +39-050-315-2965 +</td></tr><tr><td>265af79627a3d7ccf64e9fe51c10e5268fee2aae</td><td>1817 <br/>A Mixture of Transformed Hidden Markov <br/>Models for Elastic Motion Estimation </td><td>('1932096', 'Huijun Di', 'huijun di')<br/>('3265275', 'Linmi Tao', 'linmi tao')<br/>('1797002', 'Guangyou Xu', 'guangyou xu')</td><td></td></tr><tr><td>267c6e8af71bab68547d17966adfaab3b4711e6b</td><td></td><td></td><td></td></tr><tr><td>26af867977f90342c9648ccf7e30f94470d40a73</td><td>IJIRST –International Journal for Innovative Research in Science & Technology| Volume 3 | Issue 04 | September 2016 @@ -17705,7 +22443,13 @@ <br/>IPEDR vol.37 (2012) © (2012) IACSIT Press, Singapore <br/>Innovative Assessment Technologies: Comparing ‘Face-to-Face’ and <br/>Game-Based Development of Thinking Skills in Classroom Settings -<br/><b>University of Szeged, 2 E tv s Lor nd University</b></td><td>('39201903', 'Gyöngyvér Molnár', 'gyöngyvér molnár')<br/>('32197908', 'András Lőrincz', 'andrás lőrincz')</td><td></td></tr><tr><td>2654ef92491cebeef0997fd4b599ac903e48d07a</td><td>Facial Expression Recognition from Near-Infrared Video Sequences +<br/><b>University of Szeged, 2 E tv s Lor nd University</b></td><td>('39201903', 'Gyöngyvér Molnár', 'gyöngyvér molnár')<br/>('32197908', 'András Lőrincz', 'andrás lőrincz')</td><td></td></tr><tr><td>26e570049aaedcfa420fc8c7b761bc70a195657c</td><td>J Sign Process Syst +<br/>DOI 10.1007/s11265-017-1276-0 +<br/>Hybrid Facial Regions Extraction for Micro-expression +<br/>Recognition System +<br/>Received: 2 February 2016 / Revised: 20 October 2016 / Accepted: 10 August 2017 +<br/>© Springer Science+Business Media, LLC 2017 +</td><td>('39888137', 'Sze-Teng Liong', 'sze-teng liong')<br/>('2339975', 'John See', 'john see')<br/>('37809010', 'Su-Wei Tan', 'su-wei tan')</td><td></td></tr><tr><td>2654ef92491cebeef0997fd4b599ac903e48d07a</td><td>Facial Expression Recognition from Near-Infrared Video Sequences <br/>1. Machine Vision Group, Infotech Oulu and Department of Electrical and Information <br/>Engineering, <br/><b>P. O. Box 4500 FI-90014 University of Oulu, Finland</b><br/><b>Institute of Automation, Chinese Academy of Sciences</b><br/>P. O. Box 95 Zhongguancun Donglu, Beijing 100080, China @@ -17836,6 +22580,12 @@ <br/>Verification, and Attribute Estimation <br/><b>Columbia University</b><br/><b>Columbia University</b></td><td>('1778562', 'Thomas Berg', 'thomas berg')<br/>('1767767', 'Peter N. Belhumeur', 'peter n. belhumeur')</td><td>tberg@cs.columbia.edu <br/>belhumeur@cs.columbia.edu +</td></tr><tr><td>2135a3d9f4b8f5771fa5fc7c7794abf8c2840c44</td><td>Lessons from Collecting a Million Biometric Samples +<br/><b>University of Notre Dame</b><br/>Notre Dame, IN 46556, USA +<br/><b>National Institute of Standards and Technology</b><br/>Gaithersburg, MD 20899, USA +</td><td>('1704876', 'Patrick J. Flynn', 'patrick j. flynn')<br/>('1799014', 'Kevin W. Bowyer', 'kevin w. bowyer')<br/>('32028519', 'P. Jonathon Phillips', 'p. jonathon phillips')</td><td>flynn@cse.nd.edu +<br/>kwb@cse.nd.edu +<br/>jonathon@nist.gov </td></tr><tr><td>210b98394c3be96e7fd75d3eb11a391da1b3a6ca</td><td>Spatiotemporal Derivative Pattern: A Dynamic <br/>Texture Descriptor for Video Matching <br/>Saeed Mian3 @@ -17857,6 +22607,10 @@ <br/>Feira de Santana, Brazil </td><td>('2009399', 'Igor L. O. Bastos', 'igor l. o. bastos')<br/>('3057269', 'Michele F. Angelo', 'michele f. angelo')<br/>('2563043', 'Angelo C. Loula', 'angelo c. loula')</td><td>igorcrexito@gmail.com <br/>mfangelo@uefs.ecomp.br, angelocl@gmail.com +</td></tr><tr><td>212608e00fc1e8912ff845ee7a4a67f88ba938fc</td><td>Coupled Deep Learning for Heterogeneous Face Recognition +<br/>Center for Research on Intelligent Perception and Computing (CRIPAC), +<br/>National Laboratory of Pattern Recognition (NLPR), +<br/><b>Institute of Automation, Chinese Academy of Sciences, Beijing, P. R. China</b></td><td>('2225749', 'Xiang Wu', 'xiang wu')<br/>('3051419', 'Lingxiao Song', 'lingxiao song')<br/>('1705643', 'Ran He', 'ran he')<br/>('1688870', 'Tieniu Tan', 'tieniu tan')</td><td>alfredxiangwu@gmail.com, {lingxiao.song, rhe, tnt}@nlpr.ia.ac.cn </td></tr><tr><td>4d49c6cff198cccb21f4fa35fd75cbe99cfcbf27</td><td>Topological Principal Component Analysis for <br/>face encoding and recognition <br/>Juan J. Villanueva @@ -17887,7 +22641,11 @@ <br/>1 Computer Vision Center, Campus UAB, Edifici O, Bellaterra, Barcelona, Spain <br/><b>Dep. of Applied Mathematics and Analysis, University of Barcelona, Spain</b><br/>http://www.cvc.uab.es, http://www.maia.ub.es </td><td>('7629833', 'Pierluigi Casale', 'pierluigi casale')<br/>('9783922', 'Oriol Pujol', 'oriol pujol')<br/>('1724155', 'Petia Radeva', 'petia radeva')</td><td>pierluigi@cvc.uab.es -</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td></td><td></td><td></td></tr><tr><td>4dd6d511a8bbc4d9965d22d79ae6714ba48c8e41</td><td></td><td></td><td></td></tr><tr><td>4de757faa69c1632066391158648f8611889d862</td><td>International Journal of Advanced Engineering Research and Science (IJAERS) Vol-3, Issue-3 , March- 2016] +</td></tr><tr><td>4d423acc78273b75134e2afd1777ba6d3a398973</td><td></td><td></td><td></td></tr><tr><td>4db9e5f19366fe5d6a98ca43c1d113dac823a14d</td><td>Combining Crowdsourcing and Face Recognition to Identify Civil War Soldiers +<br/>Are 1,000 Features Worth A Picture? +<br/>Department of Computer Science and Center for Human-Computer Interaction +<br/>Virginia Tech, Arlington, VA, USA +</td><td>('32698591', 'Vikram Mohanty', 'vikram mohanty')<br/>('51219402', 'David Thames', 'david thames')<br/>('2427623', 'Kurt Luther', 'kurt luther')</td><td></td></tr><tr><td>4dd6d511a8bbc4d9965d22d79ae6714ba48c8e41</td><td></td><td></td><td></td></tr><tr><td>4de757faa69c1632066391158648f8611889d862</td><td>International Journal of Advanced Engineering Research and Science (IJAERS) Vol-3, Issue-3 , March- 2016] <br/>ISSN: 2349-6495 <br/>Review of Face Recognition Technology Using <br/>Feature Fusion Vector @@ -17895,7 +22653,9 @@ </td><td></td><td></td></tr><tr><td>4dd71a097e6b3cd379d8c802460667ee0cbc8463</td><td>Real-time Multi-view Facial Landmark Detector <br/>Learned by the Structured Output SVM <br/>1 Center for Machine Perception, Department of Cybernetics, Faculty of Electrical Engineering, Czech -<br/><b>Technical University in Prague, 166 27 Prague 6, Technick a 2 Czech Republic</b><br/><b>National Institute of Informatics, Tokyo, Japan</b></td><td>('39492787', 'Diego Thomas', 'diego thomas')<br/>('1691286', 'Akihiro Sugimoto', 'akihiro sugimoto')</td><td></td></tr><tr><td>4d9c02567e7b9e065108eb83ea3f03fcff880462</td><td>Towards Facial Expression Recognition in the Wild: A New Database and Deep +<br/><b>Technical University in Prague, 166 27 Prague 6, Technick a 2 Czech Republic</b><br/><b>National Institute of Informatics, Tokyo, Japan</b></td><td>('39492787', 'Diego Thomas', 'diego thomas')<br/>('1691286', 'Akihiro Sugimoto', 'akihiro sugimoto')</td><td></td></tr><tr><td>4db0968270f4e7b3fa73e41c50d13d48e20687be</td><td>Fashion Forward: Forecasting Visual Style in Fashion +<br/><b>Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany</b><br/><b>The University of Texas at Austin, 78701 Austin, USA</b></td><td>('2256981', 'Ziad Al-Halah', 'ziad al-halah')<br/>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>{ziad.al-halah, rainer.stiefelhagen}@kit.edu, grauman@cs.utexas.edu +</td></tr><tr><td>4d9c02567e7b9e065108eb83ea3f03fcff880462</td><td>Towards Facial Expression Recognition in the Wild: A New Database and Deep <br/>Recognition System <br/><b>School of Electronics and Information, Northwestern Polytechnical University, China</b></td><td>('3411701', 'Xianlin Peng', 'xianlin peng')<br/>('1917901', 'Zhaoqiang Xia', 'zhaoqiang xia')<br/>('2871379', 'Lei Li', 'lei li')<br/>('4729239', 'Xiaoyi Feng', 'xiaoyi feng')</td><td>pengxl515@163.com, zxia@nwpu.edu.cn, li lei 08@163.com, fengxiao@nwpu.edu.cn </td></tr><tr><td>4d7e1eb5d1afecb4e238ba05d4f7f487dff96c11</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE @@ -17922,6 +22682,12 @@ <br/><b>Rutgers University, Piscataway NJ 08854, USA</b><br/>2 National Laboratory of Pattern Recognition, Chinese Academy of Sciences <br/>Beijing, 100080, China </td><td>('39606160', 'Peng Yang', 'peng yang')<br/>('1734954', 'Qingshan Liu', 'qingshan liu')</td><td>peyang@cs.rutgers.edu +</td></tr><tr><td>4d6ad0c7b3cf74adb0507dc886993e603c863e8c</td><td>Human Activity Recognition Based on Wearable +<br/>Sensor Data: A Standardization of the +<br/>State-of-the-Art +<br/>Smart Surveillance Interest Group, Computer Science Department +<br/>Universidade Federal de Minas Gerais, Brazil +</td><td>('2954974', 'Antonio C. Nazare', 'antonio c. nazare')</td><td>Email: {arturjordao, antonio.nazare, jessicasena, william}@dcc.ufmg.br </td></tr><tr><td>4d16337cc0431cd43043dfef839ce5f0717c3483</td><td>A Scalable and Privacy-Aware IoT Service for Live Video Analytics <br/><b>Carnegie Mellon University</b><br/><b>Carnegie Mellon University</b><br/>Intel Labs <br/>Norman Sadeh @@ -17937,7 +22703,8 @@ <br/>Conference on <br/>Applications of <br/>Computer Vision -</td><td>('1916866', 'Nils Murrugarra-Llerena', 'nils murrugarra-llerena')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td></td></tr><tr><td>4d0ef449de476631a8d107c8ec225628a67c87f9</td><td>© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE +</td><td>('1916866', 'Nils Murrugarra-Llerena', 'nils murrugarra-llerena')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td></td></tr><tr><td>4dca3d6341e1d991c902492952e726dc2a443d1c</td><td>Learning towards Minimum Hyperspherical Energy +<br/><b>Georgia Institute of Technology 2Emory University</b><br/><b>South China University of Technology 4NVIDIA 5Google Brain 6Ant Financial</b></td><td>('36326884', 'Weiyang Liu', 'weiyang liu')<br/>('10035476', 'Rongmei Lin', 'rongmei lin')<br/>('46270580', 'Zhen Liu', 'zhen liu')<br/>('47968201', 'Lixin Liu', 'lixin liu')<br/>('1751019', 'Zhiding Yu', 'zhiding yu')<br/>('47175326', 'Bo Dai', 'bo dai')<br/>('1779453', 'Le Song', 'le song')</td><td></td></tr><tr><td>4d0ef449de476631a8d107c8ec225628a67c87f9</td><td>© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE <br/>must be obtained for all other uses, in any current or future media, including <br/>reprinting/republishing this material for advertising or promotional purposes, <br/>creating new collective works, for resale or redistribution to servers or lists, or @@ -17945,12 +22712,64 @@ <br/>Pre-print of article that appeared at BTAS 2010. <br/>The published article can be accessed from: <br/>http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5634517 +</td><td></td><td></td></tr><tr><td>4d47261b2f52c361c09f7ab96fcb3f5c22cafb9f</td><td>Deep multi-frame face super-resolution +<br/>Evgeniya Ustinova, Victor Lempitsky +<br/>October 17, 2017 </td><td></td><td></td></tr><tr><td>4df3143922bcdf7db78eb91e6b5359d6ada004d2</td><td>Behav Res (2015) 47:1122–1135 <br/>DOI 10.3758/s13428-014-0532-5 <br/>The Chicago face database: A free stimulus set of faces <br/>and norming data <br/>Published online: 13 January 2015 -<br/><b>Psychonomic Society, Inc</b></td><td>('2428798', 'Joshua Correll', 'joshua correll')</td><td></td></tr><tr><td>75fcbb01bc7e53e9de89cb1857a527f97ea532ce</td><td>Detection of Facial Landmarks from Neutral, Happy, +<br/><b>Psychonomic Society, Inc</b></td><td>('2428798', 'Joshua Correll', 'joshua correll')</td><td></td></tr><tr><td>75879ab7a77318bbe506cb9df309d99205862f6c</td><td>Analysis Of Emotion Recognition From Facial +<br/>Expressions Using Spatial And Transform Domain +<br/>Methods +</td><td>('2855399', 'P. Suja', 'p. suja')<br/>('2510426', 'Shikha Tripathi', 'shikha tripathi')</td><td></td></tr><tr><td>7574f999d2325803f88c4915ba8f304cccc232d1</td><td>Transfer Learning For Cross-Dataset Recognition: A Survey +<br/>This paper summarises and analyses the cross-dataset recognition transfer learning techniques with the +<br/>emphasis on what kinds of methods can be used when the available source and target data are presented +<br/>in different forms for boosting the target task. This paper for the first time summarises several transferring +<br/>criteria in details from the concept level, which are the key bases to guide what kind of knowledge to transfer +<br/>between datasets. In addition, a taxonomy of cross-dataset scenarios and problems is proposed according the +<br/>properties of data that define how different datasets are diverged, thereby review the recent advances on +<br/>each specific problem under different scenarios. Moreover, some real world applications and corresponding +<br/>commonly used benchmarks of cross-dataset recognition are reviewed. Lastly, several future directions are +<br/>identified. +<br/>Additional Key Words and Phrases: Cross-dataset, transfer learning, domain adaptation +<br/>1. INTRODUCTION +<br/>It has been explored how human would transfer learning in one context to another +<br/>similar context [Woodworth and Thorndike 1901; Perkins et al. 1992] in the field of +<br/>Psychology and Education. For example, learning to drive a car helps a person later +<br/>to learn more quickly to drive a truck, and learning mathematics prepares students to +<br/>study physics. The machine learning algorithms are mostly inspired by human brains. +<br/>However, most of them require a huge amount of training examples to learn a new +<br/>model from scratch and fail to apply knowledge learned from previous domains or +<br/>tasks. This may be due to that a basic assumption of statistical learning theory is +<br/>that the training and test data are drawn from the same distribution and belong to +<br/>the same task. Intuitively, learning from scratch is not realistic and practical, because +<br/>it violates how human learn things. In addition, manually labelling a large amount +<br/>of data for new domain or task is labour extensive, especially for the modern “data- +<br/>hungry” and “data-driven” learning techniques (i.e. deep learning). However, the big +<br/>data era provides a huge amount available data collected for other domains and tasks. +<br/>Hence, how to use the previously available data smartly for the current task with +<br/>scarce data will be beneficial for real world applications. +<br/>To reuse the previous knowledge for current tasks, the differences between old data +<br/>and new data need to be taken into account. Take the object recognition as an ex- +<br/>ample. As claimed by Torralba and Efros [2011], despite the great efforts of object +<br/>datasets creators, the datasets appear to have strong build-in bias caused by various +<br/>factors, such as selection bias, capture bias, category or label bias, and negative set +<br/>bias. This suggests that no matter how big the dataset is, it is impossible to cover +<br/>the complexity of the real visual world. Hence, the dataset bias needs to be consid- +<br/>ered before reusing data from previous datasets. Pan and Yang [2010] summarise that +<br/>the differences between different datasets can be caused by domain divergence (i.e. +<br/>distribution shift or feature space difference) or task divergence (i.e. conditional dis- +<br/>tribution shift or label space difference), or both. For example, in visual recognition, +<br/>the distributions between the previous and current data can be discrepant due to the +<br/>different environments, lighting, background, sensor types, resolutions, view angles, +<br/>and post-processing. Those external factors may cause the distribution divergence or +<br/>even feature space divergence between different domains. On the other hand, the task +<br/>divergence between current and previous data is also ubiquitous. For example, it is +<br/>highly possible that an animal species that we want to recognize have not been seen +<br/>ACM Journal Name, Vol. V, No. N, Article A, Publication date: January YYYY. +</td><td>('47539715', 'Jing Zhang', 'jing zhang')<br/>('40508657', 'Wanqing Li', 'wanqing li')<br/>('1719314', 'Philip Ogunbona', 'philip ogunbona')</td><td></td></tr><tr><td>75fcbb01bc7e53e9de89cb1857a527f97ea532ce</td><td>Detection of Facial Landmarks from Neutral, Happy, <br/>and Disgust Facial Images <br/>Research Group for Emotions, Sociality, and Computing <br/>Tampere Unit for Computer-Human Interaction @@ -18057,8 +22876,22 @@ <br/>TPAMI, 23(6):681–685, 2001. <br/>[2] Piotr Dollár, Peter Welinder, and Pietro Perona. Cascaded pose regres- <br/>sion. In CVPR, 2010. -</td><td>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td></td></tr><tr><td>75cd81d2513b7e41ac971be08bbb25c63c37029a</td><td></td><td></td><td></td></tr><tr><td>75bf3b6109d7a685236c8589f8ead7d769ea863f</td><td>Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation +</td><td>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td></td></tr><tr><td>75308067ddd3c53721430d7984295838c81d4106</td><td>Article +<br/>Rapid Facial Reactions +<br/>in Response to Facial +<br/>Expressions of Emotion +<br/>Displayed by Real Versus +<br/>Virtual Faces +<br/>i-Perception +<br/>2018 Vol. 9(4), 1–18 +<br/>! The Author(s) 2018 +<br/>DOI: 10.1177/2041669518786527 +<br/>journals.sagepub.com/home/ipe +<br/><b>LIMSI, CNRS, University of Paris-Sud, Orsay, France</b></td><td>('28174013', 'Jean-Claude Martin', 'jean-claude martin')</td><td></td></tr><tr><td>75cd81d2513b7e41ac971be08bbb25c63c37029a</td><td></td><td></td><td></td></tr><tr><td>75bf3b6109d7a685236c8589f8ead7d769ea863f</td><td>Model Selection with Nonlinear Embedding for Unsupervised Domain Adaptation <br/><b>Center for Cognitive Ubiquitous Computing, Arizona State University, Tempe, AZ, USA</b></td><td>('3151995', 'Hemanth Venkateswara', 'hemanth venkateswara')<br/>('2471253', 'Shayok Chakraborty', 'shayok chakraborty')<br/>('1743991', 'Sethuraman Panchanathan', 'sethuraman panchanathan')</td><td>{hemanthv, shayok.chakraborty, troy.mcdaniel, panch}@asu.edu +</td></tr><tr><td>759cf57215fcfdd8f59c97d14e7f3f62fafa2b30</td><td>Real-time Distracted Driver Posture Classification +<br/>Department of Computer Science and Engineering, School of Sciences and Engineering +<br/><b>The American University in Cairo, New Cairo 11835, Egypt</b></td><td>('3434212', 'Yehya Abouelnaga', 'yehya abouelnaga')<br/>('2150605', 'Hesham M. Eraqi', 'hesham m. eraqi')<br/>('2233511', 'Mohamed N. Moustafa', 'mohamed n. moustafa')</td><td>{devyhia,heraqi,m.moustafa}@aucegypt.edu </td></tr><tr><td>751970d4fb6f61d1b94ca82682984fd03c74f127</td><td>Array-based Electromyographic Silent Speech Interface <br/><b>Cognitive Systems Lab, Karlsruhe Institute of Technology, Karlsruhe, Germany</b><br/>Keywords: <br/>EMG, EMG-based Speech Recognition, Silent Speech Interface, Electrode Array @@ -18069,7 +22902,10 @@ <br/><b>University of Oxford</b></td><td>('3056091', 'Mark Everingham', 'mark everingham')<br/>('1782755', 'Josef Sivic', 'josef sivic')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{me,josef,az}@robots.ox.ac.uk </td></tr><tr><td>75e5ba7621935b57b2be7bf4a10cad66a9c445b9</td><td></td><td></td><td></td></tr><tr><td>75859ac30f5444f0d9acfeff618444ae280d661d</td><td>Multibiometric Cryptosystems based on Feature <br/>Level Fusion -</td><td>('2743820', 'Abhishek Nagar', 'abhishek nagar')<br/>('34633765', 'Karthik Nandakumar', 'karthik nandakumar')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>7553fba5c7f73098524fbb58ca534a65f08e91e7</td><td>Available Online at www.ijcsmc.com +</td><td>('2743820', 'Abhishek Nagar', 'abhishek nagar')<br/>('34633765', 'Karthik Nandakumar', 'karthik nandakumar')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>758d7e1be64cc668c59ef33ba8882c8597406e53</td><td>IEEE TRANSACTIONS ON AFFECTIVE COMPUTING +<br/>AffectNet: A Database for Facial Expression, +<br/>Valence, and Arousal Computing in the Wild +</td><td>('2314025', 'Ali Mollahosseini', 'ali mollahosseini')<br/>('3093835', 'Mohammad H. Mahoor', 'mohammad h. mahoor')</td><td></td></tr><tr><td>7553fba5c7f73098524fbb58ca534a65f08e91e7</td><td>Available Online at www.ijcsmc.com <br/>International Journal of Computer Science and Mobile Computing <br/>A Monthly Journal of Computer Science and Information Technology <br/>ISSN 2320–088X @@ -18091,10 +22927,23 @@ <br/>vidit@cs.umass.edu </td></tr><tr><td>75259a613285bdb339556ae30897cb7e628209fa</td><td>Unsupervised Domain Adaptation for Zero-Shot Learning <br/><b>Queen Mary University of London, London E1 4NS, UK</b></td><td>('2999293', 'Elyor Kodirov', 'elyor kodirov')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')</td><td>{e.kodirov, t.xiang, z.fu, s.gong}@qmul.ac.uk +</td></tr><tr><td>754f7f3e9a44506b814bf9dc06e44fecde599878</td><td>Quantized Densely Connected U-Nets for +<br/>Efficient Landmark Localization +</td><td>('2986505', 'Zhiqiang Tang', 'zhiqiang tang')<br/>('4340744', 'Xi Peng', 'xi peng')<br/>('1947101', 'Shijie Geng', 'shijie geng')<br/>('3008832', 'Lingfei Wu', 'lingfei wu')<br/>('1753384', 'Shaoting Zhang', 'shaoting zhang')</td><td>1Rutgers University, {zt53, sg1309, dnm}@rutgers.edu +<br/>2Binghamton University, xpeng@binghamton.edu +<br/>3IBM T. J. Watson, lwu@email.wm.edu +<br/>4SenseTime, zhangshaoting@sensetime.com +</td></tr><tr><td>75249ebb85b74e8932496272f38af274fbcfd696</td><td>Face Identification in Large Galleries +<br/>Smart Surveillance Interest Group, Department of Computer Science +<br/>Universidade Federal de Minas Gerais, Belo Horizonte, Brazil +</td><td>('1679142', 'William Robson Schwartz', 'william robson schwartz')</td><td>rafaelvareto@dcc.ufmg.br, filipe.oc87@gmail.com, william@dcc.ufmg.br </td></tr><tr><td>75d2ecbbcc934563dff6b39821605dc6f2d5ffcc</td><td>Capturing Subtle Facial Motions in 3D Face Tracking <br/><b>Beckman Institute</b><br/><b>University of Illinois at Urbana-Champaign</b><br/>Urbana, IL 61801 </td><td>('1735018', 'Zhen Wen', 'zhen wen')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>{zhenwen, huang}@ifp.uiuc.edu -</td></tr><tr><td>81bfe562e42f2eab3ae117c46c2e07b3d142dade</td><td>A Hajj And Umrah Location Classification System For Video +</td></tr><tr><td>81a142c751bf0b23315fb6717bc467aa4fdfbc92</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE +<br/>1767 +<br/>ICASSP 2017 +</td><td></td><td></td></tr><tr><td>81bfe562e42f2eab3ae117c46c2e07b3d142dade</td><td>A Hajj And Umrah Location Classification System For Video <br/>Crowded Scenes <br/>Adnan A. Gutub† <br/><b>Center of Research Excellence in Hajj and Umrah, Umm Al-Qura University, Makkah, KSA</b><br/><b>College of Computers and Information Systems, Umm Al-Qura University, Makkah, KSA</b></td><td>('2872536', 'Hossam M. Zawbaa', 'hossam m. zawbaa')<br/>('1977955', 'Salah A. Aly', 'salah a. aly')</td><td></td></tr><tr><td>81695fbbbea2972d7ab1bfb1f3a6a0dbd3475c0f</td><td><b>UNIVERSITY OF TARTU</b><br/>FACULTY OF SCIENCE AND TECHNOLOGY @@ -18108,7 +22957,12 @@ <br/>A Robust Quadratic Criterion <br/>Stella X. Yu, Member, <br/>IEEE -</td><td></td><td></td></tr><tr><td>816bd8a7f91824097f098e4f3e0f4b69f481689d</td><td>Latent Semantic Analysis of Facial Action Codes +</td><td></td><td></td></tr><tr><td>8199803f476c12c7f6c0124d55d156b5d91314b6</td><td>The iNaturalist Species Classification and Detection Dataset +<br/>1Caltech +<br/>2Google +<br/>3Cornell Tech +<br/>4iNaturalist +</td><td>('2996914', 'Grant Van Horn', 'grant van horn')<br/>('13412044', 'Alex Shepard', 'alex shepard')<br/>('1690922', 'Pietro Perona', 'pietro perona')<br/>('50172592', 'Serge Belongie', 'serge belongie')</td><td></td></tr><tr><td>816bd8a7f91824097f098e4f3e0f4b69f481689d</td><td>Latent Semantic Analysis of Facial Action Codes <br/>for Automatic Facial Expression Recognition <br/>D-ITET/BIWI <br/>ETH Zurich @@ -18118,7 +22972,17 @@ </td><td>('8745904', 'Beat Fasel', 'beat fasel')<br/>('1824057', 'Florent Monay', 'florent monay')<br/>('1698682', 'Daniel Gatica-Perez', 'daniel gatica-perez')</td><td>bfasel@vision.ee.ethz.ch <br/>monay@idiap.ch <br/>gatica@idiap.ch -</td></tr><tr><td>81831ed8e5b304e9d28d2d8524d952b12b4cbf55</td><td></td><td></td><td></td></tr><tr><td>81b2a541d6c42679e946a5281b4b9dc603bc171c</td><td>Universit¨at Ulm | 89069 Ulm | Deutschland +</td></tr><tr><td>81706277ed180a92d2eeb94ac0560f7dc591ee13</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 55– No.15, October 2012 +<br/>Emotion based Contextual Semantic Relevance +<br/>Feedback in Multimedia Information Retrieval +<br/>Department of Computer Engineering, Indian +<br/><b>Institute of Technology, Banaras Hindu</b><br/><b>University, Varanasi, 221005, India</b><br/>Anil K. Tripathi +<br/>Department of Computer Engineering, Indian +<br/><b>Institute of Technology, Banaras Hindu</b><br/><b>University, Varanasi, 221005, India</b><br/>to +<br/>find some +<br/>issued by a user +</td><td>('41132883', 'Karm Veer Singh', 'karm veer singh')</td><td></td></tr><tr><td>81831ed8e5b304e9d28d2d8524d952b12b4cbf55</td><td></td><td></td><td></td></tr><tr><td>81b2a541d6c42679e946a5281b4b9dc603bc171c</td><td>Universit¨at Ulm | 89069 Ulm | Deutschland <br/>Fakult¨at f¨ur Ingenieurwissenschaften und Informatik <br/>Institut f¨ur Neuroinformatik <br/>Direktor: Prof. Dr. G¨unther Palm @@ -18143,6 +23007,10 @@ <br/>Institut Mines-Telecom / Telecom SudParis </td><td>('2120042', 'Daniel Wesierski', 'daniel wesierski')<br/>('2603633', 'Patrick Horain', 'patrick horain')</td><td>daniel.wesierski@pg.gda.pl <br/>patrick.horain@telecom-sudaris.eu +</td></tr><tr><td>8164ebc07f51c9e0db4902980b5ac3f5a8d8d48c</td><td>Shuffle-Then-Assemble: Learning +<br/>Object-Agnostic Visual Relationship Features +<br/>School of Computer Science and Engineering, +<br/><b>Nanyang Technological University</b></td><td>('47008946', 'Xu Yang', 'xu yang')<br/>('5462268', 'Hanwang Zhang', 'hanwang zhang')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')</td><td>s170018@e.ntu.edu.sg,{hanwangzhang,asjfcai}@ntu.edu.sg </td></tr><tr><td>81fc86e86980a32c47410f0ba7b17665048141ec</td><td>Segment-based Methods for Facial Attribute <br/>Detection from Partial Faces <br/>Department of Electrical and Computer Engineering and the Center for Automation Research, @@ -18151,7 +23019,11 @@ <br/>Exploiting Discriminant Information in Nonnegative <br/>Matrix Factorization With Application <br/>to Frontal Face Verification -</td><td>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('2336758', 'Ioan Buciu', 'ioan buciu')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td></td></tr><tr><td>816eff5e92a6326a8ab50c4c50450a6d02047b5e</td><td>fLRR: Fast Low-Rank Representation Using +</td><td>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('2336758', 'Ioan Buciu', 'ioan buciu')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td></td></tr><tr><td>814d091c973ff6033a83d4e44ab3b6a88cc1cb66</td><td>Behav Res (2016) 48:567–576 +<br/>DOI 10.3758/s13428-015-0601-4 +<br/>The EU-Emotion Stimulus Set: A validation study +<br/>Published online: 30 September 2015 +<br/><b>Psychonomic Society, Inc</b></td><td>('2625704', 'Delia Pigat', 'delia pigat')<br/>('2391819', 'Shahar Tal', 'shahar tal')<br/>('2100443', 'Ofer Golan', 'ofer golan')<br/>('1884685', 'Simon Baron-Cohen', 'simon baron-cohen')<br/>('3343472', 'Daniel Lundqvist', 'daniel lundqvist')</td><td></td></tr><tr><td>816eff5e92a6326a8ab50c4c50450a6d02047b5e</td><td>fLRR: Fast Low-Rank Representation Using <br/>Frobenius Norm <br/>Low Rank Representation (LRR) intends to find the representation <br/>with lowest-rank of a given data set, which can be formulated as a @@ -18377,13 +23249,15 @@ <br/>National Library of Medicine, NIH, Bethesda, MD </td><td>('1726787', 'Zhiyun Xue', 'zhiyun xue')<br/>('1721328', 'Sameer Antani', 'sameer antani')<br/>('1691151', 'L. Rodney Long', 'l. rodney long')<br/>('1705831', 'Dina Demner-Fushman', 'dina demner-fushman')<br/>('1692057', 'George R. Thoma', 'george r. thoma')</td><td></td></tr><tr><td>86904aee566716d9bef508aa9f0255dc18be3960</td><td>Learning Anonymized Representations with <br/>Adversarial Neural Networks -</td><td>('1743922', 'Pablo Piantanida', 'pablo piantanida')<br/>('1751762', 'Yoshua Bengio', 'yoshua bengio')<br/>('1694313', 'Pierre Duhamel', 'pierre duhamel')</td><td></td></tr><tr><td>867e709a298024a3c9777145e037e239385c0129</td><td> INTERNATIONAL JOURNAL +</td><td>('1743922', 'Pablo Piantanida', 'pablo piantanida')<br/>('1751762', 'Yoshua Bengio', 'yoshua bengio')<br/>('1694313', 'Pierre Duhamel', 'pierre duhamel')</td><td></td></tr><tr><td>86f191616423efab8c0d352d986126a964983219</td><td>Visual to Sound: Generating Natural Sound for Videos in the Wild +<br/><b>University of North Carolina at Chapel Hill, 2Adobe Research</b></td><td>('49455017', 'Yipin Zhou', 'yipin zhou')<br/>('8056043', 'Zhaowen Wang', 'zhaowen wang')<br/>('2442612', 'Chen Fang', 'chen fang')<br/>('30190128', 'Trung Bui', 'trung bui')<br/>('1685538', 'Tamara L. Berg', 'tamara l. berg')</td><td></td></tr><tr><td>867e709a298024a3c9777145e037e239385c0129</td><td> INTERNATIONAL JOURNAL <br/> OF PROFESSIONAL ENGINEERING STUDIES Volume VIII /Issue 2 / FEB 2017 <br/>ANALYTICAL REPRESENTATION OF UNDERSAMPLED FACE <br/>RECOGNITION APPROACH BASED ON DICTIONARY LEARNING <br/>AND SPARSE REPRESENTATION <br/>(M.Tech)1, Assistant Professor2, Assistant Professor3, HOD of CSE Department4 -</td><td>('32628937', 'Murala Sandeep', 'murala sandeep')<br/>('1702980', 'Ranga Reddy', 'ranga reddy')</td><td></td></tr><tr><td>86c5478f21c4a9f9de71b5ffa90f2a483ba5c497</td><td>Kernel Selection using Multiple Kernel Learning and Domain +</td><td>('32628937', 'Murala Sandeep', 'murala sandeep')<br/>('1702980', 'Ranga Reddy', 'ranga reddy')</td><td></td></tr><tr><td>869a2fbe42d3fdf40ed8b768edbf54137be7ac71</td><td>Relative Attributes for Enhanced Human-Machine Communication +<br/><b>Toyota Technological Institute, Chicago</b><br/><b>Indraprastha Institute of Information Technology, Delhi</b><br/><b>University of Texas, Austin</b></td><td>('1713589', 'Devi Parikh', 'devi parikh')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')<br/>('2076800', 'Amar Parkash', 'amar parkash')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td></td></tr><tr><td>86c5478f21c4a9f9de71b5ffa90f2a483ba5c497</td><td>Kernel Selection using Multiple Kernel Learning and Domain <br/>Adaptation in Reproducing Kernel Hilbert Space, for Face <br/>Recognition under Surveillance Scenario <br/><b>Indian Institute of Technology, Madras, Chennai 600036, INDIA</b><br/>Face Recognition (FR) has been the interest to several researchers over the past few decades due to its passive nature of biometric @@ -18494,10 +23368,28 @@ <br/> Pune, India </td><td>('2947776', 'Ayesha Butalia', 'ayesha butalia')</td><td>deepikapatil941@gmail.com <br/>ayeshabutalia@gmail.com +</td></tr><tr><td>86b6afc667bb14ff4d69e7a5e8bb2454a6bbd2cd</td><td>YUE et al.: ATTENTIONAL ALIGNMENT NETWORK +<br/>Attentional Alignment Network +<br/><b>Beihang University, Beijing, China</b><br/>2 The Key Laboratory of Advanced +<br/>Technologies for Near Space +<br/>Information Systems +<br/>Ministry of +<br/>Technology of China +<br/><b>University of Texas at Arlington</b><br/>TX, USA +<br/><b>Shanghai Jiao Tong University</b><br/>Shanghai, China +<br/>Industry and Information +</td><td>('35310815', 'Lei Yue', 'lei yue')<br/>('6050999', 'Xin Miao', 'xin miao')<br/>('3127895', 'Pengbo Wang', 'pengbo wang')<br/>('1740430', 'Baochang Zhang', 'baochang zhang')<br/>('34798935', 'Xiantong Zhen', 'xiantong zhen')<br/>('40916581', 'Xianbin Cao', 'xianbin cao')</td><td>yuelei@buaa.edu.cn +<br/>xin.miao@mavs.uta.edu +<br/>wangpengbo_vincent@sjtu.edu.cn +<br/>bczhang@buaa.edu.cn +<br/>zhenxt@buaa.edu.cn +<br/>xbcao@buaa.edu.cn </td></tr><tr><td>862d17895fe822f7111e737cbcdd042ba04377e8</td><td>Semi-Latent GAN: Learning to generate and modify facial images from <br/>attributes <br/><b>The school of Data Science, Fudan University</b><br/>† Disney Research, </td><td>('11740128', 'Weidong Yin', 'weidong yin')<br/>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')</td><td>yanweifu@fudan.edu.cn +</td></tr><tr><td>86d0127e1fd04c3d8ea78401c838af621647dc95</td><td>Facial Attribute Prediction +<br/><b>College of Information and Engineering, Hunan University, Changsha, China</b><br/><b>School of Computer Science, National University of Defense Technology, Changsha, China</b><br/><b>University of Texas at San Antonio, USA</b></td><td>('48664471', 'Mingxing Duan', 'mingxing duan')<br/>('50842217', 'Qi Tian', 'qi tian')</td><td>duanmingxing16@nudt.edu.cn, lkl@hnu.edu.cn, qi.tian@utsa.edu </td></tr><tr><td>86e1bdbfd13b9ed137e4c4b8b459a3980eb257f6</td><td>The Kinetics Human Action Video Dataset <br/>Jo˜ao Carreira <br/>Paul Natsev @@ -18528,9 +23420,18 @@ </td><td>('1779859', 'Tao Liu', 'tao liu')<br/>('32611393', 'Ying Liu', 'ying liu')<br/>('38837555', 'Cong Li', 'cong li')<br/>('40032263', 'Chao Li', 'chao li')</td><td></td></tr><tr><td>86b105c3619a433b6f9632adcf9b253ff98aee87</td><td>1424403677/06/$20.00 ©2006 IEEE <br/>1013 <br/>ICME 2006 -</td><td></td><td></td></tr><tr><td>86a8b3d0f753cb49ac3250fa14d277983e30a4b7</td><td>Exploiting Unlabeled Ages for Aging Pattern Analysis on A Large Database +</td><td></td><td></td></tr><tr><td>86f3552b822f6af56cb5079cc31616b4035ccc4e</td><td>Towards Miss Universe Automatic Prediction: The Evening Gown Competition +<br/><b>University of Queensland, Brisbane, Australia</b><br/>(cid:5) Data61, CSIRO, Australia +</td><td>('1850202', 'Johanna Carvajal', 'johanna carvajal')<br/>('2331880', 'Arnold Wiliem', 'arnold wiliem')<br/>('1781182', 'Conrad Sanderson', 'conrad sanderson')</td><td></td></tr><tr><td>86a8b3d0f753cb49ac3250fa14d277983e30a4b7</td><td>Exploiting Unlabeled Ages for Aging Pattern Analysis on A Large Database <br/><b>West Virginia University, Morgantown, WV</b></td><td>('1720735', 'Chao Zhang', 'chao zhang')<br/>('1822413', 'Guodong Guo', 'guodong guo')</td><td>cazhang@mix.wvu.edu, guodong.guo@mail.wvu.edu -</td></tr><tr><td>86b51bd0c80eecd6acce9fc538f284b2ded5bcdd</td><td></td><td></td><td></td></tr><tr><td>8699268ee81a7472a0807c1d3b1db0d0ab05f40d</td><td></td><td></td><td></td></tr><tr><td>72282287f25c5419dc6fd9e89ec9d86d660dc0b5</td><td>A Rotation Invariant Latent Factor Model for +</td></tr><tr><td>860588fafcc80c823e66429fadd7e816721da42a</td><td>Unsupervised Discovery of Object Landmarks as Structural Representations +<br/><b>University of Michigan, Ann Arbor</b><br/>2Google Brain +</td><td>('1692992', 'Yuting Zhang', 'yuting zhang')<br/>('1857914', 'Yijie Guo', 'yijie guo')<br/>('50442731', 'Yixin Jin', 'yixin jin')<br/>('49513553', 'Yijun Luo', 'yijun luo')<br/>('46915665', 'Zhiyuan He', 'zhiyuan he')<br/>('1697141', 'Honglak Lee', 'honglak lee')</td><td>{yutingzh, guoyijie, jinyixin, lyjtour, zhiyuan, honglak}@umich.edu +<br/>honglak@google.com +</td></tr><tr><td>86b51bd0c80eecd6acce9fc538f284b2ded5bcdd</td><td></td><td></td><td></td></tr><tr><td>8699268ee81a7472a0807c1d3b1db0d0ab05f40d</td><td></td><td></td><td></td></tr><tr><td>86374bb8d309ad4dbde65c21c6fda6586ae4147a</td><td>Detect-and-Track: Efficient Pose Estimation in Videos +<br/><b>The Robotics Institute, Carnegie Mellon University</b><br/><b>Dartmouth College</b><br/>2Facebook +<br/>https://rohitgirdhar.github.io/DetectAndTrack +</td><td>('3102850', 'Rohit Girdhar', 'rohit girdhar')<br/>('2082991', 'Georgia Gkioxari', 'georgia gkioxari')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')<br/>('2210374', 'Manohar Paluri', 'manohar paluri')</td><td></td></tr><tr><td>869583b700ecf33a9987447aee9444abfe23f343</td><td></td><td></td><td></td></tr><tr><td>72282287f25c5419dc6fd9e89ec9d86d660dc0b5</td><td>A Rotation Invariant Latent Factor Model for <br/>Moveme Discovery from Static Poses <br/><b>California Institute of Technology, Pasadena, CA, USA</b></td><td>('3339867', 'Matteo Ruggero Ronchi', 'matteo ruggero ronchi')<br/>('14834454', 'Joon Sik Kim', 'joon sik kim')<br/>('1740159', 'Yisong Yue', 'yisong yue')</td><td>{mronchi, jkim5, yyue}@caltech.edu </td></tr><tr><td>72a87f509817b3369f2accd7024b2e4b30a1f588</td><td>Fault diagnosis of a railway device using semi-supervised @@ -18558,7 +23459,7 @@ <br/>identification <br/>Received: May 2005 / Accepted: September 2006 / Published online: 30 January 2007 <br/>C(cid:1) Springer Science + Business Media, LLC 2007 -</td><td>('2046854', 'Sinjini Mitra', 'sinjini mitra')</td><td></td></tr><tr><td>726b8aba2095eef076922351e9d3a724bb71cb51</td><td></td><td></td><td></td></tr><tr><td>727ecf8c839c9b5f7b6c7afffe219e8b270e7e15</td><td>LEVERAGING GEO-REFERENCED DIGITAL PHOTOGRAPHS +</td><td>('2046854', 'Sinjini Mitra', 'sinjini mitra')</td><td></td></tr><tr><td>726b8aba2095eef076922351e9d3a724bb71cb51</td><td></td><td></td><td></td></tr><tr><td>721b109970bf5f1862767a1bec3f9a79e815f79a</td><td></td><td></td><td></td></tr><tr><td>727ecf8c839c9b5f7b6c7afffe219e8b270e7e15</td><td>LEVERAGING GEO-REFERENCED DIGITAL PHOTOGRAPHS <br/>A DISSERTATION <br/>SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE <br/>AND THE COMMITTEE ON GRADUATE STUDIES @@ -18573,7 +23474,13 @@ </td><td>('18780812', 'Xiaohua Huang', 'xiaohua huang')<br/>('1757287', 'Guoying Zhao', 'guoying zhao')<br/>('40608983', 'Wenming Zheng', 'wenming zheng')</td><td>{huang.xiaohua,gyzhao,mkp}@ee.oulu.fi <br/>wenming_zheng@seu.edu.cn </td></tr><tr><td>72ecaff8b57023f9fbf8b5b2588f3c7019010ca7</td><td>Facial Keypoints Detection -</td><td>('27744156', 'Shenghao Shi', 'shenghao shi')</td><td></td></tr><tr><td>729dbe38538fbf2664bc79847601f00593474b05</td><td></td><td></td><td></td></tr><tr><td>729a9d35bc291cc7117b924219bef89a864ce62c</td><td>Recognizing Material Properties from Images +</td><td>('27744156', 'Shenghao Shi', 'shenghao shi')</td><td></td></tr><tr><td>72591a75469321074b072daff80477d8911c3af3</td><td>Group Component Analysis for Multi-block Data: +<br/>Common and Individual Feature Extraction +</td><td>('1764724', 'Guoxu Zhou', 'guoxu zhou')<br/>('1747156', 'Andrzej Cichocki', 'andrzej cichocki')<br/>('38741479', 'Yu Zhang', 'yu zhang')</td><td></td></tr><tr><td>7224d58a7e1f02b84994b60dc3b84d9fe6941ff5</td><td>When Face Recognition Meets with Deep Learning: an Evaluation of +<br/>Convolutional Neural Networks for Face Recognition +<br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, UK</b><br/><b>Electronic Engineering and Computer Science, Queen Mary University of London, UK</b><br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition, Chinese Academy of Sciences, China♠ +</td><td>('38819702', 'Guosheng Hu', 'guosheng hu')<br/>('2653152', 'Yongxin Yang', 'yongxin yang')<br/>('1716143', 'Dong Yi', 'dong yi')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{g.hu,j.kittler,w.christmas}@surrey.ac.uk,{yongxin.yang,t.hospedales}@qmul.ac.uk, {szli,dyi}@cbsr.ia.ac.cn +</td></tr><tr><td>729dbe38538fbf2664bc79847601f00593474b05</td><td></td><td></td><td></td></tr><tr><td>729a9d35bc291cc7117b924219bef89a864ce62c</td><td>Recognizing Material Properties from Images </td><td>('40116153', 'Gabriel Schwartz', 'gabriel schwartz')<br/>('1708819', 'Ko Nishino', 'ko nishino')</td><td></td></tr><tr><td>72e10a2a7a65db7ecdc7d9bd3b95a4160fab4114</td><td>Face Alignment using Cascade Gaussian Process Regression Trees <br/><b>Korea Advanced institute of Science and Technology</b><br/>Face alignment is a task to locate fiducial facial landmark points, such as eye <br/>corners, nose tip, mouth corners, and chin, in a face image. Shape regression @@ -18652,7 +23559,10 @@ <br/> 1 Department of Computer Science and Engineering <br/><b>Stamford University Bangladesh, Dhaka-1209, Bangladesh</b><br/>2 Department of Computer Science and Engineering <br/><b>Stamford University Bangladesh, Dhaka-1209, Bangladesh</b><br/>3 Department of Computer Science and Engineering -<br/><b>Stamford University Bangladesh, Dhaka-1209, Bangladesh</b></td><td>('7484236', 'Mohammad Shahidul Islam', 'mohammad shahidul islam')<br/>('7497618', 'Tarin Kazi', 'tarin kazi')</td><td></td></tr><tr><td>72c0c8deb9ea6f59fde4f5043bff67366b86bd66</td><td>Age progression in Human Faces : A Survey +<br/><b>Stamford University Bangladesh, Dhaka-1209, Bangladesh</b></td><td>('7484236', 'Mohammad Shahidul Islam', 'mohammad shahidul islam')<br/>('7497618', 'Tarin Kazi', 'tarin kazi')</td><td></td></tr><tr><td>72cbbdee4f6eeee8b7dd22cea6092c532271009f</td><td>Adversarial Occlusion-aware Face Detection +<br/>1National Laboratory of Pattern Recognition, CASIA +<br/>2Center for Research on Intelligent Perception and Computing, CASIA +<br/><b>University of Chinese Academy of Sciences, Beijing 100190, China</b></td><td>('3065234', 'Yujia Chen', 'yujia chen')<br/>('3051419', 'Lingxiao Song', 'lingxiao song')<br/>('1705643', 'Ran He', 'ran he')</td><td></td></tr><tr><td>721d9c387ed382988fce6fa864446fed5fb23173</td><td></td><td></td><td></td></tr><tr><td>72c0c8deb9ea6f59fde4f5043bff67366b86bd66</td><td>Age progression in Human Faces : A Survey </td><td>('34713849', 'Narayanan Ramanathan', 'narayanan ramanathan')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>721e5ba3383b05a78ef1dfe85bf38efa7e2d611d</td><td>BULAT, TZIMIROPOULOS: CONVOLUTIONAL AGGREGATION OF LOCAL EVIDENCE <br/>Convolutional aggregation of local evidence <br/>for large pose face alignment @@ -18687,6 +23597,10 @@ <br/>ElectricalandComputerEngineeringDepartment <br/><b>UniversityofMaryland</b><br/><b>CollegePark, MD</b><br/>ThesupportoftheO(cid:14)ceofNavalResearchunderGrantN </td><td></td><td>Email:fwyzhao,ramag@cfar.umd.edu +</td></tr><tr><td>725c3605c2d26d113637097358cd4c08c19ff9e1</td><td>Deep Reasoning with Knowledge Graph for Social Relationship Understanding +<br/><b>School of Data and Computer Science, Sun Yat-sen University, China</b><br/>2 SenseTime Research, China +</td><td>('29988001', 'Zhouxia Wang', 'zhouxia wang')<br/>('1765674', 'Tianshui Chen', 'tianshui chen')<br/>('12254824', 'Weihao Yu', 'weihao yu')<br/>('47413456', 'Hui Cheng', 'hui cheng')<br/>('1737218', 'Liang Lin', 'liang lin')</td><td>zhouzi1212,tianshuichen,jimmy.sj.ren,weihaoyu6@gmail.com, +<br/>chengh9@mail.sysu.edu.cn, linliang@ieee.org </td></tr><tr><td>445461a34adc4bcdccac2e3c374f5921c93750f8</td><td>Emotional Expression Classification using Time-Series Kernels∗ </td><td>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('1733113', 'Takeo Kanade', 'takeo kanade')</td><td>1E¨otv¨os Lor´and University, Budapest, Hungary, {andras.lorincz,szzoli}@elte.hu <br/>2Carnegie Mellon University, Pittsburgh, PA, laszlo.jeni@ieee.org,tk@cs.cmu.edu @@ -18735,14 +23649,21 @@ </td><td>('2716937', 'Srikanth Muralidharan', 'srikanth muralidharan')<br/>('2190580', 'Simon Fraser', 'simon fraser')<br/>('15695326', 'Mehrsan Javan', 'mehrsan javan')<br/>('10771328', 'Greg Mori', 'greg mori')<br/>('2190580', 'Simon Fraser', 'simon fraser')</td><td>smuralid@sfu.ca <br/>mehrsan@sportlogiq.com <br/>mori@cs.sfu.ca -</td></tr><tr><td>44f48a4b1ef94a9104d063e53bf88a69ff0f55f3</td><td>Automatically Building Face Datasets of New Domains +</td></tr><tr><td>44b1399e8569a29eed0d22d88767b1891dbcf987</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +<br/>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE +<br/>Learning Multi-modal Latent Attributes +</td><td>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')</td><td></td></tr><tr><td>44f48a4b1ef94a9104d063e53bf88a69ff0f55f3</td><td>Automatically Building Face Datasets of New Domains <br/>from Weakly Labeled Data with Pretrained Models -<br/><b>Sun Yat-sen University</b></td><td>('2442939', 'Shengyong Ding', 'shengyong ding')<br/>('4080607', 'Junyu Wu', 'junyu wu')<br/>('1723992', 'Wei Xu', 'wei xu')<br/>('38255852', 'Hongyang Chao', 'hongyang chao')</td><td></td></tr><tr><td>44a3ec27f92c344a15deb8e5dc3a5b3797505c06</td><td>A Taxonomy of Part and Attribute Discovery +<br/><b>Sun Yat-sen University</b></td><td>('2442939', 'Shengyong Ding', 'shengyong ding')<br/>('4080607', 'Junyu Wu', 'junyu wu')<br/>('1723992', 'Wei Xu', 'wei xu')<br/>('38255852', 'Hongyang Chao', 'hongyang chao')</td><td></td></tr><tr><td>446dc1413e1cfaee0030dc74a3cee49a47386355</td><td>Recent Advances in Zero-shot Recognition +</td><td>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')</td><td></td></tr><tr><td>44a3ec27f92c344a15deb8e5dc3a5b3797505c06</td><td>A Taxonomy of Part and Attribute Discovery <br/>Techniques </td><td>('35208858', 'Subhransu Maji', 'subhransu maji')</td><td></td></tr><tr><td>44aeda8493ad0d44ca1304756cc0126a2720f07b</td><td>Face Alive Icons </td><td>('1685323', 'Xin Li', 'xin li')<br/>('2304980', 'Chieh-Chih Chang', 'chieh-chih chang')<br/>('1679040', 'Shi-Kuo Chang', 'shi-kuo chang')</td><td>1University of Pittsburgh, USA,{flying, chang}@cs.pitt.edu <br/>2Industrial Technology Research Institute, Taiwan, chieh@itri.org.tw -</td></tr><tr><td>449b1b91029e84dab14b80852e35387a9275870e</td><td></td><td></td><td></td></tr><tr><td>44078d0daed8b13114cffb15b368acc467f96351</td><td></td><td></td><td></td></tr><tr><td>44c9b5c55ca27a4313daf3760a3f24a440ce17ad</td><td>Revisiting hand-crafted feature for action recognition: +</td></tr><tr><td>449b1b91029e84dab14b80852e35387a9275870e</td><td></td><td></td><td></td></tr><tr><td>44078d0daed8b13114cffb15b368acc467f96351</td><td></td><td></td><td></td></tr><tr><td>44d23df380af207f5ac5b41459c722c87283e1eb</td><td>Human Attribute Recognition by Deep +<br/>Hierarchical Contexts +<br/><b>The Chinese University of Hong Kong</b></td><td>('47002704', 'Yining Li', 'yining li')<br/>('2000034', 'Chen Huang', 'chen huang')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{ly015,chuang,ccloy,xtang}@ie.cuhk.edu.hk +</td></tr><tr><td>44c9b5c55ca27a4313daf3760a3f24a440ce17ad</td><td>Revisiting hand-crafted feature for action recognition: <br/>a set of improved dense trajectories <br/><b>Hiroshima University, Japan</b><br/>ENSICAEN, France <br/><b>Hiroshima University, Japan</b></td><td>('2223849', 'Kenji Matsui', 'kenji matsui')<br/>('1744862', 'Toru Tamaki', 'toru tamaki')<br/>('30171131', 'Gwladys Auffret', 'gwladys auffret')<br/>('1688940', 'Bisser Raytchev', 'bisser raytchev')<br/>('1686272', 'Kazufumi Kaneda', 'kazufumi kaneda')</td><td></td></tr><tr><td>44dd150b9020b2253107b4a4af3644f0a51718a3</td><td>An Analysis of the Sensitivity of Active Shape @@ -18819,7 +23740,9 @@ <br/><b>Institute of Automation, Chinese Academy of Sciences</b><br/><b>Michigan State University</b></td><td>('8362374', 'Xiangyu Zhu', 'xiangyu zhu')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')<br/>('1704812', 'Hailin Shi', 'hailin shi')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{xiangyu.zhu,zlei,hailin.shi,szli}@nlpr.ia.ac.cn <br/>liuxm@msu.edu </td></tr><tr><td>2aa2b312da1554a7f3e48f71f2fce7ade6d5bf40</td><td>Estimating Sheep Pain Level Using Facial Action Unit Detection -<br/><b>Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>('9871228', 'Yiting Lu', 'yiting lu')<br/>('2022940', 'Marwa Mahmoud', 'marwa mahmoud')<br/>('39626495', 'Peter Robinson', 'peter robinson')</td><td></td></tr><tr><td>2ae139b247057c02cda352f6661f46f7feb38e45</td><td>Combining Modality Specific Deep Neural Networks for +<br/><b>Computer Laboratory, University of Cambridge, Cambridge, UK</b></td><td>('9871228', 'Yiting Lu', 'yiting lu')<br/>('2022940', 'Marwa Mahmoud', 'marwa mahmoud')<br/>('39626495', 'Peter Robinson', 'peter robinson')</td><td></td></tr><tr><td>2aec012bb6dcaacd9d7a1e45bc5204fac7b63b3c</td><td>Robust Registration and Geometry Estimation from Unstructured +<br/>Facial Scans +</td><td>('19214361', 'Maxim Bazik', 'maxim bazik')</td><td></td></tr><tr><td>2ae139b247057c02cda352f6661f46f7feb38e45</td><td>Combining Modality Specific Deep Neural Networks for <br/>Emotion Recognition in Video <br/>1École Polytechique de Montréal, Université de Montréal, Montréal, Canada <br/>2Laboratoire d’Informatique des Systèmes Adaptatifs, Université de Montréal, Montréal, Canada @@ -18840,7 +23763,41 @@ <br/>cm3052@columbia.edu <br/>sfchang@ee.columbia.edu <br/>sanjivk@google.com -</td></tr><tr><td>2a02355c1155f2d2e0cf7a8e197e0d0075437b19</td><td></td><td></td><td></td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>Learning Social Relation Traits from Face Images +</td></tr><tr><td>2a5903bdb3fdfb4d51f70b77f16852df3b8e5f83</td><td>121 +<br/>The Effect of Computer-Generated Descriptions +<br/>on Photo-Sharing Experiences of People With +<br/>Visual Impairments +<br/>Like sighted people, visually impaired people want to share photographs on social networking services, but +<br/>find it difficult to identify and select photos from their albums. We aimed to address this problem by +<br/>incorporating state-of-the-art computer-generated descriptions into Facebook’s photo-sharing feature. We +<br/>interviewed 12 visually impaired participants to understand their photo-sharing experiences and designed a +<br/>photo description feature for the Facebook mobile application. We evaluated this feature with six +<br/>participants in a seven-day diary study. We found that participants used the descriptions to recall and +<br/>organize their photos, but they hesitated to upload photos without a sighted person’s input. In addition to +<br/>basic information about photo content, participants wanted to know more details about salient objects and +<br/>people, and whether the photos reflected their personal aesthetic. We discuss these findings from the lens of +<br/>self-disclosure and self-presentation theories and propose new computer vision research directions that will +<br/>better support visual content sharing by visually impaired people. +<br/>CCS Concepts: • Information interfaces and presentations → Multimedia and information systems; • +<br/>Social and professional topics → People with disabilities +<br/>KEYWORDS +<br/>Visual impairments; computer-generated descriptions; SNSs; photo sharing; self-disclosure; self-presentation +<br/>ACM Reference format: +<br/>The Effect of Computer-Generated Descriptions On Photo-Sharing Experiences of People With Visual +<br/>Impairments. Proc. ACM Hum.-Comput. Interact. 1, CSCW. 121 (November 2017), 22 pages. +<br/>DOI: 10.1145/3134756 +<br/>1 INTRODUCTION +<br/>Sharing memories and experiences via photos is a common way to engage with others on social networking +<br/>services (SNSs) [39,46,51]. For instance, Facebook users uploaded more than 350 million photos a day [24] +<br/>and Twitter, which initially supported only text in tweets, now has more than 28.4% of tweets containing +<br/>images [39]. Visually impaired people (both blind and low vision) have a strong presence on SNS and are +<br/>interested in sharing photos [50]. They take photos for the same reasons that sighted people do: sharing +<br/>daily moments with their sighted friends and family [30,32]. A prior study showed that visually impaired +<br/>people shared a relatively large number of photos on Facebook—only slightly less than their sighted +<br/>counterparts [50]. +<br/> +<br/> PACM on Human-Computer Interaction, Vol. 1, No. 2, Article 121. Publication date: November 2017 +</td><td>('2582568', 'Yuhang Zhao', 'yuhang zhao')<br/>('1968133', 'Shaomei Wu', 'shaomei wu')<br/>('39685591', 'Lindsay Reynolds', 'lindsay reynolds')<br/>('3283573', 'Shiri Azenkot', 'shiri azenkot')</td><td></td></tr><tr><td>2a02355c1155f2d2e0cf7a8e197e0d0075437b19</td><td></td><td></td><td></td></tr><tr><td>2a171f8d14b6b8735001a11c217af9587d095848</td><td>Learning Social Relation Traits from Face Images <br/><b>The Chinese University of Hong Kong</b></td><td>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('1693209', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>zz013@ie.cuhk.edu.hk, pluo@ie.cuhk.edu.hk, ccloy@ie.cuhk.edu.hk, xtang@ie.cuhk.edu.hk </td></tr><tr><td>2aea27352406a2066ddae5fad6f3f13afdc90be9</td><td></td><td></td><td></td></tr><tr><td>2a0623ae989f2236f5e1fe3db25ab708f5d02955</td><td>3D Face Modelling for 2D+3D Face Recognition <br/>J.R. Tena Rodr´ıguez @@ -18857,6 +23814,11 @@ <br/>David Kriegman, Senior Member, IEEE </td><td>('2457452', 'Kuang-chih Lee', 'kuang-chih lee')<br/>('1788818', 'Jeffrey Ho', 'jeffrey ho')</td><td></td></tr><tr><td>2afdda6fb85732d830cea242c1ff84497cd5f3cb</td><td>Face Image Retrieval by Using Haar Features <br/><b>Institute ofInformation Science, Academia Sinica, Taipei, Taiwan</b><br/><b>Graduate Institute ofNetworking and Multimedia, National Taiwan University, Taipei, Taiwan</b><br/><b>Tamkang University, Taipei, Taiwan</b></td><td>('2609751', 'Bau-Cheng Shen', 'bau-cheng shen')<br/>('1720473', 'Chu-Song Chen', 'chu-song chen')<br/>('1679560', 'Hui-Huang Hsu', 'hui-huang hsu')</td><td>{bcshen, song} @ iis.sinica. edu. tw, h_hsu@mail. tku. edu. tw +</td></tr><tr><td>2ab034e1f54c37bfc8ae93f7320160748310dc73</td><td>Siamese Capsule Networks +<br/>James O’ Neill +<br/>Department of Computer Science +<br/><b>University of Liverpool</b><br/>Liverpool, L69 3BX +</td><td></td><td>james.o-neill@liverpool.ac.uk </td></tr><tr><td>2ff9618ea521df3c916abc88e7c85220d9f0ff06</td><td>Facial Tic Detection Using Computer Vision <br/>Christopher D. Leveille <br/>March 20, 2014 @@ -18872,7 +23834,16 @@ </td><td>('1720307', 'Dong Zhang', 'dong zhang')<br/>('2405613', 'Omar Oreifej', 'omar oreifej')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td>dzhang@cs.ucf.edu <br/>oreifej@eecs.berkeley.edu <br/>shah@crcv.ucf.edu -</td></tr><tr><td>2fdce3228d384456ea9faff108b9c6d0cf39e7c7</td><td></td><td></td><td></td></tr><tr><td>2f7e9b45255c9029d2ae97bbb004d6072e70fa79</td><td>Noname manuscript No. +</td></tr><tr><td>2fdce3228d384456ea9faff108b9c6d0cf39e7c7</td><td></td><td></td><td></td></tr><tr><td>2ffcd35d9b8867a42be23978079f5f24be8d3e35</td><td> +<br/>ISSN XXXX XXXX © 2018 IJESC +<br/> +<br/> +<br/>Research Article Volume 8 Issue No.6 +<br/>Satellite based Image Processing using Data mining +<br/>E.Malleshwari1, S.Nirmal Kumar2, J.Dhinesh3 +<br/>Professor1, Assistant Professor2, PG Scholar3 +<br/>Department of Information Technology1, 2, Master of Computer Applications3 +<br/><b>Vel Tech High Tech Dr Rangarajan Dr Sakunthala Engineering College, Avadi, Chennai, India</b></td><td></td><td></td></tr><tr><td>2f7e9b45255c9029d2ae97bbb004d6072e70fa79</td><td>Noname manuscript No. <br/>(will be inserted by the editor) <br/>cvpaper.challenge in 2015 <br/>A review of CVPR2015 and DeepSurvey @@ -18918,14 +23889,31 @@ <br/><b>Engineering, Ton Duc Thang University, 19 Nguyen Huu Tho Street, Ho Chi Minh City, Vietman</b><br/>2Department of Computer Science, Faculty of Electrical Engineering and Computer Science, <br/><b>VSB Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava, Czech Republic</b><br/>DOI: 10.15598/aeee.v14i5.1116 </td><td>('1681072', 'Ivan ZELINKA', 'ivan zelinka')<br/>('1856530', 'Petr SALOUN', 'petr saloun')<br/>('2053234', 'Jakub STONAWSKI', 'jakub stonawski')<br/>('2356663', 'Adam ONDREJKA', 'adam ondrejka')</td><td>ivan.zelinka@tdt.edu.vn, petr.saloun@vsb.cz, stonawski.jakub@gmail.com, adam.ondrejka@gmail.com -</td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td>Names and Faces in the News +</td></tr><tr><td>2fc43c2c3f7ad1ca7a1ce32c5a9a98432725fb9a</td><td>Hierarchical Video Generation from Orthogonal +<br/>Information: Optical Flow and Texture +<br/><b>The University of Tokyo</b><br/><b>The University of Tokyo</b><br/><b>The University of Tokyo</b><br/><b>The University of Tokyo / RIKEN</b></td><td>('8197937', 'Katsunori Ohnishi', 'katsunori ohnishi')<br/>('48333400', 'Shohei Yamamoto', 'shohei yamamoto')<br/>('3250559', 'Yoshitaka Ushiku', 'yoshitaka ushiku')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td>ohnishi@mi.t.u-tokyo.ac.jp +<br/>yamamoto@mi.t.u-tokyo.ac.jp +<br/>ushiku@mi.t.u-tokyo.ac.jp +<br/>harada@mi.t.u-tokyo.ac.jp +</td></tr><tr><td>2f88d3189723669f957d83ad542ac5c2341c37a5</td><td>Downloaded From: https://www.spiedigitallibrary.org/journals/Journal-of-Electronic-Imaging on 9/13/2018 +<br/>Terms of Use: https://www.spiedigitallibrary.org/terms-of-use +<br/>Attribute-correlatedlocalregionsfordeeprelativeattributeslearningFenZhangXiangweiKongZeJiaFenZhang,XiangweiKong,ZeJia,“Attribute-correlatedlocalregionsfordeeprelativeattributeslearning,”J.Electron.Imaging27(4),043021(2018),doi:10.1117/1.JEI.27.4.043021. </td><td></td><td></td></tr><tr><td>2fda164863a06a92d3a910b96eef927269aeb730</td><td>Names and Faces in the News <br/>Computer Science Division <br/>U.C. Berkeley <br/>Berkeley, CA 94720 </td><td>('1685538', 'Tamara L. Berg', 'tamara l. berg')<br/>('39668247', 'Alexander C. Berg', 'alexander c. berg')<br/>('34497462', 'Jaety Edwards', 'jaety edwards')<br/>('1965929', 'Michael Maire', 'michael maire')<br/>('6714943', 'Ryan White', 'ryan white')</td><td>daf@cs.berkeley.edu </td></tr><tr><td>2fa057a20a2b4a4f344988fee0a49fce85b0dc33</td><td></td><td></td><td></td></tr><tr><td>2f8ef26bfecaaa102a55b752860dbb92f1a11dc6</td><td>A Graph Based Approach to Speaker Retrieval in Talk <br/>Show Videos with Transcript-Based Supervision -</td><td>('1859487', 'Yina Han', 'yina han')<br/>('1774346', 'Guizhong Liu', 'guizhong liu')<br/>('1692389', 'Hichem Sahbi', 'hichem sahbi')<br/>('1693574', 'Gérard Chollet', 'gérard chollet')</td><td></td></tr><tr><td>2f184c6e2c31d23ef083c881de36b9b9b6997ce9</td><td>Polichotomies on Imbalanced Domains +</td><td>('1859487', 'Yina Han', 'yina han')<br/>('1774346', 'Guizhong Liu', 'guizhong liu')<br/>('1692389', 'Hichem Sahbi', 'hichem sahbi')<br/>('1693574', 'Gérard Chollet', 'gérard chollet')</td><td></td></tr><tr><td>2f17f6c460e02bd105dcbf14c9b73f34c5fb59bd</td><td>Article +<br/>Robust Face Recognition Using the Deep C2D-CNN +<br/>Model Based on Decision-Level Fusion +<br/><b>School of Electronic and Information, Yangtze University, Jingzhou 434023, China</b><br/><b>National Demonstration Center for Experimental Electrical and Electronic Education, Yangtze University</b><br/>Jingzhou 434023, China +<br/>† These authors contributed equally to this work. +<br/>Received: 20 May 2018; Accepted: 25 June 2018; Published: 28 June 2018 +</td><td>('1723081', 'Jing Li', 'jing li')<br/>('48216473', 'Tao Qiu', 'tao qiu')<br/>('41208300', 'Chang Wen', 'chang wen')<br/>('36203475', 'Kai Xie', 'kai xie')</td><td>201501479@yangtzeu.edu.cn (J.L.); 500646@yangtzeu.edu.cn (K.X.); wenfangqing@yangtzeu.edu.cn (F-Q.W.) +<br/>School of Computer Science, Yangtze University, Jingzhou 434023, China; 201603441@yangtzeu.edu.cn +<br/>* Correspondence: 400100@yangtzeu.edu.cn; Tel.: +86-136-9731-5482 +</td></tr><tr><td>2f184c6e2c31d23ef083c881de36b9b9b6997ce9</td><td>Polichotomies on Imbalanced Domains <br/>by One-per-Class Compensated Reconstruction Rule <br/>Integrated Research Centre, Universit´a Campus Bio-Medico of Rome, Rome, Italy </td><td>('1720099', 'Paolo Soda', 'paolo soda')</td><td>{r.dambrosio,p.soda}@unicampus.it @@ -18951,7 +23939,7 @@ <br/>1Data61/CSIRO, <br/>2Australian Centre for Robotic Vision <br/><b>The Australian National University, Canberra, Australia</b></td><td>('36541522', 'Jue Wang', 'jue wang')<br/>('2691929', 'Anoop Cherian', 'anoop cherian')<br/>('2377076', 'Stephen Gould', 'stephen gould')</td><td>firstname.lastname@anu.edu.au -</td></tr><tr><td>2f0e5a4b0ef89dd2cf55a4ef65b5c78101c8bfa1</td><td>Facial Expression Recognition Using a Hybrid CNN–SIFT Aggregator +</td></tr><tr><td>2fea258320c50f36408032c05c54ba455d575809</td><td></td><td></td><td></td></tr><tr><td>2f0e5a4b0ef89dd2cf55a4ef65b5c78101c8bfa1</td><td>Facial Expression Recognition Using a Hybrid CNN–SIFT Aggregator <br/>Mundher Ahmed Al-Shabi <br/>Tee Connie <br/>Faculty of Information Science and Technology (FIST) @@ -18989,7 +23977,10 @@ <br/>Prof. Francesco G. B. De Natale <br/>Universit`a degli Studi di Trento <br/>February 2014 -</td><td>('2598811', 'Duc-Tien Dang-Nguyen', 'duc-tien dang-nguyen')</td><td></td></tr><tr><td>439ac8edfa1e7cbc65474cab544a5b8c4c65d5db</td><td>SIViP (2011) 5:401–413 +</td><td>('2598811', 'Duc-Tien Dang-Nguyen', 'duc-tien dang-nguyen')</td><td></td></tr><tr><td>438c4b320b9a94a939af21061b4502f4a86960e3</td><td>Reconstruction-Based Disentanglement for Pose-invariant Face Recognition +<br/><b>Rutgers, The State University of New Jersey</b><br/><b>University of California, San Diego</b><br/>‡ NEC Laboratories America +</td><td>('4340744', 'Xi Peng', 'xi peng')<br/>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>{xipeng.cs, dnm}@rutgers.edu, {xiangyu,ksohn,manu}@nec-labs.com +</td></tr><tr><td>439ac8edfa1e7cbc65474cab544a5b8c4c65d5db</td><td>SIViP (2011) 5:401–413 <br/>DOI 10.1007/s11760-011-0244-6 <br/>ORIGINAL PAPER <br/>Face authentication with undercontrolled pose and illumination @@ -19044,7 +24035,7 @@ </td><td>('9318822', 'Mahesh Goyani', 'mahesh goyani')<br/>('40632096', 'Ronak Paun', 'ronak paun')<br/>('40803051', 'Sardar Patel', 'sardar patel')<br/>('40803051', 'Sardar Patel', 'sardar patel')<br/>('40803051', 'Sardar Patel', 'sardar patel')</td><td>e- mail : mgoyani@gmail.com <br/>e- mail : akashdhorajiya@gmail.com <br/>e- mail : ronak_paun@yahoo.com -</td></tr><tr><td>4350bb360797a4ade4faf616ed2ac8e27315968e</td><td><b>MITSUBISHI ELECTRIC RESEARCH LABORATORIES</b><br/>http://www.merl.com +</td></tr><tr><td>43e268c118ac25f1f0e984b57bc54f0119ded520</td><td></td><td></td><td></td></tr><tr><td>4350bb360797a4ade4faf616ed2ac8e27315968e</td><td><b>MITSUBISHI ELECTRIC RESEARCH LABORATORIES</b><br/>http://www.merl.com <br/>Edge Suppression by Gradient Field <br/>Transformation using Cross-Projection <br/>Tensors @@ -19097,15 +24088,31 @@ <br/>Chennai, India </td><td>('1717115', 'Anurag Mittal', 'anurag mittal')</td><td>akatti@cse.iitm.ac.in <br/>amittal@cse.iitm.ac.in +</td></tr><tr><td>432d8cba544bf7b09b0455561fea098177a85db1</td><td>Published as a conference paper at ICLR 2017 +<br/>TOWARDS A NEURAL STATISTICIAN +<br/>Harrison Edwards +<br/>School of Informatics +<br/><b>University of Edinburgh</b><br/>Edinburgh, UK +<br/>Amos Storkey +<br/>School of Informatics +<br/><b>University of Edinburgh</b><br/>Edinburgh, UK +</td><td></td><td>H.L.Edwards@sms.ed.ac.uk +<br/>A.Storkey@ed.ac.uk </td></tr><tr><td>43ed518e466ff13118385f4e5d039ae4d1c000fb</td><td>Classification of Occluded Objects using Fast Recurrent <br/>Processing <br/>Ozgur Yilmaza,∗ <br/><b>aTurgut Ozal University, Ankara Turkey</b></td><td></td><td></td></tr><tr><td>439647914236431c858535a2354988dde042ef4d</td><td>Face Illumination Normalization on Large and Small Scale Features <br/><b>School of Mathematics and Computational Science, Sun Yat-sen University, China</b><br/><b>School of Information Science and Technology, Sun Yat-sen University, China</b><br/>3 Guangdong Province Key Laboratory of Information Security, China, <br/><b>Hong Kong Baptist University</b></td><td>('2002129', 'Xiaohua Xie', 'xiaohua xie')<br/>('3333315', 'Wei-Shi Zheng', 'wei-shi zheng')<br/>('1768574', 'Pong C. Yuen', 'pong c. yuen')</td><td>Email: sysuxiexh@gmail.com, wszheng@ieee.org, stsljh@mail.sysu.edu.cn, pcyuen@comp.hkbu.edu.hk -</td></tr><tr><td>439ca6ded75dffa5ddea203dde5e621dc4a88c3e</td><td>Robust Real-time Performance-driven 3D Face Tracking +</td></tr><tr><td>43d7d0d0d0e2d6cf5355e60c4fe5b715f0a1101a</td><td>Pobrane z czasopisma Annales AI- Informatica http://ai.annales.umcs.pl +<br/>Data: 04/05/2018 16:53:32 +<br/>U M CS +</td><td></td><td></td></tr><tr><td>439ca6ded75dffa5ddea203dde5e621dc4a88c3e</td><td>Robust Real-time Performance-driven 3D Face Tracking <br/><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore</b><br/><b>Rutgers University, USA</b></td><td>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')<br/>('1775268', 'Tat-Jen Cham', 'tat-jen cham')</td><td>{hxp1,vladimir}@cs.rutgers.edu <br/>{asjfcai,astfcham}@ntu.edu.sg +</td></tr><tr><td>88e090ffc1f75eed720b5afb167523eb2e316f7f</td><td>Attribute-Based Transfer Learning for Object +<br/>Categorization with Zero/One Training Example +<br/><b>University of Maryland, College Park, MD, USA</b></td><td>('3099583', 'Xiaodong Yu', 'xiaodong yu')<br/>('1697493', 'Yiannis Aloimonos', 'yiannis aloimonos')</td><td>xdyu@umiacs.umd.edu, yiannis@cs.umd.edu </td></tr><tr><td>8877e0b2dc3d2e8538c0cfee86b4e8657499a7c4</td><td>AUTOMATIC FACIAL EXPRESSION RECOGNITION FOR AFFECTIVE COMPUTING <br/>BASED ON BAG OF DISTANCES <br/><b>National Chung Cheng University, Chiayi, Taiwan, R.O.C</b><br/>E-mail: {hfs95p,wylin}cs.ccu.edu.tw @@ -19118,7 +24125,13 @@ </td><td>('2040369', 'Zeyu Li', 'zeyu li')</td><td></td></tr><tr><td>889bc64c7da8e2a85ae6af320ae10e05c4cd6ce7</td><td>174 <br/>Using Support Vector Machines to Enhance the <br/>Performance of Bayesian Face Recognition -</td><td>('1911510', 'Zhifeng Li', 'zhifeng li')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>88f7a3d6f0521803ca59fde45601e94c3a34a403</td><td>Semantic Aware Video Transcription +</td><td>('1911510', 'Zhifeng Li', 'zhifeng li')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>88a898592b4c1dfd707f04f09ca58ec769a257de</td><td>MobileFace: 3D Face Reconstruction +<br/>with Efficient CNN Regression +<br/>1 VisionLabs, Amsterdam, The Netherlands +<br/>2 Inria, WILLOW, Departement d’Informatique de l’Ecole Normale Superieure, PSL +<br/><b>Research University, ENS/INRIA/CNRS UMR 8548, Paris, France</b></td><td>('51318557', 'Nikolai Chinaev', 'nikolai chinaev')<br/>('2564281', 'Alexander Chigorin', 'alexander chigorin')<br/>('1785596', 'Ivan Laptev', 'ivan laptev')</td><td>{n.chinaev, a.chigorin}@visionlabs.ru +<br/>ivan.laptev@inria.fr +</td></tr><tr><td>88f7a3d6f0521803ca59fde45601e94c3a34a403</td><td>Semantic Aware Video Transcription <br/>Using Random Forest Classifiers <br/><b>University of Southern California, Institute for Robotics and Intelligent Systems</b><br/>Los Angeles, CA 90089, USA </td><td>('1726241', 'Chen Sun', 'chen sun')</td><td></td></tr><tr><td>8812aef6bdac056b00525f0642702ecf8d57790b</td><td>A Unified Features Approach to Human Face Image @@ -19228,7 +24241,10 @@ <br/>Dino.Miniutti@ausport.gov.au </td></tr><tr><td>88f2952535df5859c8f60026f08b71976f8e19ec</td><td>A neural network framework for face <br/>recognition by elastic bunch graph matching -</td><td>('37048377', 'Francisco A. Pujol López', 'francisco a. pujol lópez')<br/>('3144590', 'Higinio Mora Mora', 'higinio mora mora')<br/>('2260459', 'José A. Girona Selva', 'josé a. girona selva')</td><td></td></tr><tr><td>8862a573a42bbaedd392e9e634c1ccbfd177a01d</td><td>3D Face Tracking and Texture Fusion in the Wild +</td><td>('37048377', 'Francisco A. Pujol López', 'francisco a. pujol lópez')<br/>('3144590', 'Higinio Mora Mora', 'higinio mora mora')<br/>('2260459', 'José A. Girona Selva', 'josé a. girona selva')</td><td></td></tr><tr><td>8818b12aa0ff3bf0b20f9caa250395cbea0e8769</td><td>Fashion Conversation Data on Instagram +<br/>∗Graduate School of Culture Technology, KAIST, South Korea +<br/>†Department of Communication Studies, UCLA, USA +</td><td>('3459091', 'Yu-i Ha', 'yu-i ha')<br/>('2399803', 'Sejeong Kwon', 'sejeong kwon')<br/>('1775511', 'Meeyoung Cha', 'meeyoung cha')<br/>('1834047', 'Jungseock Joo', 'jungseock joo')</td><td></td></tr><tr><td>8862a573a42bbaedd392e9e634c1ccbfd177a01d</td><td>3D Face Tracking and Texture Fusion in the Wild <br/>Centre for Vision, Speech and Signal Processing <br/>Image Understanding and Interactive Robotics <br/><b>University of Surrey</b><br/>Guildford, GU2 7XH, United Kingdom @@ -19241,7 +24257,33 @@ <br/>Human Action Recognition in Unconstrained <br/>Videos by Explicit Motion Modeling </td><td>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('9227981', 'Qi Dai', 'qi dai')<br/>('39059457', 'Wei Liu', 'wei liu')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')<br/>('1751681', 'Chong-Wah Ngo', 'chong-wah ngo')</td><td></td></tr><tr><td>8855d6161d7e5b35f6c59e15b94db9fa5bbf2912</td><td>COGNITION IN PREGNANCY AND THE POSTPARTUM PERIOD -</td><td></td><td></td></tr><tr><td>88bee9733e96958444dc9e6bef191baba4fa6efa</td><td>Extending Face Identification to +</td><td></td><td></td></tr><tr><td>8895d6ae9f095a8413f663cc83f5b7634b3dc805</td><td>BEHL ET AL: INCREMENTAL TUBE CONSTRUCTION FOR HUMAN ACTION DETECTION 1 +<br/>Incremental Tube Construction for Human +<br/>Action Detection +<br/>Harkirat Singh Behl1 +<br/>1 Department of Engineering Science +<br/><b>University of Oxford</b><br/>Oxford, UK +<br/>2 Think Tank Team +<br/>Samsung Research America +<br/>Mountain View, CA +<br/>3 Dept. of Computing and +<br/>Communication Technologies +<br/><b>Oxford Brookes University</b><br/>Oxford, UK +<br/>(a) Illustrative results on a video sequence from the LIRIS-HARL dataset [23]. Two people enter a room +<br/>Figure 1: +<br/>and put/take an object from a box (frame 150). They then shake hands (frame 175) and start having a discussion +<br/>(frame 350). In frame 450, another person enters the room, shakes hands, and then joins the discussion. Each +<br/>action tube instance is numbered and coloured according to its action category. We selected this video to show that +<br/>our tube construction algorithm can handle very complex situations in which multiple distinct action categories +<br/>occur in sequence and at concurrent times. (b) Action tubes drawn as viewed from above, compared to (c) the +<br/>ground truth action tubes. +</td><td>('3019396', 'Michael Sapienza', 'michael sapienza')<br/>('1931660', 'Gurkirt Singh', 'gurkirt singh')<br/>('49348905', 'Suman Saha', 'suman saha')<br/>('1754181', 'Fabio Cuzzolin', 'fabio cuzzolin')<br/>('1730268', 'Philip H. S. Torr', 'philip h. s. torr')</td><td>harkirat@robots.ox.ac.uk +<br/>m.sapienza@samsung.com +<br/>gurkirt.singh-2015@brookes.ac.uk +<br/>suman.saha-2014@brookes.ac.uk +<br/>fabio.cuzzolin@brookes.ac.uk +<br/>phst@robots.ox.ac.uk +</td></tr><tr><td>88bee9733e96958444dc9e6bef191baba4fa6efa</td><td>Extending Face Identification to <br/>Open-Set Face Recognition <br/>Department of Computer Science <br/>Universidade Federal de Minas Gerais @@ -19391,7 +24433,78 @@ <br/>201 Washington Rd, <br/>Princeton, NJ, 08540 </td><td>('1981308', 'Manika Puri', 'manika puri')</td><td>{mpuri, zzhu, qyu, adivakaran, hsawhney}@sarnoff.com -</td></tr><tr><td>6b9aa288ce7740ec5ce9826c66d059ddcfd8dba9</td><td></td><td></td><td></td></tr><tr><td>6bcfcc4a0af2bf2729b5bc38f500cfaab2e653f0</td><td>Facial expression recognition in the wild using improved dense trajectories and +</td></tr><tr><td>9fdfe1695adac2380f99d3d5cb6879f0ac7f2bfd</td><td>EURASIP Journal on Applied Signal Processing 2005:13, 2091–2100 +<br/>c(cid:1) 2005 Hindawi Publishing Corporation +<br/>Spatio-Temporal Graphical-Model-Based +<br/>Multiple Facial Feature Tracking +<br/>Congyong Su +<br/><b>College of Computer Science, Zhejiang University, Hangzhou 310027, China</b><br/>Li Huang +<br/><b>College of Computer Science, Zhejiang University, Hangzhou 310027, China</b><br/>Received 1 January 2004; Revised 20 February 2005 +<br/>It is challenging to track multiple facial features simultaneously when rich expressions are presented on a face. We propose a two- +<br/>step solution. In the first step, several independent condensation-style particle filters are utilized to track each facial feature in the +<br/>temporal domain. Particle filters are very effective for visual tracking problems; however multiple independent trackers ignore +<br/>the spatial constraints and the natural relationships among facial features. In the second step, we use Bayesian inference—belief +<br/>propagation—to infer each facial feature’s contour in the spatial domain, in which we learn the relationships among contours of +<br/>facial features beforehand with the help of a large facial expression database. The experimental results show that our algorithm +<br/>can robustly track multiple facial features simultaneously, while there are large interframe motions with expression changes. +<br/>Keywords and phrases: facial feature tracking, particle filter, belief propagation, graphical model. +<br/>1. +<br/>INTRODUCTION +<br/>Multiple facial feature tracking is very important in the com- +<br/>puter vision field: it needs to be carried out before video- +<br/>based facial expression analysis and expression cloning. Mul- +<br/>tiple facial feature tracking is also very challenging be- +<br/>cause there are plentiful nonrigid motions in facial fea- +<br/>tures besides rigid motions in faces. Nonrigid facial fea- +<br/>ture motions are usually very rapid and often form dense +<br/>clutter by facial features themselves. Only using traditional +<br/>Kalman filter is inadequate because it is based on Gaus- +<br/>sian density, and works relatively poorly in clutter, which +<br/>causes the density for facial feature’s contour to be multi- +<br/>modal and therefore non-Gaussian. Isard and Blake [1] firstly +<br/>proposed a face tracker by particle filters—condensation— +<br/>which is more effective in clutter than comparable Kalman +<br/>filter. +<br/>Although particle filters are often very effective for visual +<br/>tracking problems, they are specialized to temporal problems +<br/>whose corresponding graphs are simple Markov chains (see +<br/>Figure 1). There is often structure within each time instant +<br/>that is ignored by particle filters. For example, in multiple +<br/>facial feature tracking, the expressions of each facial feature +<br/>(such as eyes, brows, lips) are closely related; therefore a more +<br/>complex graph should be formulated. +<br/>The contribution of this paper is extending particle filters +<br/>to track multiple facial features simultaneously. The straight- +<br/>forward approach of tracking each facial feature by one in- +<br/>dependent particle filter is questionable, because influences +<br/>and actions among facial features are not taken into account. +<br/>In this paper, we propose a spatio-temporal graphical +<br/>model for multiple facial feature tracking (see Figure 2). Here +<br/>the graphical model is not a 2D or a 3D facial mesh model. +<br/>In the spatial domain, the model is shown in Figure 3, where +<br/>xi is a hidden random variable and yi is a noisy local ob- +<br/>servation. Nonparametric belief propagation is used to infer +<br/>facial feature’s interrelationships in a part-based face model, +<br/>allowing positions and states of some features in clutter to +<br/>be recovered. Facial structure is also taken into account, be- +<br/>cause facial features have spatial position constraints [2]. In +<br/>the temporal domain, every facial feature forms a Markov +<br/>chain (see Figure 1). +<br/>After briefly reviewing related work in Section 2, we +<br/>introduce the details of our algorithm in Sections 3 and +<br/>4. Many convincing experimental results are shown in +<br/>Section 5. Conclusions are given in Section 6. +<br/>2. RELATED WORK +<br/>After the pioneering work of Isard and Blake [1] who +<br/>creatively used particle filters for visual tracking, many +</td><td></td><td>Email: su@cs.zju.edu.cn +<br/>Email: lihuang@cs.zju.edu.cn +</td></tr><tr><td>6b333b2c6311e36c2bde920ab5813f8cfcf2b67b</td><td></td><td></td><td></td></tr><tr><td>6b3e360b80268fda4e37ff39b7f303e3684e8719</td><td>FACE RECOGNITION FROM SKETCHES USING ADVANCED +<br/>CORRELATION FILTERS USING HYBRID EIGENANALYSIS +<br/>FOR FACE SYNTHESIS +<br/><b>Language Technology Institute, Carnegie Mellon Universty</b><br/><b>Carnegie Mellon University</b><br/>Keywords: +<br/>Face from sketch synthesis, face recognition, eigenface, advanced correlation filters, OTSDF. +</td><td>('3036546', 'Yung-hui Li', 'yung-hui li')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td></td></tr><tr><td>6b9aa288ce7740ec5ce9826c66d059ddcfd8dba9</td><td></td><td></td><td></td></tr><tr><td>6bcfcc4a0af2bf2729b5bc38f500cfaab2e653f0</td><td>Facial expression recognition in the wild using improved dense trajectories and <br/>Fisher vector encoding <br/><b>Computational Science and Engineering Program, Bo gazic i University, Istanbul, Turkey</b><br/><b>Bo gazic i University, Istanbul, Turkey</b></td><td>('2471932', 'Sadaf Afshar', 'sadaf afshar')<br/>('1764521', 'Albert Ali Salah', 'albert ali salah')</td><td>{sadaf.afshar, salah}@boun.edu.tr </td></tr><tr><td>6bca0d1f46b0f7546ad4846e89b6b842d538ee4e</td><td>FACE RECOGNITION FROM SURVEILLANCE-QUALITY VIDEO @@ -19413,7 +24526,12 @@ <br/>JANUARY 2012 <br/>Centre du Parc, Rue Marconi 19, P.O. Box 592, CH - 1920 Martigny </td><td>('1843477', 'Roy Wallace', 'roy wallace')<br/>('1698382', 'Sébastien Marcel', 'sébastien marcel')</td><td>T +41 27 721 77 11 F +41 27 721 77 12 info@idiap.ch www.idiap.ch -</td></tr><tr><td>6be0ab66c31023762e26d309a4a9d0096f72a7f0</td><td>Enhance Visual Recognition under Adverse +</td></tr><tr><td>6b8d0569fffce5cc221560d459d6aa10c4db2f03</td><td>Interlinked Convolutional Neural Networks for +<br/>Face Parsing +<br/>State Key Laboratory of Intelligent Technology and Systems +<br/>Tsinghua National Laboratory for Information Science and Technology (TNList) +<br/>Department of Computer Science and Technology +<br/><b>Tsinghua University, Beijing 100084, China</b></td><td>('1879713', 'Yisu Zhou', 'yisu zhou')<br/>('1705418', 'Xiaolin Hu', 'xiaolin hu')<br/>('49846744', 'Bo Zhang', 'bo zhang')</td><td></td></tr><tr><td>6be0ab66c31023762e26d309a4a9d0096f72a7f0</td><td>Enhance Visual Recognition under Adverse <br/>Conditions via Deep Networks </td><td>('1771885', 'Ding Liu', 'ding liu')<br/>('2392101', 'Bowen Cheng', 'bowen cheng')<br/>('2969311', 'Zhangyang Wang', 'zhangyang wang')<br/>('40479011', 'Haichao Zhang', 'haichao zhang')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>6bcee7dba5ed67b3f9926d2ae49f9a54dee64643</td><td>Assessment of Time Dependency in Face Recognition: <br/>An Initial Study @@ -19497,7 +24615,20 @@ <br/>This Technical Report is brought to you for free and open access by the School of Computer Science at Research Showcase @ CMU. It has been <br/>accepted for inclusion in Language Technologies Institute by an authorized administrator of Research Showcase @ CMU. For more information, please <br/>contact research-showcase@andrew.cmu.edu. -</td></tr><tr><td>6bb630dfa797168e6627d972560c3d438f71ea99</td><td></td><td></td><td></td></tr><tr><td>0729628db4bb99f1f70dd6cb2353d7b76a9fce47</td><td>Separating Pose and Expression in Face Images: +</td></tr><tr><td>6bb630dfa797168e6627d972560c3d438f71ea99</td><td></td><td></td><td></td></tr><tr><td>6b6ff9d55e1df06f8b3e6f257e23557a73b2df96</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 61– No.17, January 2013 +<br/>Survey of Threats to the Biometric Authentication +<br/>Systems and Solutions +<br/>Research Scholor,Mewar +<br/><b>University, Chitorgarh. (INDIA</b><br/>P.C.Gupta +<br/><b>Kota University, Kota(INDIA</b><br/>Khushboo Mantri +<br/><b>M.tech.student, Arya College of</b><br/>engineering ,Jaipur(INDIA) +</td><td>('2875951', 'Sarika Khandelwal', 'sarika khandelwal')</td><td></td></tr><tr><td>07377c375ac76a34331c660fe87ebd7f9b3d74c4</td><td>Detailed Human Avatars from Monocular Video +<br/>1Computer Graphics Lab, TU Braunschweig, Germany +<br/><b>Max Planck Institute for Informatics, Saarland Informatics Campus, Germany</b><br/>Figure 1: Our method creates a detailed avatar from a monocular video of a person turning around. Based on the SMPL +<br/>model, we first compute a medium-level avatar, then add subject-specific details and finally generate a seamless texture. +</td><td>('1914886', 'Thiemo Alldieck', 'thiemo alldieck')<br/>('9765909', 'Weipeng Xu', 'weipeng xu')</td><td>{alldieck,magnor}@cg.cs.tu-bs.de {wxu,theobalt,gpons}@mpi-inf.mpg.de +</td></tr><tr><td>0729628db4bb99f1f70dd6cb2353d7b76a9fce47</td><td>Separating Pose and Expression in Face Images: <br/>A Manifold Learning Approach <br/><b>University of Pennsylvania</b><br/>Moore Bldg, 200 South 33rd St, Philadelphia, PA 19104, USA <br/>(Submitted on December 27, 2006) @@ -19544,7 +24675,11 @@ <br/>fayyaz@iai.uni-bonn.de, vivek.sharma@kit.edu </td></tr><tr><td>0754e769eb613fd3968b6e267a301728f52358be</td><td>Towards a Watson That Sees: Language-Guided Action Recognition for <br/>Robots -</td><td>('7607499', 'Yezhou Yang', 'yezhou yang')<br/>('1697493', 'Yiannis Aloimonos', 'yiannis aloimonos')</td><td></td></tr><tr><td>0773c320713dae62848fceac5a0ac346ba224eca</td><td>Digital Facial Augmentation for Interactive +</td><td>('7607499', 'Yezhou Yang', 'yezhou yang')<br/>('1697493', 'Yiannis Aloimonos', 'yiannis aloimonos')</td><td></td></tr><tr><td>07c83f544d0604e6bab5d741b0bf9a3621d133da</td><td>Learning Spatio-Temporal Features with 3D Residual Networks +<br/>for Action Recognition +<br/><b>National Institute of Advanced Industrial Science and Technology (AIST</b><br/>Tsukuba, Ibaraki, Japan +</td><td>('2199251', 'Kensho Hara', 'kensho hara')<br/>('1730200', 'Hirokatsu Kataoka', 'hirokatsu kataoka')<br/>('1732705', 'Yutaka Satoh', 'yutaka satoh')</td><td>{kensho.hara, hirokatsu.kataoka, yu.satou}@aist.go.jp +</td></tr><tr><td>0773c320713dae62848fceac5a0ac346ba224eca</td><td>Digital Facial Augmentation for Interactive <br/>Entertainment <br/>Centre for Intelligent Machines <br/><b>McGill University</b><br/>Montreal, Quebec, Canada @@ -19567,11 +24702,17 @@ <br/>Robust Face Recognition and Tagging in Visual Surveillance <br/>System </td><td>('21008397', 'Kavitha MS', 'kavitha ms')<br/>('39546266', 'Siva Pradeepa', 'siva pradeepa')<br/>('21008397', 'Kavitha MS', 'kavitha ms')<br/>('39546266', 'Siva Pradeepa', 'siva pradeepa')</td><td>e-mail:kavithams999@gmail.com +</td></tr><tr><td>07fa153b8e6196ee6ef6efd8b743de8485a07453</td><td>Action Prediction from Videos via Memorizing Hard-to-Predict Samples +<br/><b>Northeastern University, Boston, MA, USA</b><br/><b>College of Engineering, Northeastern University, Boston, MA, USA</b><br/><b>College of Computer and Information Science, Northeastern University, Boston, MA, USA</b></td><td>('48901920', 'Yu Kong', 'yu kong')<br/>('9355577', 'Shangqian Gao', 'shangqian gao')<br/>('47935056', 'Bin Sun', 'bin sun')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td>{yukong,yunfu}@ece.neu.edu, {gao.sh,sun.bi}@husky.neu.edu </td></tr><tr><td>0708059e3bedbea1cbfae1c8cd6b7259d4b56b5b</td><td>Graph-regularized Multi-class Support Vector <br/>Machines for Face and Action Recognition <br/><b>Tampere University of Technology, Tampere, Finland</b></td><td>('9219875', 'Moncef Gabbouj', 'moncef gabbouj')</td><td>Email: {alexandros.iosifidis,moncef.gabbouj}@tut.fi </td></tr><tr><td>074af31bd9caa61fea3c4216731420bd7c08b96a</td><td>Face Verification Using Sparse Representations <br/><b>Institute for Advanced Computer Studies, University of Maryland, College Park, MD</b><br/><b>TNLIST, Tsinghua University, Beijing, 100084, China</b></td><td>('2723427', 'Huimin Guo', 'huimin guo')<br/>('3373117', 'Ruiping Wang', 'ruiping wang')<br/>('3826759', 'Jonghyun Choi', 'jonghyun choi')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td>{hmguo, jhchoi, lsd}@umiacs.umd.edu, rpwang@tsinghua.edu.cn +</td></tr><tr><td>0750a816858b601c0dbf4cfb68066ae7e788f05d</td><td>CosFace: Large Margin Cosine Loss for Deep Face Recognition +<br/>Tencent AI Lab +</td><td>('39049654', 'Hao Wang', 'hao wang')<br/>('1996677', 'Yitong Wang', 'yitong wang')<br/>('48741267', 'Zheng Zhou', 'zheng zhou')<br/>('3478009', 'Xing Ji', 'xing ji')<br/>('2856494', 'Dihong Gong', 'dihong gong')<br/>('2263912', 'Jingchao Zhou', 'jingchao zhou')<br/>('1911510', 'Zhifeng Li', 'zhifeng li')<br/>('46641573', 'Wei Liu', 'wei liu')</td><td>{hawelwang,yitongwang,encorezhou,denisji,sagazhou,michaelzfli}@tencent.com +<br/>gongdihong@gmail.com wliu@ee.columbia.edu </td></tr><tr><td>078d507703fc0ac4bf8ca758be101e75ea286c80</td><td> ISSN: 2321-8169 <br/>International Journal on Recent and Innovation Trends in Computing and Communication <br/>Volume: 3 Issue: 8 @@ -19682,7 +24823,25 @@ <br/><b>University of Piraeus</b><br/>Karaoli & Dimitriou 80, Piraeus 185 34 <br/>GREECE </td><td>('2828175', 'Ioanna-Ourania Stathopoulou', 'ioanna-ourania stathopoulou')<br/>('1802584', 'George A. Tsihrintzis', 'george a. tsihrintzis')</td><td>phone: + 30 210 4142322, fax: + 30 210 4142264, email: {iostath, geoatsi}@unipi.gr -</td></tr><tr><td>385750bcf95036c808d63db0e0b14768463ff4c6</td><td></td><td></td><td></td></tr><tr><td>3852968082a16db8be19b4cb04fb44820ae823d4</td><td>Unsupervised Learning of Long-Term Motion Dynamics for Videos +</td></tr><tr><td>3803b91e784922a2dacd6a18f61b3100629df932</td><td>Temporal Multimodal Fusion +<br/>for Video Emotion Classification in the Wild +<br/>Orange Labs +<br/>Cesson-Sévigné, France +<br/>Orange Labs +<br/>Cesson-Sévigné, France +<br/>Normandie Univ., UNICAEN, +<br/>ENSICAEN, CNRS +<br/>Caen, France +</td><td>('26339425', 'Valentin Vielzeuf', 'valentin vielzeuf')<br/>('2642628', 'Stéphane Pateux', 'stéphane pateux')<br/>('1801809', 'Frédéric Jurie', 'frédéric jurie')</td><td>valentin.vielzeuf@orange.com +<br/>stephane.pateux@orange.com +<br/>frederic.jurie@unicaen.fr +</td></tr><tr><td>38eea307445a39ee7902c1ecf8cea7e3dcb7c0e7</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Multi-distance Support Matrix Machine +<br/>Received: date / Accepted: date +</td><td>('34679353', 'Yunfei Ye', 'yunfei ye')<br/>('49405675', 'Dong Han', 'dong han')</td><td></td></tr><tr><td>38c901a58244be9a2644d486f9a1284dc0edbf8a</td><td>Multi-Camera Action Dataset for Cross-Camera Action Recognition +<br/>Benchmarking +<br/><b>School of Electronic Information Engineering, Tianjin University, China</b><br/><b>Interactive and Digital Media Institute, National University of Singapore, Singapore</b><br/><b>School of Computing, National University of Singapore, Singapore</b></td><td>('1803305', 'Wenhui Li', 'wenhui li')<br/>('3026404', 'Yongkang Wong', 'yongkang wong')<br/>('1678662', 'Yang Li', 'yang li')</td><td></td></tr><tr><td>385750bcf95036c808d63db0e0b14768463ff4c6</td><td></td><td></td><td></td></tr><tr><td>3852968082a16db8be19b4cb04fb44820ae823d4</td><td>Unsupervised Learning of Long-Term Motion Dynamics for Videos <br/><b>Stanford University</b></td><td>('3378742', 'Zelun Luo', 'zelun luo')<br/>('3378457', 'Boya Peng', 'boya peng')<br/>('38485317', 'De-An Huang', 'de-an huang')<br/>('3304525', 'Alexandre Alahi', 'alexandre alahi')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td>{zelunluo,boya,dahuang,alahi,feifeili}@cs.stanford.edu </td></tr><tr><td>38cc2f1c13420170c7adac30f9dfac69b297fb76</td><td><b>Rochester Institute of Technology</b><br/>RIT Scholar Works <br/>Theses @@ -19703,11 +24862,17 @@ <br/>Multi-Fold Gabor, PCA and ICA Filter <br/>Convolution Descriptor for Face Recognition <br/> -</td><td>('1801904', 'Andrew Beng Jin Teoh', 'andrew beng jin teoh')<br/>('3326176', 'Cong Jie Ng', 'cong jie ng')</td><td></td></tr><tr><td>38f06a75eb0519ae1d4582a86ef4730cc8fb8d7f</td><td>Shrinkage Expansion Adaptive Metric Learning +</td><td>('1801904', 'Andrew Beng Jin Teoh', 'andrew beng jin teoh')<br/>('3326176', 'Cong Jie Ng', 'cong jie ng')</td><td></td></tr><tr><td>38f1fac3ed0fd054e009515e7bbc72cdd4cf801a</td><td>Finding Person Relations in Image Data of the +<br/>Internet Archive +<br/>Eric M¨uller-Budack1,2[0000−0002−6802−1241], +<br/>1 Leibniz Information Centre for Science and Technology (TIB), Hannover, Germany +<br/><b>L3S Research Center, Leibniz Universit at Hannover, Germany</b></td><td>('51008013', 'Kader Pustu-Iren', 'kader pustu-iren')<br/>('50983345', 'Sebastian Diering', 'sebastian diering')<br/>('1738703', 'Ralph Ewerth', 'ralph ewerth')</td><td></td></tr><tr><td>38f06a75eb0519ae1d4582a86ef4730cc8fb8d7f</td><td>Shrinkage Expansion Adaptive Metric Learning <br/>1 School of Information and Communications Engineering, <br/><b>Dalian University of Technology, China</b><br/><b>School of Computer Science and Technology, Harbin Institute of Technology, China</b><br/><b>Hong Kong Polytechnic University, Hong Kong</b></td><td>('2769011', 'Qilong Wang', 'qilong wang')<br/>('1724520', 'Wangmeng Zuo', 'wangmeng zuo')<br/>('36685537', 'Lei Zhang', 'lei zhang')<br/>('40426020', 'Peihua Li', 'peihua li')</td><td>{csqlwang,cswmzuo}@gmail.com, cslzhang@comp.polyu.edu.hk, <br/>peihuali@dlut.edu.cn -</td></tr><tr><td>384945abd53f6a6af51faf254ba8ef0f0fb3f338</td><td>Visual Recognition with Humans in the Loop +</td></tr><tr><td>380d5138cadccc9b5b91c707ba0a9220b0f39271</td><td>Deep Imbalanced Learning for Face Recognition +<br/>and Attribute Prediction +</td><td>('2000034', 'Chen Huang', 'chen huang')<br/>('47002704', 'Yining Li', 'yining li')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>384945abd53f6a6af51faf254ba8ef0f0fb3f338</td><td>Visual Recognition with Humans in the Loop <br/><b>University of California, San Diego</b><br/><b>California Institute of Technology</b></td><td>('3251767', 'Steve Branson', 'steve branson')<br/>('2367820', 'Catherine Wah', 'catherine wah')<br/>('2490700', 'Boris Babenko', 'boris babenko')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>{sbranson,cwah,gschroff,bbabenko,sjb}@cs.ucsd.edu <br/>{welinder,perona}@caltech.edu </td></tr><tr><td>38215c283ce4bf2c8edd597ab21410f99dc9b094</td><td>The SEMAINE Database: Annotated Multimodal Records of @@ -19789,7 +24954,7 @@ </td></tr><tr><td>3802da31c6d33d71b839e260f4022ec4fbd88e2d</td><td>Deep Attributes for One-Shot Face Recognition <br/><b>Xerox Research Center India</b><br/>3Department of Electrical Engineering, IIT Kanpur </td><td>('5060928', 'Aishwarya Jadhav', 'aishwarya jadhav')<br/>('1744135', 'Vinay P. Namboodiri', 'vinay p. namboodiri')<br/>('1797662', 'K. S. Venkatesh', 'k. s. venkatesh')</td><td>aishwaryauj@gmail.com, vinaypn@iitk.ac.in, venkats@iitk.ac.in -</td></tr><tr><td>00f7f7b72a92939c36e2ef9be97397d8796ee07c</td><td>3D ConvNets with Optical Flow Based Regularization +</td></tr><tr><td>00fb2836068042c19b5197d0999e8e93b920eb9c</td><td></td><td></td><td></td></tr><tr><td>00f7f7b72a92939c36e2ef9be97397d8796ee07c</td><td>3D ConvNets with Optical Flow Based Regularization <br/><b>Stanford University</b><br/>Stanford, CA </td><td>('35627656', 'Kevin Chavez', 'kevin chavez')</td><td>kjchavez@stanford.edu </td></tr><tr><td>0021f46bda27ea105d722d19690f5564f2b8869e</td><td>Deep Region and Multi-label Learning for Facial Action Unit Detection @@ -19878,7 +25043,7 @@ </td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('1967060', 'Philippe Dreuw', 'philippe dreuw')</td><td></td></tr><tr><td>004e3292885463f97a70e1f511dc476289451ed5</td><td>Quadruplet-wise Image Similarity Learning <br/>Marc T. Law <br/><b>LIP6, UPMC - Sorbonne University, Paris, France</b></td><td>('1728523', 'Nicolas Thome', 'nicolas thome')<br/>('1702233', 'Matthieu Cord', 'matthieu cord')</td><td>{Marc.Law, Nicolas.Thome, Matthieu.Cord}@lip6.fr -</td></tr><tr><td>00b08d22abc85361e1c781d969a1b09b97bc7010</td><td>Who is the Hero? − Semi-Supervised Person Re-Identification in Videos +</td></tr><tr><td>0004f72a00096fa410b179ad12aa3a0d10fc853c</td><td></td><td></td><td></td></tr><tr><td>00b08d22abc85361e1c781d969a1b09b97bc7010</td><td>Who is the Hero? − Semi-Supervised Person Re-Identification in Videos <br/><b>Tampere University of Technology, Tampere, Finland</b><br/><b>Nokia Research Center, Tampere, Finland</b><br/>Keywords: <br/>Semi-supervised person re-identification, Important person detection, Face tracks, Clustering </td><td>('13413642', 'Umar Iqbal', 'umar iqbal')<br/>('9219875', 'Moncef Gabbouj', 'moncef gabbouj')</td><td>{umar.iqbal, moncef.gabbouj}@tut.fi, igor.curcio@nokia.com @@ -20029,9 +25194,26 @@ <br/>NSF-REU Site at UNC Wilmington, Summer 2017 </td><td>('39845059', 'G. Bingham', 'g. bingham')<br/>('1693470', 'B. Yip', 'b. yip')<br/>('1833570', 'M. Ferguson', 'm. ferguson')<br/>('1693283', 'C. Chen', 'c. chen')<br/>('11134292', 'Y. Wang', 'y. wang')<br/>('3369885', 'T. Kling', 't. kling')</td><td></td></tr><tr><td>6eaf446dec00536858548fe7cc66025b70ce20eb</td><td></td><td></td><td></td></tr><tr><td>6e173ad91b288418c290aa8891193873933423b3</td><td>Are you from North or South India? A hard race classification task reveals <br/>systematic representational differences between humans and machines -<br/><b>aCentre for Neuroscience, Indian Institute of Science, Bangalore, India</b></td><td>('2478739', 'Harish Katti', 'harish katti')</td><td></td></tr><tr><td>6eba25166fe461dc388805cc2452d49f5d1cdadd</td><td>Pages 122.1-122.12 +<br/><b>aCentre for Neuroscience, Indian Institute of Science, Bangalore, India</b></td><td>('2478739', 'Harish Katti', 'harish katti')</td><td></td></tr><tr><td>6e91be2ad74cf7c5969314b2327b513532b1be09</td><td>Dimensionality Reduction with Subspace Structure +<br/>Preservation +<br/>Department of Computer Science +<br/>SUNY Buffalo +<br/>Buffalo, NY 14260 +</td><td>('2309967', 'Devansh Arpit', 'devansh arpit')<br/>('1841118', 'Ifeoma Nwogu', 'ifeoma nwogu')<br/>('1723877', 'Venu Govindaraju', 'venu govindaraju')</td><td>{devansh,inwogua,govind}@buffalo.edu +</td></tr><tr><td>6eba25166fe461dc388805cc2452d49f5d1cdadd</td><td>Pages 122.1-122.12 <br/>DOI: https://dx.doi.org/10.5244/C.30.122 -</td><td></td><td></td></tr><tr><td>6ed738ff03fd9042965abdfaa3ed8322de15c116</td><td>This document is downloaded from DR-NTU, Nanyang Technological +</td><td></td><td></td></tr><tr><td>6e8a81d452a91f5231443ac83e4c0a0db4579974</td><td>Illumination robust face representation based on intrinsic geometrical +<br/>information +<br/>Soyel, H; Ozmen, B; McOwan, PW +<br/>This is a pre-copyedited, author-produced PDF of an article accepted for publication in IET +<br/>Conference on Image Processing (IPR 2012). The version of record is available +<br/>http://ieeexplore.ieee.org/document/6290632/?arnumber=6290632&tag=1 +<br/>For additional information about this publication click this link. +<br/>http://qmro.qmul.ac.uk/xmlui/handle/123456789/16147 +<br/>Information about this research object was correct at the time of download; we occasionally +<br/>make corrections to records, please therefore check the published record when citing. For +</td><td></td><td>more information contact scholarlycommunications@qmul.ac.uk +</td></tr><tr><td>6ed738ff03fd9042965abdfaa3ed8322de15c116</td><td>This document is downloaded from DR-NTU, Nanyang Technological <br/><b>University Library, Singapore</b><br/>Title <br/>K-MEAP: Generating Specified K Clusters with Multiple <br/>Exemplars by Efficient Affinity Propagation @@ -20114,7 +25296,14 @@ <br/>Andr´e Uschmajew </td><td>('2391697', 'Yuji Nakatsukasa', 'yuji nakatsukasa')</td><td></td></tr><tr><td>6ef1996563835b4dfb7fda1d14abe01c8bd24a05</td><td>Nonparametric Part Transfer for Fine-grained Recognition <br/><b>Computer Vision Group, Friedrich Schiller University Jena</b><br/>www.inf-cv.uni-jena.de -</td><td>('1679449', 'Erik Rodner', 'erik rodner')<br/>('1720839', 'Alexander Freytag', 'alexander freytag')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td></td></tr><tr><td>6ee8a94ccba10062172e5b31ee097c846821a822</td><td>Submitted 3/13; Revised 10/13; Published 12/13 +</td><td>('1679449', 'Erik Rodner', 'erik rodner')<br/>('1720839', 'Alexander Freytag', 'alexander freytag')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td></td></tr><tr><td>6e8c3b7d25e6530a631ea01fbbb93ac1e8b69d2f</td><td>Deep Episodic Memory: Encoding, Recalling, and Predicting +<br/>Episodic Experiences for Robot Action Execution +</td><td>('35309584', 'Jonas Rothfuss', 'jonas rothfuss')<br/>('2128564', 'Fabio Ferreira', 'fabio ferreira')<br/>('34876449', 'Eren Erdal Aksoy', 'eren erdal aksoy')<br/>('46432716', 'You Zhou', 'you zhou')<br/>('1722677', 'Tamim Asfour', 'tamim asfour')</td><td></td></tr><tr><td>6e911227e893d0eecb363015754824bf4366bdb7</td><td>Wasserstein Divergence for GANs +<br/>1 Computer Vision Lab, ETH Zurich, Switzerland +<br/>2 VISICS, KU Leuven, Belgium +</td><td>('1839268', 'Jiqing Wu', 'jiqing wu')<br/>('7945869', 'Zhiwu Huang', 'zhiwu huang')<br/>('30691454', 'Janine Thoma', 'janine thoma')<br/>('32610154', 'Dinesh Acharya', 'dinesh acharya')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>{jwu,zhiwu.huang,jthoma,vangool}@vision.ee.ethz.ch, +<br/>acharyad@student.ethz.ch +</td></tr><tr><td>6ee8a94ccba10062172e5b31ee097c846821a822</td><td>Submitted 3/13; Revised 10/13; Published 12/13 <br/>How to Solve Classification and Regression Problems on <br/>High-Dimensional Data with a Supervised <br/>Extension of Slow Feature Analysis @@ -20325,7 +25514,12 @@ <br/>1Neutral expression is not included. <br/>2Please see http://vdb.kyb.tuebingen.mpg.de/. <br/>3Please see http://bml.ym.edu.tw/ download/html/news.htm. -</td><td></td><td></td></tr><tr><td>6e94c579097922f4bc659dd5d6c6238a428c4d22</td><td>Graph Based Multi-class Semi-supervised +</td><td></td><td></td></tr><tr><td>6e00a406edb508312108f683effe6d3c1db020fb</td><td>Faces as Lighting Probes via Unsupervised Deep +<br/>Highlight Extraction +<br/><b>Simon Fraser University, Burnaby, Canada</b><br/><b>National University of Defense Technology, Changsha, China</b><br/>3 Microsoft Research, Beijing, China +</td><td>('2693616', 'Renjiao Yi', 'renjiao yi')<br/>('2041096', 'Chenyang Zhu', 'chenyang zhu')<br/>('37291674', 'Ping Tan', 'ping tan')<br/>('1686911', 'Stephen Lin', 'stephen lin')</td><td>{renjiaoy, cza68, pingtan}@sfu.ca +<br/>stevelin@microsoft.com +</td></tr><tr><td>6e94c579097922f4bc659dd5d6c6238a428c4d22</td><td>Graph Based Multi-class Semi-supervised <br/>Learning Using Gaussian Process <br/>State Key Laboratory of Intelligent Technology and Systems, <br/><b>Tsinghua University, Beijing, China</b></td><td>('1809614', 'Yangqiu Song', 'yangqiu song')<br/>('1700883', 'Changshui Zhang', 'changshui zhang')<br/>('1760678', 'Jianguo Lee', 'jianguo lee')</td><td>{songyq99, lijg01}@mails.tsinghua.edu.cn, zcs@mail.tsinghua.edu.cn @@ -20520,19 +25714,34 @@ </td></tr><tr><td>9ac15845defcd0d6b611ecd609c740d41f0c341d</td><td>Copyright <br/>by <br/>2011 -</td><td>('1926834', 'Juhyun Lee', 'juhyun lee')</td><td></td></tr><tr><td>9af1cf562377b307580ca214ecd2c556e20df000</td><td>Feb. 28 +</td><td>('1926834', 'Juhyun Lee', 'juhyun lee')</td><td></td></tr><tr><td>9ac43a98fe6fde668afb4fcc115e4ee353a6732d</td><td>Survey of Face Detection on Low-quality Images +<br/><b>Beckmann Institute, University of Illinois at Urbana-Champaign, USA</b></td><td>('1698743', 'Yuqian Zhou', 'yuqian zhou')<br/>('1771885', 'Ding Liu', 'ding liu')</td><td>{yuqian2, dingliu2}@illinois.edu +<br/>huang@ifp.uiuc.edu +</td></tr><tr><td>9af1cf562377b307580ca214ecd2c556e20df000</td><td>Feb. 28 <br/> International Journal of Advanced Studies in Computer Science and Engineering <br/>IJASCSE, Volume 4, Issue 2, 2015 <br/> Video-Based Facial Expression Recognition <br/>Using Local Directional Binary Pattern <br/>Electrical Engineering Dept., AmirKabir Univarsity of Technology <br/>Tehran, Iran -</td><td>('38519671', 'Sahar Hooshmand', 'sahar hooshmand')<br/>('3232144', 'Ali Jamali Avilaq', 'ali jamali avilaq')<br/>('3293075', 'Amir Hossein Rezaie', 'amir hossein rezaie')</td><td></td></tr><tr><td>9a4c45e5c6e4f616771a7325629d167a38508691</td><td>A Facial Features Detector Integrating Holistic Facial Information and +</td><td>('38519671', 'Sahar Hooshmand', 'sahar hooshmand')<br/>('3232144', 'Ali Jamali Avilaq', 'ali jamali avilaq')<br/>('3293075', 'Amir Hossein Rezaie', 'amir hossein rezaie')</td><td></td></tr><tr><td>9a23a0402ae68cc6ea2fe0092b6ec2d40f667adb</td><td>High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs +<br/>1NVIDIA Corporation +<br/>2UC Berkeley +<br/>Figure 1: We propose a generative adversarial framework for synthesizing 2048 × 1024 images from semantic label maps +<br/>(lower left corner in (a)). Compared to previous work [5], our results express more natural textures and details. (b) We can +<br/>change labels in the original label map to create new scenes, like replacing trees with buildings. (c) Our framework also +<br/>allows a user to edit the appearance of individual objects in the scene, e.g. changing the color of a car or the texture of a road. +<br/>Please visit our website for more side-by-side comparisons as well as interactive editing demos. +</td><td>('2195314', 'Ting-Chun Wang', 'ting-chun wang')<br/>('2436356', 'Jun-Yan Zhu', 'jun-yan zhu')<br/>('1690538', 'Jan Kautz', 'jan kautz')</td><td></td></tr><tr><td>9a4c45e5c6e4f616771a7325629d167a38508691</td><td>A Facial Features Detector Integrating Holistic Facial Information and <br/>Part-based Model <br/>Eslam Mostafa1,2 <br/>Aly Farag1 <br/><b>CVIP Lab, University of Louisville, Louisville, KY 40292, USA</b><br/><b>Alexandria University, Alexandria, Egypt</b><br/><b>Assiut University, Assiut 71515, Egypt</b><br/>4Kentucky Imaging Technology (KIT), Louisville, KY 40245, USA. -</td><td>('28453046', 'Asem A. Ali', 'asem a. ali')<br/>('2239392', 'Ahmed Shalaby', 'ahmed shalaby')</td><td></td></tr><tr><td>9a7858eda9b40b16002c6003b6db19828f94a6c6</td><td>MOONEY FACE CLASSIFICATION AND PREDICTION BY LEARNING ACROSS TONE +</td><td>('28453046', 'Asem A. Ali', 'asem a. ali')<br/>('2239392', 'Ahmed Shalaby', 'ahmed shalaby')</td><td></td></tr><tr><td>9af9a88c60d9e4b53e759823c439fc590a4b5bc5</td><td>Learning Deep Convolutional Embeddings for Face Representation Using Joint +<br/>Sample- and Set-based Supervision +<br/>Department of Electrical and Electronic Engineering, +<br/><b>Imperial College London</b></td><td>('2151914', 'Baris Gecer', 'baris gecer')<br/>('3288623', 'Vassileios Balntas', 'vassileios balntas')<br/>('1700968', 'Tae-Kyun Kim', 'tae-kyun kim')</td><td>{b.gecer,v.balntas15,tk.kim}@imperial.ac.uk +</td></tr><tr><td>9a7858eda9b40b16002c6003b6db19828f94a6c6</td><td>MOONEY FACE CLASSIFICATION AND PREDICTION BY LEARNING ACROSS TONE <br/>(cid:63) UC Berkeley / †ICSI </td><td>('2301765', 'Tsung-Wei Ke', 'tsung-wei ke')<br/>('2251428', 'Stella X. Yu', 'stella x. yu')<br/>('1821337', 'David Whitney', 'david whitney')</td><td></td></tr><tr><td>9a3535cabf5d0f662bff1d897fb5b777a412d82e</td><td><b>University of Kentucky</b><br/>UKnowledge <br/>Computer Science @@ -20565,13 +25774,26 @@ <br/>mfrank83@buffalo.edu </td></tr><tr><td>9a42c519f0aaa68debbe9df00b090ca446d25bc4</td><td>Face Recognition via Centralized Coordinate <br/>Learning -</td><td>('2689287', 'Xianbiao Qi', 'xianbiao qi')<br/>('1684635', 'Lei Zhang', 'lei zhang')</td><td></td></tr><tr><td>36b40c75a3e53c633c4afb5a9309d10e12c292c7</td><td></td><td></td><td></td></tr><tr><td>363ca0a3f908859b1b55c2ff77cc900957653748</td><td>International Journal of Computer Trends and Technology (IJCTT) – volume 1 Issue 3 Number 4 – Aug 2011 +</td><td>('2689287', 'Xianbiao Qi', 'xianbiao qi')<br/>('1684635', 'Lei Zhang', 'lei zhang')</td><td></td></tr><tr><td>9aad8e52aff12bd822f0011e6ef85dfc22fe8466</td><td>Temporal-Spatial Mapping for Action Recognition +</td><td>('3865974', 'Xiaolin Song', 'xiaolin song')<br/>('40093162', 'Cuiling Lan', 'cuiling lan')<br/>('8434337', 'Wenjun Zeng', 'wenjun zeng')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('1759461', 'Jingyu Yang', 'jingyu yang')<br/>('1692735', 'Xiaoyan Sun', 'xiaoyan sun')</td><td></td></tr><tr><td>36b40c75a3e53c633c4afb5a9309d10e12c292c7</td><td></td><td></td><td></td></tr><tr><td>363ca0a3f908859b1b55c2ff77cc900957653748</td><td>International Journal of Computer Trends and Technology (IJCTT) – volume 1 Issue 3 Number 4 – Aug 2011 <br/> Local Binary Patterns and Linear Programming using <br/>Facial Expression <br/>Ms.P.Jennifer <br/><b>Bharath Institute of Science and Technology</b><br/><b>B.Tech (C.S.E), Bharath University, Chennai</b><br/>Dr. A. Muthu kumaravel <br/><b>Bharath Institute of Science and Technology</b><br/><b>B.Tech (C.S.E), Bharath University, Chennai</b><br/> -</td><td></td><td></td></tr><tr><td>365f67fe670bf55dc9ccdcd6888115264b2a2c56</td><td></td><td></td><td></td></tr><tr><td>36fe39ed69a5c7ff9650fd5f4fe950b5880760b0</td><td>Tracking von Gesichtsmimik +</td><td></td><td></td></tr><tr><td>36939e6a365e9db904d81325212177c9e9e76c54</td><td>Assessing the Accuracy of Four Popular Face Recognition Tools for +<br/>Inferring Gender, Age, and Race +<br/><b>Qatar Computing Research Institute, HBKU</b><br/>HBKU Research Complex, Doha, P.O. Box 34110, Qatar +</td><td>('1861541', 'Soon-Gyo Jung', 'soon-gyo jung')<br/>('40660541', 'Jisun An', 'jisun an')<br/>('2592694', 'Haewoon Kwak', 'haewoon kwak')<br/>('2734912', 'Joni Salminen', 'joni salminen')</td><td>{sjung,jan,hkwak,jsalminen,bjansen}@hbku.edu.qa +</td></tr><tr><td>3646b42511a6a0df5470408bc9a7a69bb3c5d742</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Applications of Computers and Electronics for the Welfare of Rural Masses (ACEWRM) 2015 +<br/>Detection of Facial Parts based on ABLATA +<br/>Technical Campus, Bhilai +<br/>Vikas Singh +<br/>Technical Campus, Bhilai +<br/>Abha Choubey +<br/>Technical Campus, Bhilai +</td><td>('9173769', 'Siddhartha Choubey', 'siddhartha choubey')</td><td></td></tr><tr><td>365f67fe670bf55dc9ccdcd6888115264b2a2c56</td><td></td><td></td><td></td></tr><tr><td>36fe39ed69a5c7ff9650fd5f4fe950b5880760b0</td><td>Tracking von Gesichtsmimik <br/>mit Hilfe von Gitterstrukturen <br/>zur Klassifikation von schmerzrelevanten Action <br/>Units @@ -20624,7 +25846,36 @@ <br/>network using constructive training algorithm <br/>Received: 5 February 2014 / Revised: 22 August 2014 / Accepted: 13 October 2014 <br/>© Springer Science+Business Media New York 2014 -</td><td>('1746834', 'Hayet Boughrara', 'hayet boughrara')<br/>('3410172', 'Chokri Ben Amar', 'chokri ben amar')</td><td></td></tr><tr><td>360d66e210f7011423364327b7eccdf758b5fdd2</td><td>17th European Signal Processing Conference (EUSIPCO 2009) +</td><td>('1746834', 'Hayet Boughrara', 'hayet boughrara')<br/>('3410172', 'Chokri Ben Amar', 'chokri ben amar')</td><td></td></tr><tr><td>3674f3597bbca3ce05e4423611d871d09882043b</td><td>ISSN 1796-2048 +<br/>Volume 7, Number 4, August 2012 +<br/>Contents +<br/>Special Issue: Multimedia Contents Security in Social Networks Applications +<br/>Guest Editors: Zhiyong Zhang and Muthucumaru Maheswaran +<br/>Guest Editorial +<br/>Zhiyong Zhang and Muthucumaru Maheswaran +<br/>SPECIAL ISSUE PAPERS +<br/>DRTEMBB: Dynamic Recommendation Trust Evaluation Model Based on Bidding +<br/>Gang Wang and Xiao-lin Gui +<br/>Block-Based Parallel Intra Prediction Scheme for HEVC +<br/>Jie Jiang, Baolong, Wei Mo, and Kefeng Fan +<br/>Optimized LSB Matching Steganography Based on Fisher Information +<br/>Yi-feng Sun, Dan-mei Niu, Guang-ming Tang, and Zhan-zhan Gao +<br/>A Novel Robust Zero-Watermarking Scheme Based on Discrete Wavelet Transform +<br/>Yu Yang, Min Lei, Huaqun Liu, Yajian Zhou, and Qun Luo +<br/>Stego Key Estimation in LSB Steganography +<br/>Jing Liu and Guangming Tang +<br/>REGULAR PAPERS +<br/>Facial Expression Spacial Charts for Describing Dynamic Diversity of Facial Expressions +<br/>277 +<br/>279 +<br/>289 +<br/>295 +<br/>303 +<br/>309 +<br/>314 +</td><td>('46575279', 'H. Madokoro', 'h. madokoro')</td><td></td></tr><tr><td>362bfeb28adac5f45b6ef46c07c59744b4ed6a52</td><td>INCORPORATING SCALABILITY IN UNSUPERVISED SPATIO-TEMPORAL FEATURE +<br/>LEARNING +<br/><b>University of California, Riverside, CA</b></td><td>('49616225', 'Sujoy Paul', 'sujoy paul')<br/>('2177805', 'Sourya Roy', 'sourya roy')<br/>('1688416', 'Amit K. Roy-Chowdhury', 'amit k. roy-chowdhury')</td><td></td></tr><tr><td>360d66e210f7011423364327b7eccdf758b5fdd2</td><td>17th European Signal Processing Conference (EUSIPCO 2009) <br/>Glasgow, Scotland, August 24-28, 2009 <br/>LOCAL FEATURE EXTRACTION METHODS FOR FACIAL EXPRESSION <br/>RECOGNITION @@ -20651,11 +25902,23 @@ <br/>Dr. M.A. (Marco) Wiering <br/>Prof. dr. L.R.B. (Lambert) Schomaker <br/><b>ALICE Institute</b><br/><b>University of Groningen</b><br/>Nijenborgh 9, 9747 AG, Groningen, The Netherlands -</td><td>('3405120', 'Jos van de Wolfshaar', 'jos van de wolfshaar')</td><td></td></tr><tr><td>362a70b6e7d55a777feb7b9fc8bc4d40a57cde8c</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE +</td><td>('3405120', 'Jos van de Wolfshaar', 'jos van de wolfshaar')</td><td></td></tr><tr><td>368e99f669ea5fd395b3193cd75b301a76150f9d</td><td>One-to-many face recognition with bilinear CNNs +<br/>Aruni RoyChowdhury +<br/><b>University of Massachusetts, Amherst</b><br/>Erik Learned-Miller +</td><td>('2144284', 'Tsung-Yu Lin', 'tsung-yu lin')<br/>('35208858', 'Subhransu Maji', 'subhransu maji')</td><td>{arunirc,tsungyulin,smaji,elm}@cs.umass.edu +</td></tr><tr><td>362a70b6e7d55a777feb7b9fc8bc4d40a57cde8c</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE <br/>2792 <br/>ICASSP 2016 </td><td></td><td></td></tr><tr><td>36df81e82ea5c1e5edac40b60b374979a43668a5</td><td>ON-THE-FLY SPECIFIC PERSON RETRIEVAL <br/><b>University of Oxford, United Kingdom</b></td><td>('3188342', 'Omkar M. Parkhi', 'omkar m. parkhi')<br/>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{omkar,vedaldi,az}@robots.ox.ac.uk +</td></tr><tr><td>3619a9b46ad4779d0a63b20f7a6a8d3d49530339</td><td>SIMONYAN et al.: FISHER VECTOR FACES IN THE WILD +<br/>Fisher Vector Faces in the Wild +<br/>Visual Geometry Group +<br/>Department of Engineering Science +<br/><b>University of Oxford</b></td><td>('34838386', 'Karen Simonyan', 'karen simonyan')<br/>('3188342', 'Omkar M. Parkhi', 'omkar m. parkhi')<br/>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>karen@robots.ox.ac.uk +<br/>omkar@robots.ox.ac.uk +<br/>vedaldi@robots.ox.ac.uk +<br/>az@robots.ox.ac.uk </td></tr><tr><td>366d20f8fd25b4fe4f7dc95068abc6c6cabe1194</td><td></td><td></td><td></td></tr><tr><td>3630324c2af04fd90f8668f9ee9709604fe980fd</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2016.2607345, IEEE <br/>Transactions on Circuits and Systems for Video Technology <br/>Image Classification with Tailored Fine-Grained @@ -20713,7 +25976,28 @@ <br/>boxin@microsoft.com <br/>yizhou.wang@pku.edu.cn <br/>ganghua@microsoft.com -</td></tr><tr><td>3634b4dd263c0f330245c086ce646c9bb748cd6b</td><td>Temporal Localization of Fine-Grained Actions in Videos +</td></tr><tr><td>361d6345919c2edc5c3ce49bb4915ed2b4ee49be</td><td><b>Delft University of Technology</b><br/>Models for supervised learning in sequence data +<br/>Pei, Wenjie +<br/>DOI +<br/>10.4233/uuid:fff15717-71ec-402d-96e6-773884659f2c +<br/>Publication date +<br/>2018 +<br/>Document Version +<br/>Publisher's PDF, also known as Version of record +<br/>Citation (APA) +<br/>Pei, W. (2018). Models for supervised learning in sequence data DOI: 10.4233/uuid:fff15717-71ec-402d- +<br/>96e6-773884659f2c +<br/>Important note +<br/>To cite this publication, please use the final published version (if applicable). +<br/>Please check the document version above. +<br/>Copyright +<br/>Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent +<br/>of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons. +<br/>Takedown policy +<br/>Please contact us and provide details if you believe this document breaches copyrights. +<br/>We will remove access to the work immediately and investigate your claim. +<br/><b>This work is downloaded from Delft University of Technology</b><br/>For technical reasons the number of authors shown on this cover page is limited to a maximum of 10. +<br/> </td><td></td><td></td></tr><tr><td>3634b4dd263c0f330245c086ce646c9bb748cd6b</td><td>Temporal Localization of Fine-Grained Actions in Videos <br/>by Domain Transfer from Web Images <br/><b>University of Southern California</b><br/><b>Google, Inc</b></td><td>('1726241', 'Chen Sun', 'chen sun')</td><td>{chensun,nevatia}@usc.edu <br/>{sanketh,sukthankar}@google.com @@ -20742,6 +26026,8 @@ <br/>*Corresponding author </td><td>('1678263', 'Chandrashekhar N. Padole', 'chandrashekhar n. padole')<br/>('1712429', 'Hugo Proença', 'hugo proença')</td><td>E-mail: chandupadole@ubi.pt <br/>E-mail: hugomcp@di.ubi.pt +</td></tr><tr><td>5cbe1445d683d605b31377881ac8540e1d17adf0</td><td>On 3D Face Reconstruction via Cascaded Regression in Shape Space +<br/><b>College of Computer Science, Sichuan University, Chengdu, China</b></td><td>('50207647', 'Feng Liu', 'feng liu')<br/>('39422721', 'Dan Zeng', 'dan zeng')<br/>('1723081', 'Jing Li', 'jing li')<br/>('7345195', 'Qijun Zhao', 'qijun zhao')</td><td>qjzhao@scu.edu.cn </td></tr><tr><td>5ca23ceb0636dfc34c114d4af7276a588e0e8dac</td><td>Texture Representation in AAM using Gabor Wavelet <br/>and Local Binary Patterns <br/>School of Electronic Engineering, @@ -20756,7 +26042,12 @@ <br/>xuelong@dcs.bbk.ac.uk <br/>dacheng.tao@gmail.com <br/>xbgao@mail.xidian.edu.cn -</td></tr><tr><td>5c2a7518fb26a37139cebff76753d83e4da25159</td><td></td><td></td><td></td></tr><tr><td>5cb83eba8d265afd4eac49eb6b91cdae47def26d</td><td>Face Recognition with Local Line Binary Pattern +</td></tr><tr><td>5c2a7518fb26a37139cebff76753d83e4da25159</td><td></td><td></td><td></td></tr><tr><td>5c493c42bfd93e4d08517438983e3af65e023a87</td><td>The Thirty-Second AAAI Conference +<br/>on Artificial Intelligence (AAAI-18) +<br/>Multimodal Keyless Attention +<br/>Fusion for Video Classification +<br/><b>Tsinghua University, 2Rutgers University, 3Baidu IDL</b></td><td>('1716690', 'Xiang Long', 'xiang long')<br/>('2551285', 'Chuang Gan', 'chuang gan')<br/>('1732213', 'Gerard de Melo', 'gerard de melo')<br/>('48033101', 'Xiao Liu', 'xiao liu')<br/>('48515099', 'Yandong Li', 'yandong li')<br/>('9921390', 'Fu Li', 'fu li')<br/>('35247507', 'Shilei Wen', 'shilei wen')</td><td>{longx13, ganc13}@mails.tsinghua.edu.cn, gdm@demelo.org, {liuxiao12, liyandong, lifu, wenshilei}@baidu.com +</td></tr><tr><td>5cb83eba8d265afd4eac49eb6b91cdae47def26d</td><td>Face Recognition with Local Line Binary Pattern <br/><b>Mahanakorn University of Technology</b><br/>51 Cheum-Sampan Rd., Nong Chok, Bangkok, THAILAND 10530 </td><td>('2337544', 'Amnart Petpon', 'amnart petpon')<br/>('1805935', 'Sanun Srisuk', 'sanun srisuk')</td><td>ta tee473@hotmail.com, sanun@mut.ac.th </td></tr><tr><td>5c8672c0d2f28fd5d2d2c4b9818fcff43fb01a48</td><td>Robust Face Detection by Simple Means @@ -20804,7 +26095,10 @@ <br/>Robust Face Alignment <br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>('9120475', 'Liu Liu', 'liu liu')<br/>('23224233', 'Jiani Hu', 'jiani hu')<br/>('1678529', 'Shuo Zhang', 'shuo zhang')<br/>('1774956', 'Weihong Deng', 'weihong deng')</td><td></td></tr><tr><td>5c5e1f367e8768a9fb0f1b2f9dbfa060a22e75c0</td><td>2132 <br/>Reference Face Graph for Face Recognition -</td><td>('1784929', 'Mehran Kafai', 'mehran kafai')<br/>('39776603', 'Le An', 'le an')<br/>('1707159', 'Bir Bhanu', 'bir bhanu')</td><td></td></tr><tr><td>5c435c4bc9c9667f968f891e207d241c3e45757a</td><td>RUIZ-HERNANDEZ, CROWLEY, LUX: HOW OLD ARE YOU? +</td><td>('1784929', 'Mehran Kafai', 'mehran kafai')<br/>('39776603', 'Le An', 'le an')<br/>('1707159', 'Bir Bhanu', 'bir bhanu')</td><td></td></tr><tr><td>5c35ac04260e281141b3aaa7bbb147032c887f0c</td><td>Face Detection and Tracking Control with Omni Car +<br/>CS 231A Final Report +<br/>June 31, 2016 +</td><td>('2645488', 'Tung-Yu Wu', 'tung-yu wu')</td><td></td></tr><tr><td>5c435c4bc9c9667f968f891e207d241c3e45757a</td><td>RUIZ-HERNANDEZ, CROWLEY, LUX: HOW OLD ARE YOU? <br/>"How old are you?" : Age Estimation with <br/>Tensors of Binary Gaussian Receptive Maps <br/>INRIA Grenoble Rhones-Alpes @@ -20852,7 +26146,8 @@ <br/>ICASSP 2012 </td><td></td><td></td></tr><tr><td>5ce2cb4c76b0cdffe135cf24b9cda7ae841c8d49</td><td>Facial Expression Intensity Estimation Using Ordinal Information <br/><b>Computer and Systems Engineering, Rensselaer Polytechnic Institute</b><br/><b>School of Computer Science and Technology, University of Science and Technology of China</b></td><td>('1746803', 'Rui Zhao', 'rui zhao')<br/>('2316359', 'Quan Gan', 'quan gan')<br/>('1791319', 'Shangfei Wang', 'shangfei wang')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>1{zhaor,jiq}@rpi.edu, 2{gqquan@mail.,sfwang@}ustc.edu.cn -</td></tr><tr><td>09b80d8eea809529b08a8b0ff3417950c048d474</td><td>Adding Unlabeled Samples to Categories by Learned Attributes +</td></tr><tr><td>5c4d4fd37e8c80ae95c00973531f34a6d810ea3a</td><td>The Open World of Micro-Videos +<br/><b>UC Irvine1, INRIA2, Carnegie Mellon University</b></td><td>('1879100', 'Phuc Xuan Nguyen', 'phuc xuan nguyen')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td></td></tr><tr><td>09b80d8eea809529b08a8b0ff3417950c048d474</td><td>Adding Unlabeled Samples to Categories by Learned Attributes <br/><b>University of Maryland, College Park</b><br/><b>University of Washington</b></td><td>('3826759', 'Jonghyun Choi', 'jonghyun choi')<br/>('2270286', 'Ali Farhadi', 'ali farhadi')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td>{jhchoi,mrastega,lsd}@umiacs.umd.edu <br/>ali@cs.uw.edu </td></tr><tr><td>09f58353e48780c707cf24a0074e4d353da18934</td><td>To appear in Proc. IEEE IJCB, 2014 @@ -20939,7 +26234,12 @@ <br/>Received: 1 June 2016; Accepted: 20 July 2016; Published: 22 July 2016 </td><td>('40290479', 'Xuan Hou', 'xuan hou')<br/>('3439025', 'Guangjun Yao', 'guangjun yao')<br/>('40362316', 'Jun Wang', 'jun wang')</td><td>hx1995@email.swu.edu.cn (X.H.); guangjunyao@email.swu.edu.cn (G.Y.) <br/>* Correspondence: kingjun@swu.edu.cn; Tel.: +86-23-6825-4396 -</td></tr><tr><td>09dd01e19b247a33162d71f07491781bdf4bfd00</td><td>Efficiently Scaling Up Video Annotation +</td></tr><tr><td>09137e3c267a3414314d1e7e4b0e3a4cae801f45</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Two Birds with One Stone: Transforming and Generating +<br/>Facial Images with Iterative GAN +<br/>Received: date / Accepted: date +</td><td>('49626434', 'Dan Ma', 'dan ma')</td><td></td></tr><tr><td>09dd01e19b247a33162d71f07491781bdf4bfd00</td><td>Efficiently Scaling Up Video Annotation <br/>with Crowdsourced Marketplaces <br/>Department of Computer Science <br/><b>University of California, Irvine, USA</b></td><td>('1856025', 'Carl Vondrick', 'carl vondrick')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td>{cvondric,dramanan,djp3}@ics.uci.edu @@ -20957,6 +26257,10 @@ </td></tr><tr><td>09fa54f1ab7aaa83124d2415bfc6eb51e4b1f081</td><td>Where to Buy It: Matching Street Clothing Photos in Online Shops <br/><b>University of North Carolina at Chapel Hill</b><br/><b>University of Illinois at Urbana-Champaign</b></td><td>('1772294', 'M. Hadi Kiapour', 'm. hadi kiapour')<br/>('1682965', 'Xufeng Han', 'xufeng han')<br/>('1749609', 'Svetlana Lazebnik', 'svetlana lazebnik')<br/>('39668247', 'Alexander C. Berg', 'alexander c. berg')<br/>('1685538', 'Tamara L. Berg', 'tamara l. berg')</td><td>{hadi,xufeng,tlberg,aberg}@cs.unc.edu <br/>slazebni@illinois.edu +</td></tr><tr><td>09926ed62511c340f4540b5bc53cf2480e8063f8</td><td>Action Tubelet Detector for Spatio-Temporal Action Localization +</td><td>('1881509', 'Vicky Kalogeiton', 'vicky kalogeiton')<br/>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')<br/>('1749692', 'Vittorio Ferrari', 'vittorio ferrari')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>0951f42abbf649bb564a21d4ff5dddf9a5ea54d9</td><td>Joint Estimation of Age and Gender from Unconstrained Face Images +<br/>using Lightweight Multi-task CNN for Mobile Applications +<br/><b>Institute of Information Science, Academia Sinica, Taipei</b></td><td>('1781429', 'Jia-Hong Lee', 'jia-hong lee')<br/>('2679814', 'Yi-Ming Chan', 'yi-ming chan')<br/>('2329177', 'Ting-Yen Chen', 'ting-yen chen')<br/>('1720473', 'Chu-Song Chen', 'chu-song chen')</td><td>{honghenry.lee, yiming, timh20022002, song}@iis.sinica.edu.tw </td></tr><tr><td>09628e9116e7890bc65ebeabaaa5f607c9847bae</td><td>Semantically Consistent Regularization for Zero-Shot Recognition <br/>Department of Electrical and Computer Engineering <br/><b>University of California, San Diego</b></td><td>('1797523', 'Pedro Morgado', 'pedro morgado')<br/>('1699559', 'Nuno Vasconcelos', 'nuno vasconcelos')</td><td>{pmaravil,nuno}@ucsd.edu @@ -20973,6 +26277,13 @@ </td><td>('1968256', 'Erald VUÇINI', 'erald vuçini')<br/>('1766445', 'Muhittin GÖKMEN', 'muhittin gökmen')<br/>('1725803', 'Eduard GRÖLLER', 'eduard gröller')</td><td>vucini@cg.tuwien.ac.at <br/> gokmen@cs.itu.edu.tr <br/>groeller@cg.tuwien.ac.at +</td></tr><tr><td>097340d3ac939ce181c829afb6b6faff946cdce0</td><td>Adding New Tasks to a Single Network with +<br/>Weight Transformations using Binary Masks +<br/><b>Sapienza University of Rome, 2Fondazione Bruno Kessler, 3University of Trento</b><br/><b>Italian Institute of Technology, 5Mapillary Research</b></td><td>('38286801', 'Massimiliano Mancini', 'massimiliano mancini')<br/>('40811261', 'Elisa Ricci', 'elisa ricci')<br/>('3033284', 'Barbara Caputo', 'barbara caputo')</td><td>{mancini,caputo}@diag.uniroma1.it,eliricci@fbk.eu,samuel@mapillary.com +</td></tr><tr><td>09507f1f1253101d04a975fc5600952eac868602</td><td>Motion Feature Network: Fixed Motion Filter +<br/>for Action Recognition +<br/><b>Seoul National University, Seoul, South Korea</b><br/>2 V.DO Inc., Suwon, Korea +</td><td>('2647624', 'Myunggi Lee', 'myunggi lee')<br/>('51151436', 'Seungeui Lee', 'seungeui lee')<br/>('51136389', 'Gyutae Park', 'gyutae park')<br/>('3160425', 'Nojun Kwak', 'nojun kwak')</td><td>{myunggi89, dehlix, sjson, pgt4861, nojunk}@snu.ac.kr </td></tr><tr><td>09718bf335b926907ded5cb4c94784fd20e5ccd8</td><td>875 <br/>Recognizing Partially Occluded, Expression Variant <br/>Faces From Single Training Image per Person @@ -21154,7 +26465,25 @@ <br/>f (m) (xi,x j), <br/>(4) <br/>(5) -</td><td>('34651153', 'Junlin Hu', 'junlin hu')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('1689805', 'Yap-Peng Tan', 'yap-peng tan')</td><td></td></tr><tr><td>09b0ef3248ff8f1a05b8704a1b4cf64951575be9</td><td>Recognizing Activities of Daily Living with a Wrist-mounted Camera +</td><td>('34651153', 'Junlin Hu', 'junlin hu')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('1689805', 'Yap-Peng Tan', 'yap-peng tan')</td><td></td></tr><tr><td>09df62fd17d3d833ea6b5a52a232fc052d4da3f5</td><td>ISSN: 1405-5546 +<br/>Instituto Politécnico Nacional +<br/>México +<br/> +<br/>Rivas Araiza, Edgar A.; Mendiola Santibañez, Jorge D.; Herrera Ruiz, Gilberto; González Gutiérrez, +<br/>Carlos A.; Trejo Perea, Mario; Ríos Moreno, G. J. +<br/>Mejora de Contraste y Compensación en Cambios de la Iluminación +<br/>Instituto Politécnico Nacional +<br/>Distrito Federal, México +<br/>Disponible en: http://www.redalyc.org/articulo.oa?id=61509703 +<br/> Cómo citar el artículo +<br/> Número completo +<br/> Más información del artículo +<br/> Página de la revista en redalyc.org +<br/>Sistema de Información Científica +<br/>Red de Revistas Científicas de América Latina, el Caribe, España y Portugal +<br/>Proyecto académico sin fines de lucro, desarrollado bajo la iniciativa de acceso abierto +</td><td></td><td>computacion-y-sistemas@cic.ipn.mx +</td></tr><tr><td>09b0ef3248ff8f1a05b8704a1b4cf64951575be9</td><td>Recognizing Activities of Daily Living with a Wrist-mounted Camera <br/><b>Graduate School of Information Science and Technology, The University of Tokyo</b></td><td>('8197937', 'Katsunori Ohnishi', 'katsunori ohnishi')<br/>('2551640', 'Atsushi Kanehira', 'atsushi kanehira')<br/>('2554424', 'Asako Kanezaki', 'asako kanezaki')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td>{ohnishi, kanehira, kanezaki, harada}@mi.t.u-tokyo.ac.jp </td></tr><tr><td>097104fc731a15fad07479f4f2c4be2e071054a2</td><td></td><td></td><td></td></tr><tr><td>094357c1a2ba3fda22aa6dd9e496530d784e1721</td><td>A Unified Probabilistic Approach Modeling Relationships <br/>between Attributes and Objects @@ -21223,7 +26552,15 @@ <br/>Received: 28 April 2013 /Accepted: 19 July 2013 /Published: 31 July 2013 </td><td>('2266189', 'Jing Zhang', 'jing zhang')<br/>('2732767', 'Caixia Yang', 'caixia yang')<br/>('1809507', 'Kecheng Liu', 'kecheng liu')</td><td>* E-mail: eduzhangjing@163.com </td></tr><tr><td>5d7f8eb73b6a84eb1d27d1138965eb7aef7ba5cf</td><td>Robust Registration of Dynamic Facial Sequences -</td><td>('2046537', 'Evangelos Sariyanidi', 'evangelos sariyanidi')<br/>('1781916', 'Hatice Gunes', 'hatice gunes')<br/>('1713138', 'Andrea Cavallaro', 'andrea cavallaro')</td><td></td></tr><tr><td>5dcf78de4d3d867d0fd4a3105f0defae2234b9cb</td><td></td><td></td><td></td></tr><tr><td>5d88702cdc879396b8b2cc674e233895de99666b</td><td>Exploiting Feature Hierarchies with Convolutional Neural Networks +</td><td>('2046537', 'Evangelos Sariyanidi', 'evangelos sariyanidi')<br/>('1781916', 'Hatice Gunes', 'hatice gunes')<br/>('1713138', 'Andrea Cavallaro', 'andrea cavallaro')</td><td></td></tr><tr><td>5dcf78de4d3d867d0fd4a3105f0defae2234b9cb</td><td></td><td></td><td></td></tr><tr><td>5db4fe0ce9e9227042144758cf6c4c2de2042435</td><td>INTERNATIONAL JOURNAL OF ELECTRICAL AND ELECTRONIC SYSTEMS RESEARCH, VOL.3, JUNE 2010 +<br/>Recognition of Facial Expression Using Haar +<br/>Wavelet Transform +<br/>for +<br/>paper +<br/>features +<br/>investigates +<br/> +</td><td>('2254697', 'M. Satiyan', 'm. satiyan')</td><td></td></tr><tr><td>5d88702cdc879396b8b2cc674e233895de99666b</td><td>Exploiting Feature Hierarchies with Convolutional Neural Networks <br/>for Cultural Event Recognition <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), <br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>School of Computer Science, Carnegie Mellon University, 15213, USA</b></td><td>('1730228', 'Mengyi Liu', 'mengyi liu')<br/>('1731144', 'Xin Liu', 'xin liu')<br/>('38751558', 'Yan Li', 'yan li')<br/>('1710220', 'Xilin Chen', 'xilin chen')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')</td><td>{mengyi.liu, xin.liu, yan.li}@vipl.ict.ac.cn, {xlchen, sgshan}@ict.ac.cn, alex@cs.cmu.edu @@ -21317,7 +26654,20 @@ </td></tr><tr><td>5d479f77ecccfac9f47d91544fd67df642dfab3c</td><td>Linking People in Videos with “Their” Names <br/>Using Coreference Resolution <br/><b>Stanford University, USA</b><br/><b>Stanford University, USA</b></td><td>('34066479', 'Vignesh Ramanathan', 'vignesh ramanathan')<br/>('2319608', 'Armand Joulin', 'armand joulin')<br/>('40085065', 'Percy Liang', 'percy liang')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td>{vigneshr,ajoulin,pliang,feifeili}@cs.stanford.edu -</td></tr><tr><td>5d01283474b73a46d80745ad0cc0c4da14aae194</td><td></td><td></td><td></td></tr><tr><td>5d197c8cd34473eb6cde6b65ced1be82a3a1ed14</td><td><b>AFaceImageDatabaseforEvaluatingOut-of-FocusBlurQiHan,QiongLiandXiamuNiuHarbinInstituteofTechnologyChina1.IntroductionFacerecognitionisoneofthemostpopularresearchfieldsofcomputervisionandmachinelearning(Tores(2004);Zhaoetal.(2003)).Alongwithinvestigationoffacerecognitionalgorithmsandsystems,manyfaceimagedatabaseshavebeencollected(Gross(2005)).Facedatabasesareimportantfortheadvancementoftheresearchfield.Becauseofthenonrigidityandcomplex3Dstructureofface,manyfactorsinfluencetheperformanceoffacedetectionandrecognitionalgorithmssuchaspose,expression,age,brightness,contrast,noise,blurandetc.Someearlyfacedatabasesgatheredunderstrictlycontrolledenvironment(Belhumeuretal.(1997);Samaria&Harter(1994);Turk&Pentland(1991))onlyallowslightexpressionvariation.Toinvestigatetherelationshipsbetweenalgorithms’performanceandtheabovefactors,morefacedatabaseswithlargerscaleandvariouscharacterswerebuiltinthepastyears(Bailly-Bailliereetal.(2003);Flynnetal.(2003);Gaoetal.(2008);Georghiadesetal.(2001);Hallinan(1995);Phillipsetal.(2000);Simetal.(2003)).Forinstance,The"CAS-PEAL","FERET","CMUPIE",and"YaleB"databasesincludevariousposes(Gaoetal.(2008);Georghiadesetal.(2001);Phillipsetal.(2000);Simetal.(2003));The"HarvardRL","CMUPIE"and"YaleB"databasesinvolvemorethan40differentconditionsinillumination(Georghiadesetal.(2001);Hallinan(1995);Simetal.(2003));Andthe"BANCA",and"NDHID"databasescontainover10timesgathering(Bailly-Bailliereetal.(2003);Flynnetal.(2003)).Thesedatabaseshelpresearcherstoevaluateandimprovetheiralgorithmsaboutfacedetection,recognition,andotherpurposes.Blurisnotthemostimportantbutstillanotablefactoraffectingtheperformanceofabiometricsystem(Fronthaleretal.(2006);Zamanietal.(2007)).Themainreasonsleadingblurconsistinout-of-focusofcameraandmotionofobject,andtheout-of-focusblurismoresignificantintheapplicationenvironmentoffacerecognition(Eskicioglu&Fisher(1995);Kimetal.(1998);Tanakaetal.(2007);Yitzhaky&Kopeika(1996)).Toinvestigatetheinfluenceofbluronafacerecognitionsystem,afaceimagedatabasewithdifferentconditionsofclarityandefficientblurevaluatingalgorithmsareneeded.Thischapterintroducesanewfacedatabasebuiltforthepurposeofblurevaluation.Theapplicationenvironmentsoffacerecognitionareanalyzedfirstly,thenaimagegatheringschemeisdesigned.Twotypicalgatheringfacilitiesareusedandthefocusstatusaredividedinto11steps.Further,theblurassessmentalgorithmsaresummarizedandthecomparisonbetweenthemisraisedonthevarious-claritydatabase.The7www.intechopen.com</b></td><td></td><td></td></tr><tr><td>5df376748fe5ccd87a724ef31d4fdb579dab693f</td><td>A Dashboard for Affective E-learning: +</td></tr><tr><td>5d01283474b73a46d80745ad0cc0c4da14aae194</td><td></td><td></td><td></td></tr><tr><td>5d197c8cd34473eb6cde6b65ced1be82a3a1ed14</td><td><b>AFaceImageDatabaseforEvaluatingOut-of-FocusBlurQiHan,QiongLiandXiamuNiuHarbinInstituteofTechnologyChina1.IntroductionFacerecognitionisoneofthemostpopularresearchfieldsofcomputervisionandmachinelearning(Tores(2004);Zhaoetal.(2003)).Alongwithinvestigationoffacerecognitionalgorithmsandsystems,manyfaceimagedatabaseshavebeencollected(Gross(2005)).Facedatabasesareimportantfortheadvancementoftheresearchfield.Becauseofthenonrigidityandcomplex3Dstructureofface,manyfactorsinfluencetheperformanceoffacedetectionandrecognitionalgorithmssuchaspose,expression,age,brightness,contrast,noise,blurandetc.Someearlyfacedatabasesgatheredunderstrictlycontrolledenvironment(Belhumeuretal.(1997);Samaria&Harter(1994);Turk&Pentland(1991))onlyallowslightexpressionvariation.Toinvestigatetherelationshipsbetweenalgorithms’performanceandtheabovefactors,morefacedatabaseswithlargerscaleandvariouscharacterswerebuiltinthepastyears(Bailly-Bailliereetal.(2003);Flynnetal.(2003);Gaoetal.(2008);Georghiadesetal.(2001);Hallinan(1995);Phillipsetal.(2000);Simetal.(2003)).Forinstance,The"CAS-PEAL","FERET","CMUPIE",and"YaleB"databasesincludevariousposes(Gaoetal.(2008);Georghiadesetal.(2001);Phillipsetal.(2000);Simetal.(2003));The"HarvardRL","CMUPIE"and"YaleB"databasesinvolvemorethan40differentconditionsinillumination(Georghiadesetal.(2001);Hallinan(1995);Simetal.(2003));Andthe"BANCA",and"NDHID"databasescontainover10timesgathering(Bailly-Bailliereetal.(2003);Flynnetal.(2003)).Thesedatabaseshelpresearcherstoevaluateandimprovetheiralgorithmsaboutfacedetection,recognition,andotherpurposes.Blurisnotthemostimportantbutstillanotablefactoraffectingtheperformanceofabiometricsystem(Fronthaleretal.(2006);Zamanietal.(2007)).Themainreasonsleadingblurconsistinout-of-focusofcameraandmotionofobject,andtheout-of-focusblurismoresignificantintheapplicationenvironmentoffacerecognition(Eskicioglu&Fisher(1995);Kimetal.(1998);Tanakaetal.(2007);Yitzhaky&Kopeika(1996)).Toinvestigatetheinfluenceofbluronafacerecognitionsystem,afaceimagedatabasewithdifferentconditionsofclarityandefficientblurevaluatingalgorithmsareneeded.Thischapterintroducesanewfacedatabasebuiltforthepurposeofblurevaluation.Theapplicationenvironmentsoffacerecognitionareanalyzedfirstly,thenaimagegatheringschemeisdesigned.Twotypicalgatheringfacilitiesareusedandthefocusstatusaredividedinto11steps.Further,theblurassessmentalgorithmsaresummarizedandthecomparisonbetweenthemisraisedonthevarious-claritydatabase.The7www.intechopen.com</b></td><td></td><td></td></tr><tr><td>5da2ae30e5ee22d00f87ebba8cd44a6d55c6855e</td><td><b>This is an Open Access document downloaded from ORCA, Cardiff University's institutional</b><br/>repository: http://orca.cf.ac.uk/111659/ +<br/>This is the author’s version of a work that was submitted to / accepted for publication. +<br/>Citation for final published version: +<br/>Krumhuber, Eva G, Lai, Yukun, Rosin, Paul and Hugenberg, Kurt 2018. When facial expressions +<br/>Publishers page: +<br/>Please note: +<br/>Changes made as a result of publishing processes such as copy-editing, formatting and page +<br/>numbers may not be reflected in this version. For the definitive version of this publication, please +<br/>refer to the published source. You are advised to consult the publisher’s version if you wish to cite +<br/>this paper. +<br/>This version is being made available in accordance with publisher policies. See +<br/>http://orca.cf.ac.uk/policies.html for usage policies. Copyright and moral rights for publications +<br/>made available in ORCA are retained by the copyright holders. +</td><td></td><td></td></tr><tr><td>5df376748fe5ccd87a724ef31d4fdb579dab693f</td><td>A Dashboard for Affective E-learning: <br/>Data Visualization for Monitoring Online Learner Emotions <br/>School of Computer Science <br/><b>Carleton University</b><br/>Canada @@ -21332,8 +26682,14 @@ <br/><b>University of Science and Technology of China</b><br/>2Microsoft Research Asia, </td><td>('3093568', 'Jianmin Bao', 'jianmin bao')<br/>('39447786', 'Dong Chen', 'dong chen')<br/>('1716835', 'Fang Wen', 'fang wen')<br/>('7179232', 'Houqiang Li', 'houqiang li')<br/>('1745420', 'Gang Hua', 'gang hua')</td><td>jmbao@mail.ustc.edu.cn, lihq@ustc.edu.cn <br/>{doch,fangwen,ganghua}@microsoft.com -</td></tr><tr><td>31c0968fb5f587918f1c49bf7fa51453b3e89cf7</td><td>Deep Transfer Learning for Person Re-identification -</td><td>('3447059', 'Mengyue Geng', 'mengyue geng')<br/>('5765799', 'Yaowei Wang', 'yaowei wang')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('1705972', 'Yonghong Tian', 'yonghong tian')</td><td></td></tr><tr><td>31e57fa83ac60c03d884774d2b515813493977b9</td><td></td><td></td><td></td></tr><tr><td>3137a3fedf23717c411483c7b4bd2ed646258401</td><td>Joint Learning of Discriminative Prototypes +</td></tr><tr><td>318e7e6daa0a799c83a9fdf7dd6bc0b3e89ab24a</td><td>Sparsity in Dynamics of Spontaneous +<br/>Subtle Emotions: Analysis & Application +</td><td>('35256518', 'Anh Cat Le Ngo', 'anh cat le ngo')<br/>('2339975', 'John See', 'john see')<br/>('6633183', 'Raphael C.-W. Phan', 'raphael c.-w. phan')</td><td></td></tr><tr><td>31c0968fb5f587918f1c49bf7fa51453b3e89cf7</td><td>Deep Transfer Learning for Person Re-identification +</td><td>('3447059', 'Mengyue Geng', 'mengyue geng')<br/>('5765799', 'Yaowei Wang', 'yaowei wang')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('1705972', 'Yonghong Tian', 'yonghong tian')</td><td></td></tr><tr><td>313d5eba97fe064bdc1f00b7587a4b3543ef712a</td><td>Compact Deep Aggregation for Set Retrieval +<br/><b>Visual Geometry Group, University of Oxford, UK</b><br/>2 DeepMind +</td><td>('6730372', 'Yujie Zhong', 'yujie zhong')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>{yujie,az}@robots.ox.ac.uk +<br/>relja@google.com +</td></tr><tr><td>31e57fa83ac60c03d884774d2b515813493977b9</td><td></td><td></td><td></td></tr><tr><td>3137a3fedf23717c411483c7b4bd2ed646258401</td><td>Joint Learning of Discriminative Prototypes <br/>and Large Margin Nearest Neighbor Classifiers <br/><b>Institute for Computer Graphics and Vision, Graz University of Technology</b></td><td>('3202367', 'Paul Wohlhart', 'paul wohlhart')<br/>('1791182', 'Peter M. Roth', 'peter m. roth')<br/>('3628150', 'Horst Bischof', 'horst bischof')</td><td>{koestinger,wohlhart,pmroth,bischof}@icg.tugraz.at </td></tr><tr><td>31c34a5b42a640b824fa4e3d6187e3675226143e</td><td>Shape and Texture based Facial Action and Emotion @@ -21349,9 +26705,21 @@ <br/>High Dimensional Binary Features <br/>´Ecole Polytechique de Montr´eal, Universit´e de Montr´eal, Montr´eal, Canada </td><td>('3127597', 'Samira Ebrahimi Kahou', 'samira ebrahimi kahou')<br/>('2558801', 'Pierre Froumenty', 'pierre froumenty')</td><td>{samira.ebrahimi-kahou, pierre.froumenty, christopher.pal}@polymtl.ca +</td></tr><tr><td>31ea88f29e7f01a9801648d808f90862e066f9ea</td><td>Published as a conference paper at ICLR 2017 +<br/>DEEP MULTI-TASK REPRESENTATION LEARNING: +<br/>A TENSOR FACTORISATION APPROACH +<br/><b>Queen Mary, University of London</b></td><td>('2653152', 'Yongxin Yang', 'yongxin yang')<br/>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')</td><td>{yongxin.yang, t.hospedales}@qmul.ac.uk +</td></tr><tr><td>3176ee88d1bb137d0b561ee63edf10876f805cf0</td><td>Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation +<br/><b>University of Montreal, 2Cornell University, 3Ecole Polytechnique of Montreal, 4CIFAR</b></td><td>('25056820', 'Sina Honari', 'sina honari')<br/>('2965424', 'Jason Yosinski', 'jason yosinski')<br/>('1707326', 'Pascal Vincent', 'pascal vincent')</td><td>1{honaris, vincentp}@iro.umontreal.ca, 2yosinski@cs.cornell.edu, 3christopher.pal@polymtl.ca </td></tr><tr><td>31b58ced31f22eab10bd3ee2d9174e7c14c27c01</td><td></td><td></td><td></td></tr><tr><td>31835472821c7e3090abb42e57c38f7043dc3636</td><td>Flow Counting Using Realboosted <br/>Multi-sized Window Detectors -<br/><b>Lund University, Cognimatics AB</b></td><td>('38481779', 'Mikael Nilsson', 'mikael nilsson')<br/>('3181258', 'Rikard Berthilsson', 'rikard berthilsson')</td><td></td></tr><tr><td>3152e89963b8a4028c4abf6e1dc19e91c4c5a8f4</td><td>Exploring Stereotypes and Biased Data with the Crowd +<br/><b>Lund University, Cognimatics AB</b></td><td>('38481779', 'Mikael Nilsson', 'mikael nilsson')<br/>('3181258', 'Rikard Berthilsson', 'rikard berthilsson')</td><td></td></tr><tr><td>312b2566e315dd6e65bd42cfcbe4d919159de8a1</td><td>An Accurate Algorithm for Generating a Music Playlist +<br/>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 100– No.9, August 2014 +<br/>based on Facial Expressions +<br/>Computer Science and Engineering Department +<br/>Amity School of Engineering & Technology, +<br/><b>Amity University, Noida, India</b></td><td></td><td></td></tr><tr><td>3152e89963b8a4028c4abf6e1dc19e91c4c5a8f4</td><td>Exploring Stereotypes and Biased Data with the Crowd <br/>Department of Computer Science <br/><b>The University of Texas at Austin</b><br/>Department of Computer Science <br/><b>The University of Texas at Austin</b><br/>Introduction @@ -21508,7 +26876,18 @@ <br/>jeffcohn@pitt.edu </td></tr><tr><td>91811203c2511e919b047ebc86edad87d985a4fa</td><td>Expression Subspace Projection for Face <br/>Recognition from Single Sample per Person -</td><td>('1782221', 'Hoda Mohammadzade', 'hoda mohammadzade')</td><td></td></tr><tr><td>910524c0d0fe062bf806bb545627bf2c9a236a03</td><td>Master Thesis +</td><td>('1782221', 'Hoda Mohammadzade', 'hoda mohammadzade')</td><td></td></tr><tr><td>91495c689e6e614247495c3f322d400d8098de43</td><td>A Deep-Learning Approach to Facial Expression Recognition +<br/>with Candid Images +<br/>Wei Li +<br/><b>CUNY City College</b><br/>Min Li +<br/>Alibaba. Inc +<br/>Zhong Su +<br/><b>IBM China Research Lab</b><br/>Zhigang Zhu +<br/><b>CUNY Graduate Center and City College</b></td><td></td><td>lwei000@citymail.cuny.edu +<br/>mushi.lm@alibaba.inc +<br/>suzhong@cn.ibm.com +<br/>zhu@cs.ccny.cuny.edu +</td></tr><tr><td>910524c0d0fe062bf806bb545627bf2c9a236a03</td><td>Master Thesis <br/>Improvement of Facial Expression Recognition through the <br/>Evaluation of Dynamic and Static Features in Video Sequences <br/>Submitted by: @@ -21571,7 +26950,12 @@ <br/>Publisher: Springer <br/>http://link.springer.com/content/pdf/10.1007%2F978-3- <br/>642-04146-4_50.pdf -</td><td></td><td></td></tr><tr><td>91883dabc11245e393786d85941fb99a6248c1fb</td><td></td><td></td><td></td></tr><tr><td>91b1a59b9e0e7f4db0828bf36654b84ba53b0557</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI +</td><td></td><td></td></tr><tr><td>91883dabc11245e393786d85941fb99a6248c1fb</td><td></td><td></td><td></td></tr><tr><td>917bea27af1846b649e2bced624e8df1d9b79d6f</td><td>Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for +<br/>Mobile and Embedded Applications +<br/>Gyrfalcon Technology Inc. +<br/>1900 McCarthy Blvd. Milpitas, CA 95035 +</td><td>('47935028', 'Baohua Sun', 'baohua sun')<br/>('49576071', 'Lin Yang', 'lin yang')<br/>('46195424', 'Patrick Dong', 'patrick dong')<br/>('49039276', 'Wenhan Zhang', 'wenhan zhang')<br/>('35287113', 'Jason Dong', 'jason dong')<br/>('48990565', 'Charles Young', 'charles young')</td><td>{baohua.sun,lin.yang,patrick.dong,wenhan.zhang,jason.dong,charles.yang}@gyrfalcontech.com +</td></tr><tr><td>91b1a59b9e0e7f4db0828bf36654b84ba53b0557</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI <br/>> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < <br/> <br/>Simultaneous Hallucination and Recognition of @@ -21579,7 +26963,16 @@ <br/>Decomposition <br/>(SVD) <br/>for performing both -</td><td>('1783889', 'Muwei Jian', 'muwei jian')<br/>('1703078', 'Kin-Man Lam', 'kin-man lam')</td><td></td></tr><tr><td>919d0e681c4ef687bf0b89fe7c0615221e9a1d30</td><td></td><td></td><td></td></tr><tr><td>912a6a97af390d009773452814a401e258b77640</td><td></td><td></td><td></td></tr><tr><td>91d513af1f667f64c9afc55ea1f45b0be7ba08d4</td><td>Automatic Face Image Quality Prediction +</td><td>('1783889', 'Muwei Jian', 'muwei jian')<br/>('1703078', 'Kin-Man Lam', 'kin-man lam')</td><td></td></tr><tr><td>911bef7465665d8b194b6b0370b2b2389dfda1a1</td><td>RANJAN, ROMERO, BLACK: LEARNING HUMAN OPTICAL FLOW +<br/>Learning Human Optical Flow +<br/>1 MPI for Intelligent Systems +<br/>Tübingen, Germany +<br/>2 Amazon Inc. +</td><td>('1952002', 'Anurag Ranjan', 'anurag ranjan')<br/>('39040964', 'Javier Romero', 'javier romero')<br/>('2105795', 'Michael J. Black', 'michael j. black')</td><td>aranjan@tuebingen.mpg.de +<br/>javier@amazon.com +<br/>black@tuebingen.mpg.de +</td></tr><tr><td>91ead35d1d2ff2ea7cf35d15b14996471404f68d</td><td>Combining and Steganography of 3D Face Textures +</td><td>('38478675', 'Mohsen Moradi', 'mohsen moradi')</td><td></td></tr><tr><td>919d0e681c4ef687bf0b89fe7c0615221e9a1d30</td><td></td><td></td><td></td></tr><tr><td>912a6a97af390d009773452814a401e258b77640</td><td></td><td></td><td></td></tr><tr><td>91d513af1f667f64c9afc55ea1f45b0be7ba08d4</td><td>Automatic Face Image Quality Prediction </td><td>('2180413', 'Lacey Best-Rowden', 'lacey best-rowden')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>91e507d2d8375bf474f6ffa87788aa3e742333ce</td><td>Robust Face Recognition Using Probabilistic <br/>Facial Trait Code <br/>†Department of Computer Science and Information Engineering, National Taiwan @@ -21594,7 +26987,10 @@ <br/>Faculty of Engineering and Physical Sciences <br/><b>University of Surrey</b><br/>Guildford, Surrey GU2 7XH, U.K. <br/>April 2015 -</td><td>('38819702', 'Guosheng Hu', 'guosheng hu')<br/>('38819702', 'Guosheng Hu', 'guosheng hu')</td><td></td></tr><tr><td>915d4a0fb523249ecbc88eb62cb150a60cf60fa0</td><td>Comparison of Feature Extraction Techniques in Automatic +</td><td>('38819702', 'Guosheng Hu', 'guosheng hu')<br/>('38819702', 'Guosheng Hu', 'guosheng hu')</td><td></td></tr><tr><td>9131c990fad219726eb38384976868b968ee9d9c</td><td>Deep Facial Expression Recognition: A Survey +</td><td>('39433609', 'Shan Li', 'shan li')<br/>('1774956', 'Weihong Deng', 'weihong deng')</td><td></td></tr><tr><td>911505a4242da555c6828509d1b47ba7854abb7a</td><td>IMPROVED ACTIVE SHAPE MODEL FOR FACIAL FEATURE LOCALIZATION +<br/><b>National Formosa University, Taiwan</b></td><td>('1711364', 'Hui-Yu Huang', 'hui-yu huang')<br/>('2782376', 'Shih-Hang Hsu', 'shih-hang hsu')</td><td>Email: hyhuang@nfu.edu.tw +</td></tr><tr><td>915d4a0fb523249ecbc88eb62cb150a60cf60fa0</td><td>Comparison of Feature Extraction Techniques in Automatic <br/>Face Recognition Systems for Security Applications <br/>S . Cruz-Llanas, J. Ortega-Garcia, E. Martinez-Torrico, J. Gonzalez-Rodriguez <br/>Dpto. Ingenieria Audiovisual y Comunicaciones, EUIT Telecomunicacion, Univ. PolitCcnica de Madrid, Spain @@ -21665,6 +27061,26 @@ <br/><b>University of Georgia, Athens, GA, U.S.A</b></td><td>('2278811', 'Rabia Jafri', 'rabia jafri')<br/>('2227653', 'Syed Abid Ali', 'syed abid ali')<br/>('1712033', 'Hamid R. Arabnia', 'hamid r. arabnia')</td><td></td></tr><tr><td>65bba9fba03e420c96ec432a2a82521ddd848c09</td><td>Connectionist Temporal Modeling for Weakly <br/>Supervised Action Labeling <br/><b>Stanford University</b></td><td>('38485317', 'De-An Huang', 'de-an huang')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')</td><td>{dahuang,feifeili,jniebles}@cs.stanford.edu +</td></tr><tr><td>656531036cee6b2c2c71954bb6540ef6b2e016d0</td><td>W. LIU ET AL.: JOINTLY LEARNING NON-NEGATIVE PROJECTION AND DICTIONARY 1 +<br/>Jointly Learning Non-negative Projection +<br/>and Dictionary with Discriminative Graph +<br/>Constraints for Classification +<br/>Yandong Wen3 +<br/>Rongmei Lin4 +<br/>Meng Yang*1 +<br/><b>College of Computer Science</b><br/>Software Engineering, +<br/><b>Shenzhen University, China</b><br/>2 School of ECE, +<br/><b>Peking University, China</b><br/>3 Dept. of ECE, +<br/><b>Carnegie Mellon University, USA</b><br/>4 Dept. of Math & Computer Science, +<br/><b>Emory University, USA</b></td><td>('36326884', 'Weiyang Liu', 'weiyang liu')<br/>('1751019', 'Zhiding Yu', 'zhiding yu')</td><td>wyliu@pku.edu.cn +<br/>yzhiding@andrew.cmu.edu +<br/>yandongw@andrew.cmu.edu +<br/>rongmei.lin@emory.edu +<br/>yang.meng@szu.edu.cn +</td></tr><tr><td>65b1209d38c259fe9ca17b537f3fb4d1857580ae</td><td>Information Constraints on Auto-Encoding Variational Bayes +<br/><b>University of California, Berkeley</b><br/><b>University of California, Berkeley</b><br/><b>Ragon Institute of MGH, MIT and Harvard</b><br/>4Chan-Zuckerberg Biohub +</td><td>('39848341', 'Romain Lopez', 'romain lopez')<br/>('39967607', 'Jeffrey Regier', 'jeffrey regier')<br/>('1694621', 'Michael I. Jordan', 'michael i. jordan')<br/>('2163873', 'Nir Yosef', 'nir yosef')</td><td>{romain_lopez, regier, niryosef}@berkeley.edu +<br/>jordan@cs.berkeley.edu </td></tr><tr><td>655d9ba828eeff47c600240e0327c3102b9aba7c</td><td>IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005 <br/>489 <br/>Kernel Pooled Local Subspaces for Classification @@ -21695,7 +27111,7 @@ <br/>FOR IMPROVING REAL TIME FACE RECOGNITION EFFICIENCY <br/>ON WEARABLE GADGETS <br/><b>Asia Pacific University of Technology and Innovation, Kuala Lumpur 57000, Malaysia</b><br/><b>Staffordshire University, Beaconside Stafford ST18 0AB, United Kingdom</b></td><td>('22422404', 'MUHAMMAD EHSAN RANA', 'muhammad ehsan rana')</td><td>*Corresponding Author: muhd_ehsanrana@apu.edu.my -</td></tr><tr><td>6577c76395896dd4d352f7b1ee8b705b1a45fa90</td><td>TOWARDS COMPUTATIONAL MODELS OF KINSHIP VERIFICATION +</td></tr><tr><td>656f05741c402ba43bb1b9a58bcc5f7ce2403d9a</td><td></td><td>('2319574', 'Danila Potapov', 'danila potapov')</td><td></td></tr><tr><td>6577c76395896dd4d352f7b1ee8b705b1a45fa90</td><td>TOWARDS COMPUTATIONAL MODELS OF KINSHIP VERIFICATION <br/><b>Cornell University</b><br/><b>Cornell University</b></td><td>('2666471', 'Ruogu Fang', 'ruogu fang')<br/>('1830653', 'Noah Snavely', 'noah snavely')<br/>('1746230', 'Tsuhan Chen', 'tsuhan chen')</td><td></td></tr><tr><td>650bfe7acc3f03eb4ba91d9f93da8ef0ae8ba772</td><td>A Deep Learning Approach for Subject Independent Emotion <br/>Recognition from Facial Expressions <br/>*Faculty of Electronics, Telecommunications & Information Technology @@ -21745,7 +27161,17 @@ <br/><b>Rensselaer Polytechnic Institute</b><br/>Troy, NY, USA <br/>2 Visualization and Computer Vision Lab <br/><b>GE Global Research Center</b><br/>Niskayuna, NY, USA -</td><td>('1686235', 'Yan Tong', 'yan tong')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td></td></tr><tr><td>62d1a31b8acd2141d3a994f2d2ec7a3baf0e6dc4</td><td>Ding et al. EURASIP Journal on Image and Video Processing (2017) 2017:43 +</td><td>('1686235', 'Yan Tong', 'yan tong')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td></td></tr><tr><td>653d19e64bd75648cdb149f755d59e583b8367e3</td><td>Decoupling “when to update” from “how to +<br/>update” +<br/><b>School of Computer Science, The Hebrew University, Israel</b></td><td>('19201820', 'Eran Malach', 'eran malach')<br/>('2554670', 'Shai Shalev-Shwartz', 'shai shalev-shwartz')</td><td></td></tr><tr><td>65babb10e727382b31ca5479b452ee725917c739</td><td>Label Distribution Learning +</td><td>('1735299', 'Xin Geng', 'xin geng')</td><td></td></tr><tr><td>62dccab9ab715f33761a5315746ed02e48eed2a0</td><td>A Short Note about Kinetics-600 +<br/>Jo˜ao Carreira +</td><td>('51210148', 'Eric Noland', 'eric noland')<br/>('51215438', 'Andras Banki-Horvath', 'andras banki-horvath')<br/>('38961760', 'Chloe Hillier', 'chloe hillier')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>joaoluis@google.com +<br/>enoland@google.com +<br/>bhandras@google.com +<br/>chillier@google.com +<br/>zisserman@google.com +</td></tr><tr><td>62d1a31b8acd2141d3a994f2d2ec7a3baf0e6dc4</td><td>Ding et al. EURASIP Journal on Image and Video Processing (2017) 2017:43 <br/>DOI 10.1186/s13640-017-0188-z <br/>EURASIP Journal on Image <br/>and Video Processing @@ -21773,11 +27199,78 @@ </td><td>('1746363', 'Eva L. Dyer', 'eva l. dyer')<br/>('1745861', 'Aswin C. Sankaranarayanan', 'aswin c. sankaranarayanan')<br/>('1746260', 'Richard G. Baraniuk', 'richard g. baraniuk')</td><td>e.dyer@rice.edu <br/>saswin@ece.cmu.edu <br/>richb@rice.edu -</td></tr><tr><td>62f0d8446adee6a5e8102053a63a61af07ac4098</td><td>FACIAL POINT DETECTION USING CONVOLUTIONAL NEURAL NETWORK +</td></tr><tr><td>620339aef06aed07a78f9ed1a057a25433faa58b</td><td></td><td></td><td></td></tr><tr><td>62b3598b401c807288a113796f424612cc5833ca</td><td></td><td></td><td></td></tr><tr><td>62f0d8446adee6a5e8102053a63a61af07ac4098</td><td>FACIAL POINT DETECTION USING CONVOLUTIONAL NEURAL NETWORK <br/>TRANSFERRED FROM A HETEROGENEOUS TASK <br/>**Tome R&D <br/><b>Chubu University</b><br/>1200, Matsumoto-cho, Kasugai, AICHI -</td><td>('1687819', 'Takayoshi Yamashita', 'takayoshi yamashita')</td><td></td></tr><tr><td>62374b9e0e814e672db75c2c00f0023f58ef442c</td><td>Frontalfaceauthenticationusingdiscriminatinggridswith +</td><td>('1687819', 'Takayoshi Yamashita', 'takayoshi yamashita')</td><td></td></tr><tr><td>628a3f027b7646f398c68a680add48c7969ab1d9</td><td>Plan for Final Year Project: +<br/>HKU-Face: A Large Scale Dataset for Deep Face +<br/>Recognition +<br/>3035140108 +<br/>3035141841 +<br/>Introduction +<br/>Face recognition has been one of the most successful techniques in the field of artificial intelligence +<br/>because of its surpassing human-level performance in academic experiments and broad application in +<br/>the industrial world. Gaussian-face[1] and Facenet[2] hold state-of-the-art record using statistical +<br/>method and deep-learning method respectively. What’s more, face recognition has been applied +<br/>in various areas like authority checking and recording, fostering a large number of start-ups like +<br/>Face++. +<br/>Our final year project will deal with the face recognition task by building a large-scaled and carefully- +<br/>filtered dataset. Our project plan specifies our roadmap and current research process. This plan first +<br/>illustrates the significance and potential enhancement in constructing large-scale face dataset for +<br/>both academics and companies. Then objectives to accomplish and related literature review will be +<br/>expressed in detail. Next, methodologies used, scope of our project and challenges faced by us are +<br/>described. The detailed timeline for this project follows as well as a small summary. +<br/>2 Motivation +<br/>Nowadays most of the face recognition tasks are supervised learning tasks which use dataset annotated +<br/>by human beings. This contains mainly two drawbacks: (1) limited size of dataset due to limited +<br/>human effort; (2) accuracy problem resulted from human perceptual bias. +<br/>Parkhi et al.[3] discuss the first problem, showing that giant companies hold private face databases +<br/>with larger size of data (See the comparison in Table 1). Other research institution could only get +<br/>access to public but smaller databases like LFW[4, 5], which acts like a barricade to even higher +<br/>performance. +<br/>Dataset +<br/>IJB-A [6] +<br/>LFW [4, 5] +<br/>YFD [7] +<br/>CelebFaces [8] +<br/>CASIA-WebFace [9] +<br/>MS-Celeb-1M [10] +<br/>Facebook +<br/>Google +<br/>Availability +<br/>public +<br/>public +<br/>public +<br/>public +<br/>public +<br/>public +<br/>private +<br/>private +<br/>identities +<br/>500 +<br/>5K +<br/>1595 +<br/>10K +<br/>10K +<br/>100K +<br/>4K +<br/>8M +<br/>images +<br/>5712 +<br/>13K +<br/>3425 videos +<br/>202K +<br/>500K +<br/>about 10M +<br/>4400K +<br/>100-200M +<br/>Table 1: Face recognition datasets +</td><td>('3347561', 'Haicheng Wang', 'haicheng wang')<br/>('40456402', 'Haoyu Li', 'haoyu li')</td><td></td></tr><tr><td>626913b8fcbbaee8932997d6c4a78fe1ce646127</td><td>Learning from Millions of 3D Scans for Large-scale 3D Face Recognition +<br/>(This the preprint of the paper published in CVPR 2018) +<br/>School of Computer Science and Software Engineering, +<br/><b>The University of Western Australia</b></td><td>('1746166', 'Syed Zulqarnain Gilani', 'syed zulqarnain gilani')<br/>('46332747', 'Ajmal Mian', 'ajmal mian')</td><td>{zulqarnain.gilani,ajmal.mian}@uwa.edu.au +</td></tr><tr><td>62374b9e0e814e672db75c2c00f0023f58ef442c</td><td>Frontalfaceauthenticationusingdiscriminatinggridswith <br/>morphologicalfeaturevectors <br/>A.Tefas <br/>C.Kotropoulos @@ -21868,17 +27361,28 @@ <br/>November 2015 | Volume 2 | Article 29 </td><td>('1689681', 'Rodrigo Verschae', 'rodrigo verschae')<br/>('1737300', 'Javier Ruiz-del-Solar', 'javier ruiz-del-solar')<br/>('1689681', 'Rodrigo Verschae', 'rodrigo verschae')<br/>('1689681', 'Rodrigo Verschae', 'rodrigo verschae')</td><td>rodrigo@verschae.org </td></tr><tr><td>62e913431bcef5983955e9ca160b91bb19d9de42</td><td>Facial Landmark Detection with Tweaked Convolutional Neural Networks -<br/><b>USC Information Sciences Institute</b><br/><b>The Open University of Israel</b></td><td>('1746738', 'Yue Wu', 'yue wu')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>624e9d9d3d941bab6aaccdd93432fc45cac28d4b</td><td>Object-Scene Convolutional Neural Networks for Event Recognition in Images +<br/><b>USC Information Sciences Institute</b><br/><b>The Open University of Israel</b></td><td>('1746738', 'Yue Wu', 'yue wu')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>626859fe8cafd25da13b19d44d8d9eb6f0918647</td><td>Activity Recognition based on a +<br/>Magnitude-Orientation Stream Network +<br/>Smart Surveillance Interest Group, Department of Computer Science +<br/>Universidade Federal de Minas Gerais, Belo Horizonte, Brazil +</td><td>('2119408', 'Carlos Caetano', 'carlos caetano')<br/>('1679142', 'William Robson Schwartz', 'william robson schwartz')</td><td>{carlos.caetano,victorhcmelo,jefersson,william}@dcc.ufmg.br +</td></tr><tr><td>624e9d9d3d941bab6aaccdd93432fc45cac28d4b</td><td>Object-Scene Convolutional Neural Networks for Event Recognition in Images <br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen key lab of Comp. Vis. and Pat. Rec., Shenzhen Institutes of Advanced Technology, CAS, China</b></td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('1915826', 'Zhe Wang', 'zhe wang')<br/>('35031371', 'Wenbin Du', 'wenbin du')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td>07wanglimin@gmail.com, buptwangzhe2012@gmail.com, wb.du@siat.ac.cn, yu.qiao@siat.ac.cn </td></tr><tr><td>620e1dbf88069408b008347cd563e16aeeebeb83</td><td></td><td></td><td></td></tr><tr><td>624496296af19243d5f05e7505fd927db02fd0ce</td><td>Gauss-Newton Deformable Part Models for Face Alignment in-the-Wild <br/>1. School of Computer Science <br/><b>University of Lincoln, U.K</b><br/>2. Department of Computing <br/><b>Imperial College London, U.K</b></td><td>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td>gtzimiropoulos@lincoln.ac.uk -</td></tr><tr><td>621ff353960d5d9320242f39f85921f72be69dc8</td><td>Explicit Occlusion Detection based Deformable Fitting for +</td></tr><tr><td>62fd622b3ca97eb5577fd423fb9efde9a849cbef</td><td>Turning a Blind Eye: Explicit Removal of Biases and +<br/>Variation from Deep Neural Network Embeddings +<br/><b>Visual Geometry Group, University of Oxford</b><br/><b>University of Oxford</b><br/><b>Big Data Institute, University of Oxford</b></td><td>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td></td></tr><tr><td>621ff353960d5d9320242f39f85921f72be69dc8</td><td>Explicit Occlusion Detection based Deformable Fitting for <br/>Facial Landmark Localization <br/>1Department of Computer Science <br/><b>Rutgers University</b><br/>617 Bowser Road, Piscataway, N.J, USA </td><td>('39960064', 'Xiang Yu', 'xiang yu')<br/>('1684164', 'Fei Yang', 'fei yang')<br/>('1768190', 'Junzhou Huang', 'junzhou huang')<br/>('1711560', 'Dimitris N. Metaxas', 'dimitris n. metaxas')</td><td>{xiangyu,feiyang,dnm}@cs.rutgers.edu +</td></tr><tr><td>62007c30f148334fb4d8975f80afe76e5aef8c7f</td><td>Eye In-Painting with Exemplar Generative Adversarial Networks +<br/>Facebook Inc. +<br/>1 Hacker Way, Menlo Park (CA), USA +</td><td>('8277405', 'Brian Dolhansky', 'brian dolhansky')</td><td>{bdol, ccanton}@fb.com </td></tr><tr><td>62a30f1b149843860938de6dd6d1874954de24b7</td><td>418 <br/>Fast Algorithm for Updating the Discriminant Vectors <br/>of Dual-Space LDA @@ -21914,13 +27418,22 @@ <br/>1 ESAT-PSI/VISICS, iMinds, KU Leuven, Belgium <br/>2 MPI Informatics, Saarbrücken, Germany <br/>3 D-ITET/CVL, ETH Zürich, Switzerland -</td><td>('11983029', 'Markus Mathias', 'markus mathias')<br/>('1798000', 'Rodrigo Benenson', 'rodrigo benenson')<br/>('3048367', 'Marco Pedersoli', 'marco pedersoli')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td></td></tr><tr><td>9626bcb3fc7c7df2c5a423ae8d0a046b2f69180c</td><td>UPTEC STS 17033 +</td><td>('11983029', 'Markus Mathias', 'markus mathias')<br/>('1798000', 'Rodrigo Benenson', 'rodrigo benenson')<br/>('3048367', 'Marco Pedersoli', 'marco pedersoli')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td></td></tr><tr><td>96f0e7416994035c91f4e0dfa40fd45090debfc5</td><td>Unsupervised Learning of Face Representations +<br/><b>Georgia Institute of Technology, CVIT, IIIT Hyderabad, IIT Kanpur</b></td><td>('19200118', 'Samyak Datta', 'samyak datta')<br/>('39396475', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>9626bcb3fc7c7df2c5a423ae8d0a046b2f69180c</td><td>UPTEC STS 17033 <br/>Examensarbete 30 hp <br/>November 2017 <br/>A deep learning approach for <br/>action classification in American <br/>football video sequences -</td><td>('5845058', 'Jacob Westerberg', 'jacob westerberg')</td><td></td></tr><tr><td>968b983fa9967ff82e0798a5967920188a3590a8</td><td>2013, Vol. 139, No. 2, 271–299 +</td><td>('5845058', 'Jacob Westerberg', 'jacob westerberg')</td><td></td></tr><tr><td>963d0d40de8780161b70d28d2b125b5222e75596</td><td>Convolutional Experts Network for Facial Landmark Detection +<br/><b>Carnegie Mellon University</b><br/>Tadas Baltruˇsaitis∗ +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +<br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +</td><td>('1783029', 'Amir Zadeh', 'amir zadeh')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')</td><td>abagherz@cs.cmu.edu +<br/>tbaltrus@cs.cmu.edu +<br/>morency@cs.cmu.edu +</td></tr><tr><td>968b983fa9967ff82e0798a5967920188a3590a8</td><td>2013, Vol. 139, No. 2, 271–299 <br/>© 2013 American Psychological Association <br/>0033-2909/13/$12.00 DOI: 10.1037/a0031640 <br/>Children’s Recognition of Disgust in Others @@ -22008,16 +27521,32 @@ </td><td>('39106061', 'Liying Chi', 'liying chi')<br/>('35028106', 'Hongxin Zhang', 'hongxin zhang')<br/>('9932177', 'Mingxiu Chen', 'mingxiu chen')</td><td>charrin0531@gmail.com <br/>zhx@cad.zju.edu.cn <br/>cmxnono@rokid.com +</td></tr><tr><td>96a9ca7a8366ae0efe6b58a515d15b44776faf6e</td><td>Grid Loss: Detecting Occluded Faces +<br/><b>Institute for Computer Graphics and Vision</b><br/><b>Graz University of Technology</b></td><td>('34847524', 'Michael Opitz', 'michael opitz')<br/>('1903921', 'Georg Waltner', 'georg waltner')<br/>('1762885', 'Georg Poier', 'georg poier')<br/>('1720811', 'Horst Possegger', 'horst possegger')<br/>('3628150', 'Horst Bischof', 'horst bischof')</td><td>{michael.opitz,waltner,poier,possegger,bischof}@icg.tugraz.at </td></tr><tr><td>9696b172d66e402a2e9d0a8d2b3f204ad8b98cc4</td><td>J Inf Process Syst, Vol.9, No.1, March 2013 <br/>pISSN 1976-913X <br/>eISSN 2092-805X <br/>Region-Based Facial Expression Recognition in <br/>Still Images -</td><td>('2648759', 'Gawed M. Nagi', 'gawed m. nagi')<br/>('2057896', 'Fatimah Khalid', 'fatimah khalid')</td><td></td></tr><tr><td>964a3196d44f0fefa7de3403849d22bbafa73886</td><td></td><td></td><td></td></tr><tr><td>96f4a1dd1146064d1586ebe86293d02e8480d181</td><td>COMPARATIVE ANALYSIS OF RERANKING +</td><td>('2648759', 'Gawed M. Nagi', 'gawed m. nagi')<br/>('2057896', 'Fatimah Khalid', 'fatimah khalid')</td><td></td></tr><tr><td>964a3196d44f0fefa7de3403849d22bbafa73886</td><td></td><td></td><td></td></tr><tr><td>96e1ccfe96566e3c96d7b86e134fa698c01f2289</td><td>Published in Proc. of 11th IAPR International Conference on Biometrics (ICB 2018). Gold Coast, Australia, Feb. 2018 +<br/>Semi-Adversarial Networks: Convolutional Autoencoders for Imparting Privacy +<br/>to Face Images +<br/>Anoop Namboodiri 2 +<br/><b>Michigan State University, East Lansing, USA</b><br/><b>International Institute of Information Technology, Hyderabad, India</b></td><td>('5456235', 'Vahid Mirjalili', 'vahid mirjalili')<br/>('2562040', 'Sebastian Raschka', 'sebastian raschka')<br/>('1698707', 'Arun Ross', 'arun ross')</td><td>mirjalil@msu.edu +<br/>raschkas@msu.edu +<br/>anoop@iiit.ac.in +<br/>rossarun@cse.msu.edu +</td></tr><tr><td>96f4a1dd1146064d1586ebe86293d02e8480d181</td><td>COMPARATIVE ANALYSIS OF RERANKING <br/>TECHNIQUES FOR WEB IMAGE SEARCH <br/><b>Pune Institute of Computer Technology, Pune, ( India</b></td><td></td><td></td></tr><tr><td>9606b1c88b891d433927b1f841dce44b8d3af066</td><td>Principal Component Analysis with Tensor Train <br/>Subspace -</td><td>('2329741', 'Wenqi Wang', 'wenqi wang')<br/>('1732805', 'Vaneet Aggarwal', 'vaneet aggarwal')<br/>('1980683', 'Shuchin Aeron', 'shuchin aeron')</td><td></td></tr><tr><td>966e36f15b05ef8436afecf57a97b73d6dcada94</td><td>Dimensionality Reduction using Relative +</td><td>('2329741', 'Wenqi Wang', 'wenqi wang')<br/>('1732805', 'Vaneet Aggarwal', 'vaneet aggarwal')<br/>('1980683', 'Shuchin Aeron', 'shuchin aeron')</td><td></td></tr><tr><td>9627f28ea5f4c389350572b15968386d7ce3fe49</td><td>Load Balanced GANs for Multi-view Face Image Synthesis +<br/>1National Laboratory of Pattern Recognition, CASIA +<br/>2Center for Research on Intelligent Perception and Computing, CASIA +<br/>3Center for Excellence in Brain Science and Intelligence Technology, CAS +<br/><b>University of Chinese Academy of Sciences, Beijing, 100049, China</b><br/>5Noah’s Ark Lab of Huawei Technologies +</td><td>('1680853', 'Jie Cao', 'jie cao')<br/>('49995036', 'Yibo Hu', 'yibo hu')<br/>('49828394', 'Bing Yu', 'bing yu')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>{jie.cao,yibo.hu}@cripac.ia.ac.cn, yubing5@huawei.com, {rhe, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>966e36f15b05ef8436afecf57a97b73d6dcada94</td><td>Dimensionality Reduction using Relative <br/>Attributes <br/><b>Institute for Human-Machine Communication, Technische Universit at M unchen</b><br/><b>Iran</b><br/><b>The Remote Sensing Technology Institute (IMF), German Aerospace Center</b><br/>1 Introduction <br/>Visual attributes are high-level semantic description of visual data that are close @@ -22049,6 +27578,13 @@ </td><td>('2133342', 'Mohammadreza Babaee', 'mohammadreza babaee')<br/>('2165157', 'Stefanos Tsoukalas', 'stefanos tsoukalas')<br/>('3281049', 'Maryam Babaee', 'maryam babaee')<br/>('1705843', 'Gerhard Rigoll', 'gerhard rigoll')<br/>('1777167', 'Mihai Datcu', 'mihai datcu')</td><td>{reza.babaee,rigoll}@tum.de, s.tsoukalas@mytum.de <br/>babaee@eng.ui.ac.ir <br/>mihai.datcu@dlr.de +</td></tr><tr><td>96b1000031c53cd4c1c154013bb722ffd87fa7da</td><td>ContextVP: Fully Context-Aware Video +<br/>Prediction +<br/>1 NVIDIA, Santa Clara, CA, USA +<br/>2 ETH Zurich, Zurich, Switzerland +<br/>3 The Swiss AI Lab IDSIA, Manno, Switzerland +<br/>4 NNAISENSE, Lugano, Switzerland +</td><td>('2387035', 'Wonmin Byeon', 'wonmin byeon')<br/>('1794816', 'Qin Wang', 'qin wang')<br/>('2100612', 'Rupesh Kumar Srivastava', 'rupesh kumar srivastava')<br/>('1802604', 'Petros Koumoutsakos', 'petros koumoutsakos')</td><td>wbyeon@nvidia.com </td></tr><tr><td>96578785836d7416bf2e9c154f687eed8f93b1e4</td><td>Automated video-based facial expression analysis <br/>of neuropsychiatric disorders <br/><b>a Section of Biomedical Image Analysis, University of Pennsylvania, 3600 Market, Suite 380, Philadelphia, PA 19104, USA</b><br/><b>b Brain Behavior Center, University of Pennsylvania Medical Center, Hospital of the University of Pennsylvania</b><br/>3400 Spruce Street, 10th Floor Gates Building Philadelphia, PA 19104, USA @@ -22068,7 +27604,10 @@ <br/>mega-scale (with a million distractors). Observe that rates drop with increasing numbers of distractors, even though the probe set is fixed, <br/>and that algorithms trained on larger sets (dashed lines) generally perform better. Participate at: http://megaface.cs.washington.edu. </td><td>('2419955', 'Ira Kemelmacher-Shlizerman', 'ira kemelmacher-shlizerman')<br/>('1679223', 'Steven M. Seitz', 'steven m. seitz')<br/>('2721528', 'Evan Brossard', 'evan brossard')</td><td></td></tr><tr><td>968f472477a8afbadb5d92ff1b9c7fdc89f0c009</td><td>Firefly-based Facial Expression Recognition -</td><td></td><td></td></tr><tr><td>96e731e82b817c95d4ce48b9e6b08d2394937cf8</td><td>Unconstrained Face Verification using Deep CNN Features +</td><td></td><td></td></tr><tr><td>96c6f50ce8e1b9e8215b8791dabd78b2bbd5f28d</td><td>Dynamic Attention-controlled Cascaded Shape Regression Exploiting Training +<br/>Data Augmentation and Fuzzy-set Sample Weighting +<br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK</b><br/><b>School of IoT Engineering, Jiangnan University, Wuxi 214122, China</b></td><td>('2976854', 'Zhen-Hua Feng', 'zhen-hua feng')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>{z.feng, j.kittler, w.christmas, p.huber}@surrey.ac.uk, wu xiaojun@jiangnan.edu.cn +</td></tr><tr><td>96e731e82b817c95d4ce48b9e6b08d2394937cf8</td><td>Unconstrained Face Verification using Deep CNN Features <br/><b>University of Maryland, College Park</b><br/><b>Rutgers, The State University of New Jersey</b></td><td>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>pullpull@cs.umd.edu, vishal.m.patel@rutgers.edu, rama@umiacs.umd.edu </td></tr><tr><td>9686dcf40e6fdc4152f38bd12b929bcd4f3bbbcc</td><td>International Journal of Engineering Research and General Science Volume 3, Issue 1, January-February, 2015 <br/>ISSN 2091-2730 @@ -22078,7 +27617,13 @@ <br/>3Department of Computer Science and Engineering <br/>4Asst. Professor, Department of Computer Science and Engineering <br/><b>M.H Saboo Siddik College of Engineering, University of Mumbai, India</b></td><td>('9928295', 'Sharik Khan', 'sharik khan')<br/>('1762886', 'Omar Khan', 'omar khan')<br/>('16079307', 'Shabana Tadvi', 'shabana tadvi')</td><td>Email:-kabani152@gmail.com -</td></tr><tr><td>9636c7d3643fc598dacb83d71f199f1d2cc34415</td><td></td><td></td><td></td></tr><tr><td>3af8d38469fb21368ee947d53746ea68cd64eeae</td><td>Multimodal Intelligent Affect Detection with Kinect +</td></tr><tr><td>9636c7d3643fc598dacb83d71f199f1d2cc34415</td><td></td><td></td><td></td></tr><tr><td>3a27d164e931c422d16481916a2fa6401b74bcef</td><td>Anti-Makeup: Learning A Bi-Level Adversarial Network for Makeup-Invariant +<br/>Face Verification +<br/>National Laboratory of Pattern Recognition, CASIA +<br/>Center for Research on Intelligent Perception and Computing, CASIA +<br/>Center for Excellence in Brain Science and Intelligence Technology, CAS +<br/><b>University of Chinese Academy of Sciences, Beijing 100190, China</b></td><td>('2496686', 'Yi Li', 'yi li')<br/>('3051419', 'Lingxiao Song', 'lingxiao song')<br/>('2225749', 'Xiang Wu', 'xiang wu')<br/>('1705643', 'Ran He', 'ran he')<br/>('1688870', 'Tieniu Tan', 'tieniu tan')</td><td>yi.li@cripac.ia.ac.cn, {lingxiao.song, rhe, tnt}@nlpr.ia.ac.cn, alfredxiangwu@gmail.com +</td></tr><tr><td>3af8d38469fb21368ee947d53746ea68cd64eeae</td><td>Multimodal Intelligent Affect Detection with Kinect <br/>(Doctoral Consortium) <br/><b>Northumbria University</b><br/>United Kingdom <br/><b>Northumbria University</b><br/>United Kingdom @@ -22087,9 +27632,13 @@ <br/>Yang4.zhang@northumbria.ac.uk </td></tr><tr><td>3a2fc58222870d8bed62442c00341e8c0a39ec87</td><td>Probabilistic Local Variation <br/>Segmentation -<br/>Technion - Computer Science Department - M.Sc. Thesis MSC-2014-02 - 2014 </td><td>('3139600', 'Michael Baltaxe', 'michael baltaxe')</td><td></td></tr><tr><td>3a76e9fc2e89bdd10a9818f7249fbf61d216efc4</td><td>Face Sketch Matching via Coupled Deep Transform Learning +<br/>Technion - Computer Science Department - M.Sc. Thesis MSC-2014-02 - 2014 </td><td>('3139600', 'Michael Baltaxe', 'michael baltaxe')</td><td></td></tr><tr><td>3a3f75e0ffdc0eef07c42b470593827fcd4020b4</td><td>NORMAL SIMILARITY NETWORK FOR GENERATIVE MODELLING +<br/><b>School of Computing, National University of Singapore</b></td><td>('40456486', 'Jay Nandy', 'jay nandy')<br/>('1725063', 'Wynne Hsu', 'wynne hsu')</td><td></td></tr><tr><td>3a76e9fc2e89bdd10a9818f7249fbf61d216efc4</td><td>Face Sketch Matching via Coupled Deep Transform Learning <br/><b>IIIT-Delhi, India, 2West Virginia University</b></td><td>('1925017', 'Shruti Nagpal', 'shruti nagpal')<br/>('2220719', 'Maneet Singh', 'maneet singh')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('2487227', 'Afzel Noore', 'afzel noore')<br/>('2641605', 'Angshul Majumdar', 'angshul majumdar')</td><td>{shrutin, maneets, rsingh, mayank, angshul}@iiitd.ac.in, afzel.noore@mail.wvu.edu -</td></tr><tr><td>3a0ea368d7606030a94eb5527a12e6789f727994</td><td>Categorization by Learning +</td></tr><tr><td>3a2c90e0963bfb07fc7cd1b5061383e9a99c39d2</td><td>End-to-End Deep Learning for Steering Autonomous +<br/>Vehicles Considering Temporal Dependencies +<br/><b>The American University in Cairo, Egypt</b><br/>2Valeo Schalter und Sensoren GmbH, Germany +</td><td>('2150605', 'Hesham M. Eraqi', 'hesham m. eraqi')<br/>('2233511', 'Mohamed N. Moustafa', 'mohamed n. moustafa')<br/>('11300101', 'Jens Honer', 'jens honer')</td><td></td></tr><tr><td>3a0ea368d7606030a94eb5527a12e6789f727994</td><td>Categorization by Learning <br/>and Combining Object Parts <br/> <br/>Tomaso Poggio @@ -22233,7 +27782,11 @@ <br/>Philadelphia, PA 19104 </td><td>('1722767', 'Peng Wang', 'peng wang')<br/>('15741672', 'Fred Barrett', 'fred barrett')<br/>('7467718', 'Ragini Verma', 'ragini verma')</td><td>{wpeng@ieee.org, ragini.verma@uphs.upenn.edu } <br/>{kohler, fbarrett, raquel, gur}@bbl.med.upenn.edu -</td></tr><tr><td>3a846704ef4792dd329a5c7a2cb8b330ab6b8b4e</td><td>in any current or +</td></tr><tr><td>3a9681e2e07be7b40b59c32a49a6ff4c40c962a2</td><td>Biometrics & Biostatistics International Journal +<br/>Comparing treatment means: overlapping standard +<br/>errors, overlapping confidence intervals, and tests of +<br/>hypothesis +</td><td></td><td></td></tr><tr><td>3a846704ef4792dd329a5c7a2cb8b330ab6b8b4e</td><td>in any current or <br/>future media, <br/>for all other uses, <br/>© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be @@ -22260,7 +27813,28 @@ <br/>Sricharan H S1, Srinidhi K S1, Rajath D N1, Tejas J N1, Chandrakala B M2 <br/> BE, DSCE, Bangalore1 <br/>Assistant Professor, DSCE, Bangalore2 -</td><td></td><td></td></tr><tr><td>54bb25a213944b08298e4e2de54f2ddea890954a</td><td>AgeDB: the first manually collected, in-the-wild age database +</td><td></td><td></td></tr><tr><td>54948ee407b5d32da4b2eee377cc44f20c3a7e0c</td><td>Right for the Right Reason: Training Agnostic +<br/>Networks +<br/><b>Intelligent Systems Laboratory, University of Bristol, Bristol BS8 1UB, UK</b><br/>use of classifiers in “out of domain” situations, a problem that +<br/>leads to research questions in domain adaptation [6], [18]. +<br/>Other concerns are also created around issues of bias, e.g. +<br/>classifiers incorporating biases that are present in the data +<br/>and are not intended to be used [2], which run the risk of +<br/>reinforcing or amplifying cultural (and other) biases [20]. +<br/>Therefore, both predictive accuracy and fairness are heavily +<br/>influenced by the choices made when developing black-box +<br/>machine-learning models. +</td><td>('1805367', 'Sen Jia', 'sen jia')<br/>('2031978', 'Thomas Lansdall-Welfare', 'thomas lansdall-welfare')<br/>('1685083', 'Nello Cristianini', 'nello cristianini')</td><td>{sen.jia, thomas.lansdall-welfare, nello.cristianini}@bris.ac.uk +</td></tr><tr><td>540b39ba1b8ef06293ed793f130e0483e777e278</td><td>ORIGINAL RESEARCH +<br/>published: 13 July 2018 +<br/>doi: 10.3389/fpsyg.2018.01191 +<br/>Biologically Inspired Emotional +<br/>Expressions for Artificial Agents +<br/><b>Optics and Engineering Informatics, Budapest University of Technology and Economics</b><br/><b>Budapest, Hungary, E tv s Lor nd University, Budapest, Hungary, 3 Institute for Computer Science</b><br/><b>and Control, Hungarian Academy of Sciences, Budapest, Hungary, Chuo University</b><br/>Tokyo, Japan, 5 MTA-ELTE Comparative Ethology Research Group, Budapest, Hungary, 6 Department of Telecommunications +<br/><b>and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary</b><br/>A special area of human-machine interaction, +<br/>the expression of emotions gains +<br/>importance with the continuous development of artificial agents such as social robots or +</td><td>('31575111', 'Beáta Korcsok', 'beáta korcsok')<br/>('3410664', 'Veronika Konok', 'veronika konok')<br/>('10791722', 'György Persa', 'györgy persa')<br/>('2725581', 'Tamás Faragó', 'tamás faragó')<br/>('1701851', 'Mihoko Niitsuma', 'mihoko niitsuma')<br/>('1769570', 'Péter Baranyi', 'péter baranyi')<br/>('3131165', 'Márta Gácsi', 'márta gácsi')</td><td></td></tr><tr><td>54bb25a213944b08298e4e2de54f2ddea890954a</td><td>AgeDB: the first manually collected, in-the-wild age database <br/><b>Imperial College London</b><br/><b>Imperial College London</b><br/><b>Imperial College London, On do</b><br/><b>Imperial College London</b><br/><b>Middlesex University London</b><br/><b>Imperial College London</b></td><td>('24278037', 'Stylianos Moschoglou', 'stylianos moschoglou')<br/>('40598566', 'Athanasios Papaioannou', 'athanasios papaioannou')<br/>('3320415', 'Christos Sagonas', 'christos sagonas')<br/>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('1754270', 'Irene Kotsia', 'irene kotsia')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td>s.moschoglou@imperial.ac.uk <br/>a.papaioannou11@imperial.ac.uk <br/>c.sagonas@imperial.ac.uk @@ -22286,19 +27860,28 @@ <br/>NETWORKS <br/><b>University of Freiburg</b><br/>79110 Freiburg, Germany </td><td>('2060551', 'Jost Tobias Springenberg', 'jost tobias springenberg')</td><td>springj@cs.uni-freiburg.de -</td></tr><tr><td>5456166e3bfe78a353df988897ec0bd66cee937f</td><td>Improved Boosting Performance by Exclusion +</td></tr><tr><td>54969bcd728b0f2d3285866c86ef0b4797c2a74d</td><td>IEEE TRANSACTION SUBMISSION +<br/>Learning for Video Compression +</td><td>('31482866', 'Zhibo Chen', 'zhibo chen')<br/>('50258851', 'Tianyu He', 'tianyu he')<br/>('50562569', 'Xin Jin', 'xin jin')<br/>('1697194', 'Feng Wu', 'feng wu')</td><td></td></tr><tr><td>5456166e3bfe78a353df988897ec0bd66cee937f</td><td>Improved Boosting Performance by Exclusion <br/>of Ambiguous Positive Examples <br/>Computer Vision and Active Perception, KTH, Stockholm 10800, Sweden <br/>Keywords: <br/>Boosting, Image Classification, Algorithm Evaluation, Dataset Pruning, VOC2007. </td><td>('1750517', 'Miroslav Kobetski', 'miroslav kobetski')<br/>('1736906', 'Josephine Sullivan', 'josephine sullivan')</td><td>{kobetski, sullivan}@kth.se -</td></tr><tr><td>541f1436c8ffef1118a0121088584ddbfd3a0a8a</td><td>A Spatio-Temporal Feature based on Triangulation of Dense SURF +</td></tr><tr><td>54a9ed950458f4b7e348fa78a718657c8d3d0e05</td><td>Learning Neural Models for End-to-End +<br/>Clustering +<br/>1 ZHAW Datalab & School of Engineering, Winterthur, Switzerland +<br/>2 ARGUS DATA INSIGHTS Schweiz AG, Zurich, Switzerland +<br/><b>Ca Foscari University of Venice, Venice, Italy</b><br/><b>Institute of Neural Information Processing, Ulm University, Germany</b><br/><b>Institute for Optical Systems, HTWG Konstanz, Germany</b></td><td>('50415299', 'Benjamin Bruno Meier', 'benjamin bruno meier')<br/>('3469013', 'Ismail Elezi', 'ismail elezi')<br/>('1985672', 'Mohammadreza Amirian', 'mohammadreza amirian')<br/>('3238279', 'Oliver Dürr', 'oliver dürr')<br/>('2793787', 'Thilo Stadelmann', 'thilo stadelmann')</td><td></td></tr><tr><td>541f1436c8ffef1118a0121088584ddbfd3a0a8a</td><td>A Spatio-Temporal Feature based on Triangulation of Dense SURF <br/><b>The University of Electro-Communications, Tokyo</b><br/>1-5-1 Chofu, Tokyo 182-0021 JAPAN </td><td>('2274625', 'Do Hang Nga', 'do hang nga')<br/>('1681659', 'Keiji Yanai', 'keiji yanai')</td><td>dohang@mm.cs.uec.ac.jp, yanai@cs.uec.ac.jp </td></tr><tr><td>54aacc196ffe49b3450059fccdf7cd3bb6f6f3c3</td><td>A Joint Learning Framework for Attribute Models and Object Descriptions <br/>Dhruv Mahajan <br/>Yahoo! Labs, Bangalore, India </td><td>('1779926', 'Sundararajan Sellamanickam', 'sundararajan sellamanickam')<br/>('4989209', 'Vinod Nair', 'vinod nair')</td><td>{dkm,ssrajan,vnair}@yahoo-inc.com +</td></tr><tr><td>54ce3ff2ab6e4465c2f94eb4d636183fa7878ab7</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Local Centroids Structured Non-Negative Matrix Factorization +<br/><b>University of Texas at Arlington, Texas, USA</b><br/><b>School of Computer Science, OPTIMAL, Northwestern Polytechnical University, Xian 710072, Shaanxi, P. R. China</b></td><td>('2141896', 'Hongchang Gao', 'hongchang gao')<br/>('1688370', 'Feiping Nie', 'feiping nie')</td><td>{hongchanggao, feipingnie}@gmail.com, heng@uta.edu </td></tr><tr><td>541bccf19086755f8b5f57fd15177dc49e77d675</td><td></td><td>('2154872', 'Lijin Aryananda', 'lijin aryananda')</td><td></td></tr><tr><td>5495e224ac7b45b9edc5cfeabbb754d8a40a879b</td><td>Feature Reconstruction Disentangling for Pose-invariant Face Recognition <br/>Supplementary Material <br/><b>Rutgers, The State University of New Jersey</b><br/><b>University of California, San Diego</b><br/>‡ NEC Laboratories America @@ -22419,7 +28002,10 @@ <br/>useful information from the vast and ever changing image and video data available on the world wide web. For <br/>some of this data people provide partial annotation in the form of tags, captions, and freeform text on web pages. <br/>One major challenge is to combine results from computational visual recognition with these partial annotations to -</td><td>('39668247', 'Alexander C. Berg', 'alexander c. berg')</td><td></td></tr><tr><td>549c719c4429812dff4d02753d2db11dd490b2ae</td><td>YouTube-BoundingBoxes: A Large High-Precision +</td><td>('39668247', 'Alexander C. Berg', 'alexander c. berg')</td><td></td></tr><tr><td>54204e28af73c7aca073835a14afcc5d8f52a515</td><td>Fine-Pruning: Defending Against Backdooring Attacks +<br/>on Deep Neural Networks +<br/><b>New York University, Brooklyn, NY, USA</b></td><td>('48087922', 'Kang Liu', 'kang liu')<br/>('3337066', 'Brendan Dolan-Gavitt', 'brendan dolan-gavitt')<br/>('1696125', 'Siddharth Garg', 'siddharth garg')</td><td>{kang.liu,brendandg,siddharth.garg}@nyu.edu +</td></tr><tr><td>549c719c4429812dff4d02753d2db11dd490b2ae</td><td>YouTube-BoundingBoxes: A Large High-Precision <br/>Human-Annotated Data Set for Object Detection in Video <br/>Google Brain <br/>Google Brain @@ -22502,7 +28088,26 @@ <br/>Frontiers in Psychology | www.frontiersin.org <br/>September 2015 | Volume 6 | Article 1386 </td><td>('6402753', 'Peter Lewinski', 'peter lewinski')<br/>('6402753', 'Peter Lewinski', 'peter lewinski')</td><td>p.lewinski@uva.nl -</td></tr><tr><td>989332c5f1b22604d6bb1f78e606cb6b1f694e1a</td><td>Recurrent Face Aging +</td></tr><tr><td>9853136dbd7d5f6a9c57dc66060cab44a86cd662</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 34– No.2, November 2011 +<br/>Improving the Neural Network Training for Face +<br/>Recognition using Adaptive Learning Rate, Resilient +<br/>Back Propagation and Conjugate Gradient Algorithm +<br/>M.Sc. Student +<br/>Department of Electrical +<br/><b>Engineering, Iran University</b><br/>of Science and Technology, +<br/>Tehran, Iran +<br/>Saeid Sanei +<br/>Associate Professor +<br/>Department of Computing, +<br/>Faculty of Engineering and +<br/><b>Physical Sciences, University</b><br/>of Surrey, UK +<br/>Karim Mohammadi +<br/>Professor +<br/>Department of Electrical +<br/><b>Engineering, Iran University</b><br/>of Science and Technology, +<br/>Tehran, Iran +</td><td>('47250218', 'Hamed Azami', 'hamed azami')</td><td></td></tr><tr><td>989332c5f1b22604d6bb1f78e606cb6b1f694e1a</td><td>Recurrent Face Aging <br/><b>University of Trento, Italy</b><br/><b>National University of Singapore</b><br/><b>Research Center for Learning Science, Southeast University, Nanjing, China</b><br/><b>Arti cial Intelligence Institute, China</b></td><td>('39792736', 'Wei Wang', 'wei wang')<br/>('10338111', 'Zhen Cui', 'zhen cui')<br/>('32059677', 'Yan Yan', 'yan yan')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('2287686', 'Xiangbo Shu', 'xiangbo shu')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td>{wei.wang,yan.yan,niculae.sebe}@unitn.it {elefjia,eleyans}@nus.edu.sg <br/>zhen.cui@seu.edu.cn shuxb104@gmail.com </td></tr><tr><td>982f5c625d6ad0dac25d7acbce4dabfb35dd7f23</td><td>Facial Expression Recognition by SVM-based Two-stage Classifier on @@ -22545,6 +28150,21 @@ <br/>Center for Electrical Engineering and Informatics (CEEI) <br/><b>Federal University of Campina Grande (UFCG</b><br/>Campina Grande, Para´ıba, Brazil </td><td>('2092178', 'Herman Martins Gomes', 'herman martins gomes')</td><td>Email: {edumoura,hmg}@dsc.ufcg.edu.br, carvalho@dee.ufcg.edu.br +</td></tr><tr><td>9865fe20df8fe11717d92b5ea63469f59cf1635a</td><td>YUCEL ET AL.: WILDEST FACES +<br/>Wildest Faces: Face Detection and +<br/>Recognition in Violent Settings +<br/>Pinar Duygulu1 +<br/>1 Department of Computer Science +<br/><b>Hacettepe University</b><br/>Ankara, Turkey +<br/>2 Department of Computer Engineering +<br/><b>Middle East Technical University</b><br/>Ankara, Turkey +<br/>* indicates equal contribution. +</td><td>('46234524', 'Mehmet Kerim Yucel', 'mehmet kerim yucel')<br/>('39032755', 'Yunus Can Bilge', 'yunus can bilge')<br/>('46437368', 'Oguzhan Oguz', 'oguzhan oguz')<br/>('2011587', 'Nazli Ikizler-Cinbis', 'nazli ikizler-cinbis')<br/>('1939006', 'Ramazan Gokberk Cinbis', 'ramazan gokberk cinbis')</td><td>mkerimyucel@hacettepe.edu.tr +<br/>yunuscan.bilge@hacettepe.edu.tr +<br/>oguzhan.oguz@hacettepe.edu.tr +<br/>nazli@cs.hacettepe.edu.tr +<br/>pinar@cs.hacettepe.edu.tr +<br/>gcinbis@ceng.metu.edu.tr </td></tr><tr><td>98c2053e0c31fab5bcb9ce5386335b647160cc09</td><td>A Distributed Framework for Spatio-temporal Analysis on Large-scale Camera <br/>Networks <br/><b>Georgia Institute of Technology</b><br/><b>University of Stuttgart</b><br/>†SUNY Buffalo @@ -22587,7 +28207,10 @@ <br/>BANGALORE, INDIA </td><td>('39365176', 'Gouri Patil', 'gouri patil')<br/>('4787347', 'Snehalata Patil', 'snehalata patil')</td><td>Email-jyoti.spatil35@gmail.com Email-greatgouri@gmail.com <br/> Email-snehasharad09@gmail.com -</td></tr><tr><td>980266ad6807531fea94252e8f2b771c20e173b3</td><td>Continuous Regression for +</td></tr><tr><td>9825c4dddeb2ed7eaab668b55403aa2c38bc3320</td><td>Aerial Imagery for Roof Segmentation: A Large-Scale Dataset +<br/>towards Automatic Mapping of Buildings +<br/><b>aCenter for Spatial Information Science, University of Tokyo, Kashiwa 277-8568, Japan</b><br/><b>University of Waterloo, Waterloo, ON N2L 3G1, Canada</b><br/><b>cFaculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China</b><br/>dAtlasAI Inc., Waterloo, ON N2L 3G1, Canada +</td><td>('1783637', 'Qi Chen', 'qi chen')<br/>('48169641', 'Lei Wang', 'lei wang')<br/>('50117915', 'Yifan Wu', 'yifan wu')<br/>('3043983', 'Guangming Wu', 'guangming wu')<br/>('40477085', 'Zhiling Guo', 'zhiling guo')</td><td></td></tr><tr><td>980266ad6807531fea94252e8f2b771c20e173b3</td><td>Continuous Regression for <br/>Non-Rigid Image Alignment <br/>Enrique S´anchez-Lozano1 <br/>Daniel Gonz´alez-Jim´enez1 @@ -22603,7 +28226,9 @@ <br/><b>California Institute of Technology</b><br/>Pasadena, California <br/>2007 <br/>(Defended April 30, 2007) -</td><td>('3075121', 'Alex Holub', 'alex holub')</td><td></td></tr><tr><td>5334ac0a6438483890d5eef64f6db93f44aacdf4</td><td></td><td></td><td></td></tr><tr><td>53e081f5af505374c3b8491e9c4470fe77fe7934</td><td>Unconstrained Realtime Facial Performance Capture +</td><td>('3075121', 'Alex Holub', 'alex holub')</td><td></td></tr><tr><td>533d14e539ae5cdca0ece392487a2b19106d468a</td><td>Bidirectional Multirate Reconstruction for Temporal Modeling in Videos +<br/><b>University of Technology Sydney</b></td><td>('2948393', 'Linchao Zhu', 'linchao zhu')<br/>('2351434', 'Zhongwen Xu', 'zhongwen xu')<br/>('1698559', 'Yi Yang', 'yi yang')</td><td>{zhulinchao7, zhongwen.s.xu, yee.i.yang}@gmail.com +</td></tr><tr><td>5334ac0a6438483890d5eef64f6db93f44aacdf4</td><td></td><td></td><td></td></tr><tr><td>53dd25350d3b3aaf19beb2104f1e389e3442df61</td><td></td><td></td><td></td></tr><tr><td>53e081f5af505374c3b8491e9c4470fe77fe7934</td><td>Unconstrained Realtime Facial Performance Capture <br/><b>University of Southern California</b><br/>† Industrial Light & Magic <br/>Figure 1: Calibration-free realtime facial performance capture on highly occluded subjects using an RGB-D sensor. </td><td>('2519072', 'Pei-Lun Hsieh', 'pei-lun hsieh')<br/>('1797422', 'Chongyang Ma', 'chongyang ma')<br/>('2977637', 'Jihun Yu', 'jihun yu')<br/>('1706574', 'Hao Li', 'hao li')</td><td></td></tr><tr><td>53698b91709112e5bb71eeeae94607db2aefc57c</td><td>Two-Stream Convolutional Networks @@ -22614,7 +28239,7 @@ <br/><b>Nanjing University, China</b><br/>Minieye, Youjia Innovation LLC </td><td>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('2226422', 'Bin-Bin Gao', 'bin-bin gao')<br/>('15527784', 'Guoqing Liu', 'guoqing liu')</td><td>guoqing@minieye.cc <br/>wujx2001@nju.edu.cn, gaobb@lamda.nju.edu.cn -</td></tr><tr><td>5397c34a5e396658fa57e3ca0065a2878c3cced7</td><td>Lighting Normalization with Generic Intrinsic Illumination Subspace for Face +</td></tr><tr><td>530243b61fa5aea19b454b7dbcac9f463ed0460e</td><td></td><td></td><td></td></tr><tr><td>5397c34a5e396658fa57e3ca0065a2878c3cced7</td><td>Lighting Normalization with Generic Intrinsic Illumination Subspace for Face <br/>Recognition <br/><b>Institute of Information Science, Academia Sinica, Taipei, Taiwan</b></td><td>('1686057', 'Chia-Ping Chen', 'chia-ping chen')<br/>('1720473', 'Chu-Song Chen', 'chu-song chen')</td><td>{cpchen, song}@iis.sinica.edu.tw </td></tr><tr><td>539ca9db570b5e43be0576bb250e1ba7a727d640</td><td></td><td></td><td></td></tr><tr><td>539287d8967cdeb3ef60d60157ee93e8724efcac</td><td>Learning Deep (cid:96)0 Encoders @@ -22626,16 +28251,44 @@ <br/>tel: +30 2310 996361 <br/>1. INTRODUCTION </td><td>('1905139', 'Olga Zoidi', 'olga zoidi')<br/>('1718330', 'Nikos Nikolaidis', 'nikos nikolaidis')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td>{ozoidi, nikolaid, pitas}@aiia.csd.auth.gr -</td></tr><tr><td>53c8cbc4a3a3752a74f79b74370ed8aeed97db85</td><td></td><td></td><td></td></tr><tr><td>5366573e96a1dadfcd4fd592f83017e378a0e185</td><td>Böhlen, Chandola and Salunkhe +</td></tr><tr><td>53c8cbc4a3a3752a74f79b74370ed8aeed97db85</td><td></td><td></td><td></td></tr><tr><td>53c36186bf0ffbe2f39165a1824c965c6394fe0d</td><td>I Know How You Feel: Emotion Recognition with Facial Landmarks +<br/><b>Tooploox 2Polish-Japanese Academy of Information Technology 3Warsaw University of Technology</b></td><td>('22188614', 'Ivona Tautkute', 'ivona tautkute')<br/>('1760267', 'Tomasz Trzcinski', 'tomasz trzcinski')<br/>('48657002', 'Adam Bielski', 'adam bielski')</td><td>{firstname.lastname}@tooploox.com +</td></tr><tr><td>5366573e96a1dadfcd4fd592f83017e378a0e185</td><td>Böhlen, Chandola and Salunkhe <br/>Server, server in the cloud. <br/>Who is the fairest in the crowd? -</td><td></td><td></td></tr><tr><td>533bfb82c54f261e6a2b7ed7d31a2fd679c56d18</td><td>Technical Report MSU-CSE-14-1 +</td><td></td><td></td></tr><tr><td>53a41c711b40e7fe3dc2b12e0790933d9c99a6e0</td><td>Recurrent Memory Addressing for describing videos +<br/><b>Indian Institute of Technology Kharagpur</b></td><td>('7284555', 'Arnav Kumar Jain', 'arnav kumar jain')<br/>('6565766', 'Kumar Krishna Agrawal', 'kumar krishna agrawal')<br/>('1781070', 'Pabitra Mitra', 'pabitra mitra')</td><td>{arnavkj95, abhinavagarawalla, kumarkrishna, pabitra}@iitkgp.ac.in +</td></tr><tr><td>53bfe2ab770e74d064303f3bd2867e5bf7b86379</td><td>Learning to Synthesize and Manipulate Natural Images +<br/>By +<br/>A dissertation submitted in partial satisfaction of the +<br/>requirements for the degree of +<br/>Doctor of Philosophy +<br/>in +<br/>Engineering - Electrical Engineering and Computer Science +<br/>in the +<br/>Graduate Division +<br/>of the +<br/><b>University of California, Berkeley</b><br/>Committee in charge: +<br/>Professor Alexei A. Efros, Chair +<br/>Professor Jitendra Malik +<br/>Professor Ren Ng +<br/>Professor Michael DeWeese +<br/>Fall 2017 +</td><td>('3132726', 'Junyan Zhu', 'junyan zhu')</td><td></td></tr><tr><td>533bfb82c54f261e6a2b7ed7d31a2fd679c56d18</td><td>Technical Report MSU-CSE-14-1 <br/>Unconstrained Face Recognition: Identifying a <br/>Person of Interest from a Media Collection </td><td>('2180413', 'Lacey Best-Rowden', 'lacey best-rowden')<br/>('34393045', 'Hu Han', 'hu han')<br/>('40653304', 'Charles Otto', 'charles otto')<br/>('1817623', 'Brendan Klare', 'brendan klare')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>537d8c4c53604fd419918ec90d6ef28d045311d0</td><td>Active Collaborative Ensemble Tracking <br/><b>Graduate School of Informatics, Kyoto University</b><br/>Yoshida-Honmachi, Sakyo Ward, Kyoto 606–8501, Japan </td><td>('2146623', 'Kourosh Meshgi', 'kourosh meshgi')<br/>('31095396', 'Maryam Sadat Mirzaei', 'maryam sadat mirzaei')<br/>('38809507', 'Shigeyuki Oba', 'shigeyuki oba')<br/>('2851612', 'Shin Ishii', 'shin ishii')</td><td>meshgi-k@sys.i.kyoto-u.ac.jp -</td></tr><tr><td>530ce1097d0681a0f9d3ce877c5ba31617b1d709</td><td></td><td></td><td></td></tr><tr><td>3fbd68d1268922ee50c92b28bd23ca6669ff87e5</td><td>598 +</td></tr><tr><td>530ce1097d0681a0f9d3ce877c5ba31617b1d709</td><td></td><td></td><td></td></tr><tr><td>53ce84598052308b86ba79d873082853022aa7e9</td><td>Optimized Method for Real-Time Face Recognition System Based +<br/>on PCA and Multiclass Support Vector Machine +<br/><b>IEEE Member, Shahid Rajaee Teacher training University</b><br/>Tehran, Iran +<br/><b>Institute of Computer science, Shahid Bahonar University</b><br/>Shiraz, Iran +<br/><b>Islamic Azad University, Science and Research Campus</b><br/>Hamedan, Iran +</td><td>('1763181', 'Reza Azad', 'reza azad')<br/>('39864738', 'Babak Azad', 'babak azad')<br/>('2904132', 'Iman Tavakoli Kazerooni', 'iman tavakoli kazerooni')</td><td>rezazad68@gmail.com +<br/>babak.babi72@gmail.com +<br/>iman_tavakoli2008@yahoo.com +</td></tr><tr><td>3fbd68d1268922ee50c92b28bd23ca6669ff87e5</td><td>598 <br/>IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 10, NO. 4, APRIL 2001 <br/>A Shape- and Texture-Based Enhanced Fisher <br/>Classifier for Face Recognition @@ -22688,7 +28341,12 @@ <br/>http://crcv.ucf.edu/projects/DaMN/ </td><td>('2099254', 'Rui Hou', 'rui hou')<br/>('40029556', 'Amir Roshan Zamir', 'amir roshan zamir')<br/>('1694199', 'Rahul Sukthankar', 'rahul sukthankar')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td></td></tr><tr><td>3fb26f3abcf0d287243646426cd5ddeee33624d4</td><td>Joint Training of Cascaded CNN for Face Detection <br/><b>Grad. School at Shenzhen, Tsinghua University</b><br/><b>Tsinghua University 4SenseTime</b></td><td>('2137185', 'Hongwei Qin', 'hongwei qin')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('2693308', 'Xiu Li', 'xiu li')<br/>('1705418', 'Xiaolin Hu', 'xiaolin hu')</td><td>{qhw12@mails., li.xiu@sz., xlhu@}tsinghua.edu.cn yanjunjie@outlook.com -</td></tr><tr><td>3f57c3fc2d9d4a230ccb57eed1d4f0b56062d4d5</td><td>Face Recognition Across Poses Using A Single 3D Reference Model +</td></tr><tr><td>3f9ca2526013e358cd8caeb66a3d7161f5507cbc</td><td>Improving Sparse Representation-Based Classification +<br/>Using Local Principal Component Analysis +<br/>Department of Mathematics +<br/><b>University of California, Davis</b><br/>One Shields Avenue +<br/>Davis, California, 95616, United States +</td><td>('32898818', 'Chelsea Weaver', 'chelsea weaver')<br/>('3493752', 'Naoki Saito', 'naoki saito')</td><td></td></tr><tr><td>3f57c3fc2d9d4a230ccb57eed1d4f0b56062d4d5</td><td>Face Recognition Across Poses Using A Single 3D Reference Model <br/><b>National Taiwan University of Science and Technology</b><br/>No. 43, Sec.4, Keelung Rd., Taipei, 106, Taiwan </td><td>('38801529', 'Gee-Sern Hsu', 'gee-sern hsu')<br/>('3329222', 'Hsiao-Chia Peng', 'hsiao-chia peng')</td><td>∗jison@mail.ntust.edu.tw </td></tr><tr><td>3feb69531653e83d0986a0643e4a6210a088e3e5</td><td>Using Group Prior to Identify People in Consumer Images @@ -22698,7 +28356,9 @@ <br/>tsuhan@cmu.edu </td></tr><tr><td>3f12701449a82a5e01845001afab3580b92da858</td><td>Joint Object Class Sequencing and Trajectory <br/>Triangulation (JOST) -<br/><b>The University of North Carolina, Chapel Hill</b></td><td>('2873326', 'Enliang Zheng', 'enliang zheng')<br/>('1751643', 'Ke Wang', 'ke wang')<br/>('29274093', 'Enrique Dunn', 'enrique dunn')<br/>('40454588', 'Jan-Michael Frahm', 'jan-michael frahm')</td><td></td></tr><tr><td>3fde656343d3fd4223e08e0bc835552bff4bda40</td><td>Available Online at www.ijcsmc.com +<br/><b>The University of North Carolina, Chapel Hill</b></td><td>('2873326', 'Enliang Zheng', 'enliang zheng')<br/>('1751643', 'Ke Wang', 'ke wang')<br/>('29274093', 'Enrique Dunn', 'enrique dunn')<br/>('40454588', 'Jan-Michael Frahm', 'jan-michael frahm')</td><td></td></tr><tr><td>3fb98e76ffd8ba79e1c22eda4d640da0c037e98a</td><td>Convolutional Neural Networks for Crop Yield Prediction using Satellite Images +<br/>H. Russello +</td><td></td><td></td></tr><tr><td>3fde656343d3fd4223e08e0bc835552bff4bda40</td><td>Available Online at www.ijcsmc.com <br/>International Journal of Computer Science and Mobile Computing <br/>A Monthly Journal of Computer Science and Information Technology <br/>ISSN 2320–088X @@ -22744,7 +28404,14 @@ <br/>system uses Gabor <br/>images produces Gabor </td><td>('1810015', 'Dakshina Ranjan Kisku', 'dakshina ranjan kisku')<br/>('1868921', 'Hunny Mehrotra', 'hunny mehrotra')<br/>('1687389', 'Phalguni Gupta', 'phalguni gupta')<br/>('1786127', 'Jamuna Kanta Sing', 'jamuna kanta sing')</td><td>drkisku@ieee.org; hunny04@gmail.com; pg@cse.iitk.ac.in; , jksing@ieee.org -</td></tr><tr><td>3f5cf3771446da44d48f1d5ca2121c52975bb3d3</td><td></td><td></td><td></td></tr><tr><td>3f14b504c2b37a0e8119fbda0eff52efb2eb2461</td><td>5727 +</td></tr><tr><td>3f5cf3771446da44d48f1d5ca2121c52975bb3d3</td><td></td><td></td><td></td></tr><tr><td>3fb4bf38d34f7f7e5b3df36de2413d34da3e174a</td><td>THOMAS AND KOVASHKA: PERSUASIVE FACES: GENERATING FACES IN ADS +<br/>Persuasive Faces: Generating Faces in +<br/>Advertisements +<br/>Department of Computer Science +<br/><b>University of Pittsburgh</b><br/>Pittsburgh, PA USA +</td><td>('40540691', 'Christopher Thomas', 'christopher thomas')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td>chris@cs.pitt.edu +<br/>kovashka@cs.pitt.edu +</td></tr><tr><td>3f14b504c2b37a0e8119fbda0eff52efb2eb2461</td><td>5727 <br/>Joint Facial Action Unit Detection and Feature <br/>Fusion: A Multi-Conditional Learning Approach </td><td>('2308430', 'Stefanos Eleftheriadis', 'stefanos eleftheriadis')<br/>('1729713', 'Ognjen Rudovic', 'ognjen rudovic')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>3fac7c60136a67b320fc1c132fde45205cd2ac66</td><td>Remarks on Computational Facial Expression @@ -22753,7 +28420,13 @@ <br/><b>Information Systems Design, Doshisha University, Kyoto, Japan</b><br/><b>Graduate School of Doshisha University, Kyoto, Japan</b><br/><b>Intelligent Information Engineering and Science, Doshisha University, Kyoto, Japan</b></td><td>('39452921', 'Kazuhiko Takahashi', 'kazuhiko takahashi')<br/>('10728256', 'Sae Takahashi', 'sae takahashi')<br/>('1824476', 'Yunduan Cui', 'yunduan cui')<br/>('2565962', 'Masafumi Hashimoto', 'masafumi hashimoto')</td><td>{katakaha@mail,buj1078@mail4}.doshisha.ac.jp <br/>dum3101@mail4.doshisha.ac.jp <br/>mhashimo@mail.doshisha.ac.jp -</td></tr><tr><td>3fd90098551bf88c7509521adf1c0ba9b5dfeb57</td><td>Page 1 of 21 +</td></tr><tr><td>3f9a7d690db82cf5c3940fbb06b827ced59ec01e</td><td>VIP: Finding Important People in Images +<br/>Virginia Tech +<br/>Google Inc. +<br/>Virginia Tech +<br/>Project: https://computing.ece.vt.edu/~mclint/vip/ +<br/>Demo: http://cloudcv.org/vip/ +</td><td>('3085140', 'Clint Solomon Mathialagan', 'clint solomon mathialagan')<br/>('39460815', 'Andrew C. Gallagher', 'andrew c. gallagher')<br/>('1746610', 'Dhruv Batra', 'dhruv batra')</td><td></td></tr><tr><td>3fd90098551bf88c7509521adf1c0ba9b5dfeb57</td><td>Page 1 of 21 <br/>*****For Peer Review Only***** <br/>10 <br/>11 @@ -22824,7 +28497,18 @@ </td><td>('2108310', 'TIWUYA H. FAAYA', 'tiwuya h. faaya')</td><td></td></tr><tr><td>3f7723ab51417b85aa909e739fc4c43c64bf3e84</td><td>Improved Performance in Facial Expression <br/>Recognition Using 32 Geometric Features <br/><b>University of Bari, Bari, Italy</b><br/><b>National Institute of Optics, National Research Council, Arnesano, LE, Italy</b></td><td>('2235498', 'Giuseppe Palestra', 'giuseppe palestra')<br/>('39814343', 'Adriana Pettinicchio', 'adriana pettinicchio')<br/>('33097940', 'Marco Del Coco', 'marco del coco')<br/>('4730472', 'Marco Leo', 'marco leo')<br/>('1741861', 'Cosimo Distante', 'cosimo distante')</td><td>giuseppe.palestra@gmail.com -</td></tr><tr><td>3f63f9aaec8ba1fa801d131e3680900680f14139</td><td>Facial Expression Recognition using Local Binary +</td></tr><tr><td>3f5e8f884e71310d7d5571bd98e5a049b8175075</td><td>Making a Science of Model Search: Hyperparameter Optimization +<br/>in Hundreds of Dimensions for Vision Architectures +<br/>J. Bergstra +<br/><b>Rowland Institute at Harvard</b><br/>100 Edwin H. Land Boulevard +<br/>Cambridge, MA 02142, USA +<br/>D. Yamins +<br/>Department of Brain and Cognitive Sciences +<br/><b>Massachusetts Institute of Technology</b><br/>Cambridge, MA 02139, USA +<br/>D. D. Cox +<br/><b>Rowland Institute at Harvard</b><br/>100 Edwin H. Land Boulevard +<br/>Cambridge, MA 02142, USA +</td><td></td><td></td></tr><tr><td>3f63f9aaec8ba1fa801d131e3680900680f14139</td><td>Facial Expression Recognition using Local Binary <br/>Patterns and Kullback Leibler Divergence <br/>AnushaVupputuri, SukadevMeher <br/> @@ -22839,9 +28523,24 @@ </td><td>('3310120', 'Ali Diba', 'ali diba')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>ali.diba@esat.kuleuven.be <br/>pazandeh@ee.sharif.ir <br/>luc.vangool@esat.kuleuven.be +</td></tr><tr><td>3f5693584d7dab13ffc12122d6ddbf862783028b</td><td>Ranking CGANs: Subjective Control over Semantic Image +<br/>Attributes +<br/><b>University of Bath</b></td><td>('41020280', 'Yassir Saquil', 'yassir saquil')<br/>('1808255', 'Kwang In Kim', 'kwang in kim')</td><td></td></tr><tr><td>30b15cdb72760f20f80e04157b57be9029d8a1ab</td><td>Face Aging with Identity-Preserved +<br/>Conditional Generative Adversarial Networks +<br/><b>Shanghaitech University</b><br/>Baidu +<br/><b>Shanghaitech University</b></td><td>('50219041', 'Zongwei Wang', 'zongwei wang')<br/>('48785141', 'Xu Tang', 'xu tang')<br/>('2074878', 'Weixin Luo', 'weixin luo')<br/>('1702868', 'Shenghua Gao', 'shenghua gao')</td><td>wangzw@shanghaitech.edu.cn +<br/>tangxu02@baidu.com +<br/>{luowx, gaoshh}@shanghaitech.edu.cn </td></tr><tr><td>3039627fa612c184228b0bed0a8c03c7f754748c</td><td>Robust Regression on Image Manifolds for Ordered Label Denoising <br/><b>University of North Carolina at Charlotte</b></td><td>('1873911', 'Hui Wu', 'hui wu')<br/>('1690110', 'Richard Souvenir', 'richard souvenir')</td><td>{hwu13,souvenir}@uncc.edu -</td></tr><tr><td>303065c44cf847849d04da16b8b1d9a120cef73a</td><td></td><td></td><td></td></tr><tr><td>303a7099c01530fa0beb197eb1305b574168b653</td><td>Occlusion-free Face Alignment: Deep Regression Networks Coupled with +</td></tr><tr><td>30870ef75aa57e41f54310283c0057451c8c822b</td><td>Overcoming Catastrophic Forgetting with Hard Attention to the Task +</td><td>('50101040', 'Marius Miron', 'marius miron')</td><td></td></tr><tr><td>303065c44cf847849d04da16b8b1d9a120cef73a</td><td></td><td></td><td></td></tr><tr><td>305346d01298edeb5c6dc8b55679e8f60ba97efb</td><td>Article +<br/>Fine-Grained Face Annotation Using Deep +<br/>Multi-Task CNN +<br/><b>Systems and Communication, University of Milano-Bicocca</b><br/>Received: 3 July 2018; Accepted: 13 August 2018; Published: 14 August 2018 +</td><td>('3390122', 'Luigi Celona', 'luigi celona')<br/>('2217051', 'Simone Bianco', 'simone bianco')<br/>('1743714', 'Raimondo Schettini', 'raimondo schettini')</td><td>viale Sarca, 336 Milano, Italy; bianco@disco.unimib.it (S.B.); schettini@disco.unimib.it (R.S.) +<br/>* Correspondence: luigi.celona@disco.unimib.it +</td></tr><tr><td>303a7099c01530fa0beb197eb1305b574168b653</td><td>Occlusion-free Face Alignment: Deep Regression Networks Coupled with <br/>De-corrupt AutoEncoders <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), <br/><b>Institute of Computing Technology, CAS, Beijing 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b><br/>3CAS Center for Excellence in Brain Science and Intelligence Technology @@ -22857,7 +28556,14 @@ <br/>Face Recognition <br/>Galaxy Global Imperial Technical Campus <br/>Galaxy Global Imperial Technical Campus -<br/><b>DIT UNIVERSITY, DEHRADUN</b></td><td>('34272062', 'PRACHI BANSAL', 'prachi bansal')</td><td></td></tr><tr><td>309e17e6223e13b1f76b5b0eaa123b96ef22f51b</td><td>Face Recognition based on a 3D Morphable Model +<br/><b>DIT UNIVERSITY, DEHRADUN</b></td><td>('34272062', 'PRACHI BANSAL', 'prachi bansal')</td><td></td></tr><tr><td>30fd1363fa14965e3ab48a7d6235e4b3516c1da1</td><td>A Deep Semi-NMF Model for Learning Hidden Representations +<br/>Stefanos Zafeiriou +<br/>Bj¨orn W. Schuller +<br/><b>Imperial College London, United Kingdom</b></td><td>('2814229', 'George Trigeorgis', 'george trigeorgis')<br/>('2732737', 'Konstantinos Bousmalis', 'konstantinos bousmalis')</td><td>GEORGE.TRIGEORGIS08@IMPERIAL.AC.UK +<br/>K.BOUSMALIS@IMPERIAL.AC.UK +<br/>S.ZAFEIRIOU@IMPERIAL.AC.UK +<br/>BJOERN.SCHULLER@IMPERIAL.AC.UK +</td></tr><tr><td>309e17e6223e13b1f76b5b0eaa123b96ef22f51b</td><td>Face Recognition based on a 3D Morphable Model <br/><b>University of Siegen</b><br/>H¤olderlinstr. 3 <br/>57068 Siegen, Germany </td><td>('2880906', 'Volker Blanz', 'volker blanz')</td><td>blanz@informatik.uni-siegen.de @@ -23017,7 +28723,9 @@ <br/>labeled samples. <br/>The third contribution is to apply a recently proposed machine learning technique called <br/>covariate shift adaptation (Shimodaira, 2000; Sugiyama & Kawanabe, 2011; Sugiyama et al., -</td><td>('2163491', 'Kazuya Ueki', 'kazuya ueki')<br/>('1853974', 'Yasuyuki Ihara', 'yasuyuki ihara')<br/>('1719221', 'Masashi Sugiyama', 'masashi sugiyama')</td><td></td></tr><tr><td>302c9c105d49c1348b8f1d8cc47bead70e2acf08</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2710120, IEEE +</td><td>('2163491', 'Kazuya Ueki', 'kazuya ueki')<br/>('1853974', 'Yasuyuki Ihara', 'yasuyuki ihara')<br/>('1719221', 'Masashi Sugiyama', 'masashi sugiyama')</td><td></td></tr><tr><td>30cbd41e997445745b6edd31f2ebcc7533453b61</td><td>What Makes a Video a Video: Analyzing Temporal Information in Video +<br/>Understanding Models and Datasets +<br/><b>Stanford University, 2Facebook, 3Dartmouth College</b></td><td>('38485317', 'De-An Huang', 'de-an huang')<br/>('34066479', 'Vignesh Ramanathan', 'vignesh ramanathan')<br/>('49274550', 'Dhruv Mahajan', 'dhruv mahajan')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')<br/>('2210374', 'Manohar Paluri', 'manohar paluri')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')</td><td></td></tr><tr><td>302c9c105d49c1348b8f1d8cc47bead70e2acf08</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TCSVT.2017.2710120, IEEE <br/>Transactions on Circuits and Systems for Video Technology <br/>IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY <br/>Unconstrained Face Recognition Using A Set-to-Set @@ -23034,11 +28742,14 @@ <br/><b>Queensland University of Technology(QUT</b></td><td>('2256817', 'Fahimeh Rezazadegan', 'fahimeh rezazadegan')<br/>('34686772', 'Sareh Shirazi', 'sareh shirazi')<br/>('1771913', 'Niko Sünderhauf', 'niko sünderhauf')<br/>('1809144', 'Michael Milford', 'michael milford')<br/>('1803115', 'Ben Upcroft', 'ben upcroft')</td><td>fahimeh.rezazadegan@qut.edu.au </td></tr><tr><td>5e59193a0fc22a0c37301fb05b198dd96df94266</td><td>Example-Based Modeling of Facial Texture from Deficient Data <br/>1 IMB / LaBRI, Universit´e de Bordeaux, France -<br/><b>University of York, UK</b></td><td>('34895713', 'Arnaud Dessein', 'arnaud dessein')<br/>('1679753', 'Edwin R. Hancock', 'edwin r. hancock')<br/>('1687021', 'William A. P. Smith', 'william a. p. smith')<br/>('1718243', 'Richard C. Wilson', 'richard c. wilson')</td><td></td></tr><tr><td>5e0eb34aeb2b58000726540336771053ecd335fc</td><td>Low-Quality Video Face Recognition with Deep +<br/><b>University of York, UK</b></td><td>('34895713', 'Arnaud Dessein', 'arnaud dessein')<br/>('1679753', 'Edwin R. Hancock', 'edwin r. hancock')<br/>('1687021', 'William A. P. Smith', 'william a. p. smith')<br/>('1718243', 'Richard C. Wilson', 'richard c. wilson')</td><td></td></tr><tr><td>5e6f546a50ed97658be9310d5e0a67891fe8a102</td><td>Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? +<br/><b>National Institute of Advanced Industrial Science and Technology (AIST</b><br/>Tsukuba, Ibaraki, Japan +</td><td>('2199251', 'Kensho Hara', 'kensho hara')<br/>('1730200', 'Hirokatsu Kataoka', 'hirokatsu kataoka')<br/>('1732705', 'Yutaka Satoh', 'yutaka satoh')</td><td>{kensho.hara, hirokatsu.kataoka, yu.satou}@aist.go.jp +</td></tr><tr><td>5e0eb34aeb2b58000726540336771053ecd335fc</td><td>Low-Quality Video Face Recognition with Deep <br/>Networks and Polygonal Chain Distance <br/><b>Vision and Fusion Lab, Karlsruhe Institute of Technology KIT, Karlsruhe, Germany</b><br/>†Fraunhofer IOSB, Karlsruhe, Germany </td><td>('37646107', 'Christian Herrmann', 'christian herrmann')<br/>('1783486', 'Dieter Willersinn', 'dieter willersinn')</td><td>{christian.herrmann|dieter.willersinn|juergen.beyerer}@iosb.fraunhofer.de -</td></tr><tr><td>5e28673a930131b1ee50d11f69573c17db8fff3e</td><td>Author manuscript, published in "Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France +</td></tr><tr><td>5e7e055ef9ba6e8566a400a8b1c6d8f827099553</td><td></td><td></td><td>Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreadingprocess.Copyright © 2018 the authorsThis Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version.Research Articles: Behavioral/CognitiveOn the role of cortex-basal ganglia interactions for category learning: Aneuro-computational approachFrancesc Villagrasa1, Javier Baladron1, Julien Vitay1, Henning Schroll1, Evan G. Antzoulatos2, Earl K.Miller3 and Fred H. Hamker11Chemnitz University of Technology, Department of Computer Science, 09107 Chemnitz, Germany2UC Davis Center for Neuroscience and Department of Neurobiology, Physiology and Behavior, Davis, CA95616, United States3The Picower Institute for Learning and Memory and Department of Brain and Cognitive Sciences,Massachusetts Institute of Technology, Cambridge, MA 02139, United StatesDOI: 10.1523/JNEUROSCI.0874-18.2018Received: 5 April 2018Revised: 7 August 2018Accepted: 28 August 2018Published: 18 September 2018Author contributions: F.V., J.V., E.G.A., and F.H.H. performed research; F.V., J.B., J.V., H.S., E.G.A., andE.K.M. analyzed data; F.V. wrote the first draft of the paper; J.B. and F.H.H. designed research; J.B., J.V., H.S.,E.G.A., E.K.M., and F.H.H. edited the paper; F.H.H. wrote the paper.Conflict of Interest: The authors declare no competing financial interests.This work has been supported by the German Research Foundation (DFG, grant agreements no. HA2630/4-2and HA2630/8-1), the European Social Fund and the Free State of Saxony (ESF, grant agreement no.ESF-100269974), the NIMH R01MH065252, and the MIT Picower Institute Innovation Fund.Corresponding author: Fred H. Hamker, fred.hamker@informatik.tu-chemnitz.de, 09107 Chemnitz, GermanyCite as: J. Neurosci ; 10.1523/JNEUROSCI.0874-18.2018Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formattedversion of this article is published. </td></tr><tr><td>5e28673a930131b1ee50d11f69573c17db8fff3e</td><td>Author manuscript, published in "Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : France <br/>(2008)" </td><td></td><td></td></tr><tr><td>5ea9063b44b56d9c1942b8484572790dff82731e</td><td>MULTICLASS SUPPORT VECTOR MACHINES AND METRIC MULTIDIMENSIONAL <br/>SCALING FOR FACIAL EXPRESSION RECOGNITION @@ -23126,7 +28837,12 @@ </td><td>('7484236', 'Mohammad Shahidul Islam', 'mohammad shahidul islam')</td><td></td></tr><tr><td>5b7cb9b97c425b52b2e6f41ba8028836029c4432</td><td>Smooth Representation Clustering <br/>1State Key Laboratory on Intelligent Technology and Systems, TNList <br/><b>Tsinghua University</b><br/><b>Key Lab. of Machine Perception, School of EECS, Peking University</b></td><td>('40234323', 'Han Hu', 'han hu')<br/>('33383055', 'Zhouchen Lin', 'zhouchen lin')<br/>('2632601', 'Jianjiang Feng', 'jianjiang feng')<br/>('39491387', 'Jie Zhou', 'jie zhou')</td><td>huh04@mails.thu.edu.cn, zlin@pku.edu.cn, {jfeng,jzhou}@tsinghua.edu.cn -</td></tr><tr><td>5b6f0a508c1f4097dd8dced751df46230450b01a</td><td>Finding Lost Children +</td></tr><tr><td>5ba7882700718e996d576b58528f1838e5559225</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TAFFC.2016.2628787, IEEE +<br/>Transactions on Affective Computing +<br/>IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, VOL. X, NO. X, OCTOBER 2016 +<br/>Predicting Personalized Image Emotion +<br/>Perceptions in Social Networks +</td><td>('1755487', 'Sicheng Zhao', 'sicheng zhao')<br/>('1720100', 'Hongxun Yao', 'hongxun yao')<br/>('33375873', 'Yue Gao', 'yue gao')<br/>('38329336', 'Guiguang Ding', 'guiguang ding')<br/>('1684968', 'Tat-Seng Chua', 'tat-seng chua')</td><td></td></tr><tr><td>5b6f0a508c1f4097dd8dced751df46230450b01a</td><td>Finding Lost Children <br/>Ashley Michelle Eden <br/>Electrical Engineering and Computer Sciences <br/><b>University of California at Berkeley</b><br/>Technical Report No. UCB/EECS-2010-174 @@ -23161,7 +28877,28 @@ <br/>Dean, Graduate School </td><td></td><td></td></tr><tr><td>5bae9822d703c585a61575dced83fa2f4dea1c6d</td><td>MOTChallenge 2015: <br/>Towards a Benchmark for Multi-Target Tracking -</td><td>('34761498', 'Anton Milan', 'anton milan')<br/>('34493380', 'Stefan Roth', 'stefan roth')<br/>('1803034', 'Konrad Schindler', 'konrad schindler')</td><td></td></tr><tr><td>5bb87c7462c6c1ec5d60bde169c3a785ba5ea48f</td><td>Targeting Ultimate Accuracy: Face Recognition via Deep Embedding +</td><td>('34761498', 'Anton Milan', 'anton milan')<br/>('34493380', 'Stefan Roth', 'stefan roth')<br/>('1803034', 'Konrad Schindler', 'konrad schindler')</td><td></td></tr><tr><td>5b0008ba87667085912ea474025d2323a14bfc90</td><td>SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace +<br/>Clustering Algorithms∗ +<br/>Electrical and Computer Engineering +<br/><b>Northeastern University, Boston, MA</b></td><td>('1687866', 'Mario Sznaier', 'mario sznaier')</td><td>{msznaier,camps}@coe.neu.edu +</td></tr><tr><td>5b97e997b9b654373bd129b3baf5b82c2def13d1</td><td>3D Face Tracking and Texture Fusion in the Wild +<br/>Centre for Vision, Speech and Signal Processing +<br/>Image Understanding and Interactive Robotics +<br/><b>University of Surrey</b><br/>Guildford, GU2 7XH, United Kingdom +<br/>Contact: http://www.patrikhuber.ch +<br/><b>Reutlingen University</b><br/>D-72762 Reutlingen, Germany +</td><td>('39976184', 'Patrik Huber', 'patrik huber')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('49330989', 'Philipp Kopp', 'philipp kopp')</td><td></td></tr><tr><td>5bd3d08335bb4e444a86200c5e9f57fd9d719e14</td><td>3D Face Morphable Models “In-the-Wild” +<br/>,∗ +<br/>Stefanos Zafeiriou1 +<br/><b>Imperial College London, UK</b><br/>2Amazon, Berlin, Germany +<br/><b>University of Oulu, Finland</b></td><td>('47456731', 'James Booth', 'james booth')<br/>('2788012', 'Epameinondas Antonakos', 'epameinondas antonakos')<br/>('2015036', 'Stylianos Ploumpis', 'stylianos ploumpis')<br/>('2814229', 'George Trigeorgis', 'george trigeorgis')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')</td><td>1{james.booth,s.ploumpis,g.trigeorgis,i.panagakis,s.zafeiriou}@imperial.ac.uk +<br/>2antonak@amazon.com +</td></tr><tr><td>5babbad3daac5c26503088782fd5b62067b94fa5</td><td>Are You Sure You Want To Do That? +<br/>Classification with Verification +</td><td>('31920847', 'Harris Chan', 'harris chan')<br/>('36964031', 'Atef Chaudhury', 'atef chaudhury')<br/>('50715871', 'Kevin Shen', 'kevin shen')</td><td>hchan@cs.toronto.edu +<br/>atef@cs.toronto.edu +<br/>shenkev@cs.toronto.edu +</td></tr><tr><td>5bb87c7462c6c1ec5d60bde169c3a785ba5ea48f</td><td>Targeting Ultimate Accuracy: Face Recognition via Deep Embedding <br/><b>Baidu Research Institute of Deep Learning</b></td><td>('2272123', 'Jingtuo Liu', 'jingtuo liu')</td><td></td></tr><tr><td>5b9d9f5a59c48bc8dd409a1bd5abf1d642463d65</td><td>Evolving Systems. manuscript No. <br/>(will be inserted by the editor) <br/>An evolving spatio-temporal approach for gender and age @@ -23174,7 +28911,7 @@ <br/>IIIT-Delhi, New Delhi, India <br/>Article history: <br/>Received 29 March 2017 -</td><td>('40639989', 'Akshay Sethi', 'akshay sethi')<br/>('2220719', 'Maneet Singh', 'maneet singh')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td></td></tr><tr><td>5b01d4338734aefb16ee82c4c59763d3abc008e6</td><td>A Robust Face Recognition Algorithm Based on Kernel Regularized +</td><td>('40639989', 'Akshay Sethi', 'akshay sethi')<br/>('2220719', 'Maneet Singh', 'maneet singh')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td></td></tr><tr><td>5b2cfee6e81ef36507ebf3c305e84e9e0473575a</td><td></td><td></td><td></td></tr><tr><td>5b01d4338734aefb16ee82c4c59763d3abc008e6</td><td>A Robust Face Recognition Algorithm Based on Kernel Regularized <br/>Relevance-Weighted Discriminant Analysis <br/> <br/><b>Hunan Provincial Key Laboratory of Wind Generator and Its Control, Hunan Institute of Engineering, Xiangtan, China</b><br/><b>College of Electrical and Information Engineering</b><br/>or @@ -23186,7 +28923,18 @@ <br/>from <br/>this paper, we propose an effective </td><td>('38296532', 'Di WU', 'di wu')<br/>('38296532', 'Di WU', 'di wu')</td><td> [e-mail: wudi6152007@163.com] -</td></tr><tr><td>5b6ecbf5f1eecfe1a9074d31fe2fb030d75d9a79</td><td>Improving 3D Face Details based on Normal Map of Hetero-source Images +</td></tr><tr><td>5b721f86f4a394f05350641e639a9d6cb2046c45</td><td>A short version of this paper is accepted to ACM Asia Conference on Computer and Communications Security (ASIACCS) 2018 +<br/>Detection under Privileged Information (Full Paper)∗ +<br/><b>Pennsylvania State University</b><br/>Patrick McDaniel +<br/><b>Pennsylvania State University</b><br/>Vencore Labs +<br/><b>Pennsylvania State University</b><br/><b>Army Research Laboratory</b></td><td>('2950892', 'Z. Berkay Celik', 'z. berkay celik')<br/>('1804289', 'Rauf Izmailov', 'rauf izmailov')<br/>('1967156', 'Nicolas Papernot', 'nicolas papernot')<br/>('9541640', 'Ryan Sheatsley', 'ryan sheatsley')<br/>('30792942', 'Raquel Alvarez', 'raquel alvarez')<br/>('1703726', 'Ananthram Swami', 'ananthram swami')</td><td>zbc102@cse.psu.edu +<br/>mcdaniel@cse.psu.edu +<br/>rizmailov@appcomsci.com +<br/>{ngp5056,rms5643,rva5120}@cse.psu.edu +<br/>ananthram.swami.civ@mail.mil +</td></tr><tr><td>5b4b84ce3518c8a14f57f5f95a1d07fb60e58223</td><td>Diagnosing Error in Object Detectors +<br/>Department of Computer Science +<br/><b>University of Illinois at Urbana-Champaign</b></td><td>('2433269', 'Derek Hoiem', 'derek hoiem')<br/>('2918391', 'Yodsawalai Chodpathumwan', 'yodsawalai chodpathumwan')<br/>('2279233', 'Qieyun Dai', 'qieyun dai')</td><td></td></tr><tr><td>5b6ecbf5f1eecfe1a9074d31fe2fb030d75d9a79</td><td>Improving 3D Face Details based on Normal Map of Hetero-source Images <br/><b>Tsinghua University</b><br/>Beijing, 100084, China </td><td>('8100333', 'Chang Yang', 'chang yang')<br/>('1752427', 'Jiansheng Chen', 'jiansheng chen')<br/>('1949216', 'Nan Su', 'nan su')<br/>('7284296', 'Guangda Su', 'guangda su')</td><td>yangchang11@mails.tsinghua.edu.cn, jschenthu@tsinghua.edu.cn <br/>v377026@sina.com, susu@tsinghua.edu.cn @@ -23383,6 +29131,14 @@ </td></tr><tr><td>37619564574856c6184005830deda4310d3ca580</td><td>A Deep Pyramid Deformable Part Model for Face Detection <br/>Center for Automation Research <br/><b>University of Maryland, College Park, MD</b></td><td>('26988560', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{rranjan1, pvishalm, rama}@umiacs.umd.edu +</td></tr><tr><td>372fb32569ced35eaf3740a29890bec2be1869fa</td><td>Running head: MU RHYTHM MODULATION BY CLASSIFICATION OF EMOTION 1 +<br/>Mu rhythm suppression is associated with the classification of emotion in faces +<br/><b>University of Otago, Dunedin, New Zealand</b><br/>Corresponding authors: +<br/>Phone: +64 (3) 479 5269; Fax: +64 (3) 479 8335 +<br/>Department of Psychology +<br/><b>University of Otago</b><br/>PO Box 56 +<br/>Dunedin, New Zealand +</td><td>('2187036', 'Elizabeth A. Franz', 'elizabeth a. franz')</td><td>Matthew Moore (matthew.moore@otago.ac.nz) & Liz Franz (lfranz@psy.otago.ac.nz) </td></tr><tr><td>37ce1d3a6415d6fc1760964e2a04174c24208173</td><td>Pose-Invariant 3D Face Alignment <br/>Department of Computer Science and Engineering <br/><b>Michigan State University, East Lansing MI</b></td><td>('2357264', 'Amin Jourabloo', 'amin jourabloo')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>{jourablo, liuxm}@msu.edu @@ -23447,7 +29203,15 @@ <br/>Approach <br/>Anonymous WACV submission <br/>Paper ID 394 -</td><td></td><td></td></tr><tr><td>37278ffce3a0fe2c2bbf6232e805dd3f5267eba3</td><td>Can we still avoid automatic face detection? +</td><td></td><td></td></tr><tr><td>3795974e24296185d9b64454cde6f796ca235387</td><td>Finding your Lookalike: +<br/>Measuring Face Similarity Rather than Face Identity +<br/><b>Lafayette College</b><br/>Easton, PA +<br/>Andrew Gallagher +<br/>Google Research +<br/>Mountain View, CA +</td><td>('1803066', 'Amir Sadovnik', 'amir sadovnik')<br/>('50977255', 'Wassim Gharbi', 'wassim gharbi')<br/>('2197717', 'Thanh Vu', 'thanh vu')</td><td>{sadovnia,gharbiw,vut}@lafayette.edu +<br/>agallagher@google.com +</td></tr><tr><td>37278ffce3a0fe2c2bbf6232e805dd3f5267eba3</td><td>Can we still avoid automatic face detection? <br/>Serge Belongie1,2 <br/><b>Cornell University 2 Cornell Tech</b></td><td>('3035230', 'Michael J. Wilber', 'michael j. wilber')<br/>('1723945', 'Vitaly Shmatikov', 'vitaly shmatikov')</td><td></td></tr><tr><td>377a1be5113f38297716c4bb951ebef7a93f949a</td><td>Dear Faculty, IGERT Fellows, IGERT Associates and Students, <br/>You are cordially invited to attend a Seminar presented by Albert Cruz. Please @@ -23485,12 +29249,36 @@ </td><td>('40564016', 'Dragomir Dimitrov', 'dragomir dimitrov')<br/>('1736011', 'Stefano Lonardi', 'stefano lonardi')</td><td></td></tr><tr><td>37eb666b7eb225ffdafc6f318639bea7f0ba9a24</td><td>MSU Technical Report (2014): MSU-CSE-14-5 <br/>Age, Gender and Race Estimation from <br/>Unconstrained Face Images -</td><td>('34393045', 'Hu Han', 'hu han')<br/>('40437942', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>375435fb0da220a65ac9e82275a880e1b9f0a557</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI +</td><td>('34393045', 'Hu Han', 'hu han')<br/>('40437942', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>377f2b65e6a9300448bdccf678cde59449ecd337</td><td>Pushing the Limits of Unconstrained Face Detection: +<br/>a Challenge Dataset and Baseline Results +<br/>1Fujitsu Laboratories Ltd., Kanagawa, Japan +<br/><b>Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b><br/><b>Rutgers University, 94 Brett Rd, Piscataway Township, NJ 08854, USA</b></td><td>('41018586', 'Hajime Nada', 'hajime nada')<br/>('2577847', 'Vishwanath A. Sindagi', 'vishwanath a. sindagi')<br/>('46197381', 'He Zhang', 'he zhang')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')</td><td>nada.hajime@jp.fujitsu.com, vishwanath.sindagi@gmail.com, he.zhang92@rutgers.edu, +<br/>vpatel36@jhu.edu +</td></tr><tr><td>375435fb0da220a65ac9e82275a880e1b9f0a557</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI <br/>From Pixels to Response Maps: Discriminative Image <br/>Filtering for Face Alignment in the Wild -</td><td>('3183108', 'Akshay Asthana', 'akshay asthana')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1902288', 'Shiyang Cheng', 'shiyang cheng')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>37b6d6577541ed991435eaf899a2f82fdd72c790</td><td>Vision-based Human Gender Recognition: A Survey +</td><td>('3183108', 'Akshay Asthana', 'akshay asthana')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1902288', 'Shiyang Cheng', 'shiyang cheng')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>370b6b83c7512419188f5373a962dd3175a56a9b</td><td>Face Alignment Refinement via Exploiting +<br/>Low-Rank property and Temporal Stability +<br/>Shuang LIU +<br/><b>Bournemouth University</b><br/><b>Bournemouth University</b><br/>Wenyu HU +<br/><b>Gannan Normal University</b><br/>Xiaosong YANG +<br/>Ruofeng TONG +<br/><b>Zhejiang University</b><br/>Jian J. ZHANG +<br/><b>Bournemouth University</b><br/><b>Bournemouth University</b><br/>face +<br/>and +<br/>alignment +</td><td>('48708691', 'Zhao Wang', 'zhao wang')</td><td>zwang@bournemouth.ac.uk +<br/>sliu@bournemouth.ac.uk +<br/>wenyu.huu@gmail.com +<br/>trf@zju.edu.cn +<br/>xyang@bournemouth.ac.uk +<br/>jzhang@bournemouth.ac.uk +</td></tr><tr><td>37b6d6577541ed991435eaf899a2f82fdd72c790</td><td>Vision-based Human Gender Recognition: A Survey <br/>Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia. </td><td>('32877936', 'Choon Boon Ng', 'choon boon ng')<br/>('9201065', 'Yong Haur Tay', 'yong haur tay')</td><td>{ngcb,tayyh,goibm}@utar.edu.my +</td></tr><tr><td>372a8bf0ef757c08551d41e40cb7a485527b6cd7</td><td>Unsupervised Video Hashing by Exploiting +<br/>Spatio-Temporal Feature +<br/><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong</b><br/><b>University, Shanghai, China</b></td><td>('46194894', 'Chao Ma', 'chao ma')<br/>('46964428', 'Yun Gu', 'yun gu')<br/>('46641573', 'Wei Liu', 'wei liu')<br/>('39264954', 'Jie Yang', 'jie yang')</td><td>{sjtu_machao,geron762,liuwei.1989,jieyang}@sjtu.edu.cn </td></tr><tr><td>37ef18d71c1ca71c0a33fc625ef439391926bfbb</td><td>Extraction of Subject-Specific Facial Expression <br/>Categories and Generation of Facial Expression <br/>Feature Space using Self-Mapping @@ -23646,7 +29434,17 @@ <br/>sagepub.co.uk/journalsPermissions.nav <br/>DOI: 10.1177/ToBeAssigned <br/>www.sagepub.com/ -</td><td>('3280554', 'Jawad Tayyub', 'jawad tayyub')<br/>('2762811', 'Majd Hawasly', 'majd hawasly')<br/>('1967104', 'David C. Hogg', 'david c. hogg')<br/>('1703235', 'Anthony G. Cohn', 'anthony g. cohn')</td><td></td></tr><tr><td>08a1fc55d03e4a73cad447e5c9ec79a6630f3e2d</td><td>BERG, BELHUMEUR: TOM-VS-PETE CLASSIFIERS AND IDENTITY-PRESERVING ALIGNMENT +</td><td>('3280554', 'Jawad Tayyub', 'jawad tayyub')<br/>('2762811', 'Majd Hawasly', 'majd hawasly')<br/>('1967104', 'David C. Hogg', 'david c. hogg')<br/>('1703235', 'Anthony G. Cohn', 'anthony g. cohn')</td><td></td></tr><tr><td>08f4832507259ded9700de81f5fd462caf0d5be8</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 118 – No.14, May 2015 +<br/>Geometric Approach for Human Emotion +<br/>Recognition using Facial Expression +<br/>S. S. Bavkar +<br/>Assistant Professor +<br/>J. S. Rangole +<br/>Assistant Professor +<br/>V. U. Deshmukh +<br/>Assistant Professor +</td><td></td><td></td></tr><tr><td>08a1fc55d03e4a73cad447e5c9ec79a6630f3e2d</td><td>BERG, BELHUMEUR: TOM-VS-PETE CLASSIFIERS AND IDENTITY-PRESERVING ALIGNMENT <br/>Tom-vs-Pete Classifiers and Identity-Preserving <br/>Alignment for Face Verification <br/><b>Columbia University</b><br/>New York, NY @@ -23665,7 +29463,8 @@ <br/>Images for Multimodal Pain Level <br/>Recognition <br/><b>Visual Analysis of People Lab, Aalborg University, Denmark</b><br/>Computer Vision Center, UAB, Barcelona, Spain -<br/><b>Aalborg University, Denmark</b></td><td>('37541412', 'Ramin Irani', 'ramin irani')<br/>('1803459', 'Kamal Nasrollahi', 'kamal nasrollahi')<br/>('3321700', 'Ciprian A. Corneanu', 'ciprian a. corneanu')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('40526933', 'Tanja L. Pedersen', 'tanja l. pedersen')<br/>('31627926', 'Maria-Louise Klitgaard', 'maria-louise klitgaard')<br/>('35675498', 'Laura Petrini', 'laura petrini')</td><td></td></tr><tr><td>08cb294a08365e36dd7ed4167b1fd04f847651a9</td><td>EXAMINING VISIBLE ARTICULATORY FEATURES IN CLEAR AND +<br/><b>Aalborg University, Denmark</b></td><td>('37541412', 'Ramin Irani', 'ramin irani')<br/>('1803459', 'Kamal Nasrollahi', 'kamal nasrollahi')<br/>('3321700', 'Ciprian A. Corneanu', 'ciprian a. corneanu')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('40526933', 'Tanja L. Pedersen', 'tanja l. pedersen')<br/>('31627926', 'Maria-Louise Klitgaard', 'maria-louise klitgaard')<br/>('35675498', 'Laura Petrini', 'laura petrini')</td><td></td></tr><tr><td>08903bf161a1e8dec29250a752ce9e2a508a711c</td><td>Joint Dimensionality Reduction and Metric Learning: A Geometric Take +</td><td>('2862871', 'Mathieu Salzmann', 'mathieu salzmann')</td><td></td></tr><tr><td>08cb294a08365e36dd7ed4167b1fd04f847651a9</td><td>EXAMINING VISIBLE ARTICULATORY FEATURES IN CLEAR AND <br/>CONVERSATIONAL SPEECH <br/><b>Medical Image Analysis Lab, School of Computing Science, Simon Fraser University, Canada</b><br/><b>Language and Brain Lab, Simon Fraser University, Canada</b><br/><b>KU Phonetics and Psycholinguistics Lab, University of Kansas</b></td><td>('2664514', 'Lisa Tang', 'lisa tang')<br/>('26839551', 'Beverly Hannah', 'beverly hannah')<br/>('3200950', 'Allard Jongman', 'allard jongman')<br/>('1723309', 'Yue Wang', 'yue wang')<br/>('3049056', 'Ghassan Hamarneh', 'ghassan hamarneh')</td><td> lisat@sfu.ca, beverlyw@sfu.ca, jongman@ku.edu, sereno@ku.edu, yuew@sfu.ca, hamarneh@sfu.ca </td></tr><tr><td>081286ede247c5789081502a700b378b6223f94b</td><td>ORIGINAL RESEARCH @@ -23761,13 +29560,35 @@ </td></tr><tr><td>081fb4e97d6bb357506d1b125153111b673cc128</td><td></td><td></td><td></td></tr><tr><td>08a98822739bb8e6b1388c266938e10eaa01d903</td><td>SensorSift: Balancing Sensor Data Privacy and Utility in <br/>Automated Face Understanding <br/><b>University of Washington</b><br/>**Microsoft Research, Redmond WA -</td><td>('3299424', 'Miro Enev', 'miro enev')<br/>('33481800', 'Jaeyeon Jung', 'jaeyeon jung')<br/>('1766509', 'Liefeng Bo', 'liefeng bo')<br/>('1728501', 'Xiaofeng Ren', 'xiaofeng ren')<br/>('1769675', 'Tadayoshi Kohno', 'tadayoshi kohno')</td><td></td></tr><tr><td>08f1e9e14775757298afd9039f46ec56e80677f9</td><td>Attentional Push: Augmenting Salience with +</td><td>('3299424', 'Miro Enev', 'miro enev')<br/>('33481800', 'Jaeyeon Jung', 'jaeyeon jung')<br/>('1766509', 'Liefeng Bo', 'liefeng bo')<br/>('1728501', 'Xiaofeng Ren', 'xiaofeng ren')<br/>('1769675', 'Tadayoshi Kohno', 'tadayoshi kohno')</td><td></td></tr><tr><td>084bebc5c98872e9307cd8e7f571d39ef9c1b81e</td><td>A Discriminative Feature Learning Approach +<br/>for Deep Face Recognition +<br/>1 Shenzhen Key Lab of Computer Vision and Pattern Recognition, +<br/><b>Shenzhen Institutes of Advanced Technology, CAS, Shenzhen, China</b><br/><b>The Chinese University of Hong Kong, Sha Tin, Hong Kong</b></td><td>('2512949', 'Yandong Wen', 'yandong wen')<br/>('3393556', 'Kaipeng Zhang', 'kaipeng zhang')<br/>('1911510', 'Zhifeng Li', 'zhifeng li')<br/>('33427555', 'Yu Qiao', 'yu qiao')</td><td>yandongw@andrew.cmu.edu, {kp.zhang,zhifeng.li,yu.qiao}@siat.ac.cn +</td></tr><tr><td>0857281a3b6a5faba1405e2c11f4e17191d3824d</td><td>Chude-Olisah et al. EURASIP Journal on Advances in Signal Processing 2014, 2014:102 +<br/>http://asp.eurasipjournals.com/content/2014/1/102 +<br/>R ES EAR CH +<br/>Face recognition via edge-based Gabor feature +<br/>representation for plastic surgery-altered images +<br/>Open Access +</td><td>('2529988', 'Ghazali Sulong', 'ghazali sulong')</td><td></td></tr><tr><td>08f1e9e14775757298afd9039f46ec56e80677f9</td><td>Attentional Push: Augmenting Salience with <br/>Shared Attention Modeling <br/>Centre for Intelligent Machines, Department of Electrical and Computer Engineering, <br/><b>McGill University</b><br/>Montreal, Quebec, Canada </td><td>('38111179', 'Siavash Gorji', 'siavash gorji')<br/>('1713608', 'James J. Clark', 'james j. clark')</td><td>siagorji@cim.mcgill.ca clark@cim.mcgill.ca -</td></tr><tr><td>08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7</td><td>Understanding Kin Relationships in a Photo -</td><td>('2025056', 'Ming Shao', 'ming shao')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td></td></tr><tr><td>082ad50ac59fc694ba4369d0f9b87430553b11db</td><td></td><td></td><td></td></tr><tr><td>6dd052df6b0e89d394192f7f2af4a3e3b8f89875</td><td>International Journal of Engineering and Advanced Technology (IJEAT) +</td></tr><tr><td>08d41d2f68a2bf0091dc373573ca379de9b16385</td><td>Recursive Chaining of Reversible Image-to-Image +<br/>Translators for Face Aging +<br/><b>Aalto University, Espoo, Finland</b><br/>1 GenMind Ltd, Finland +<br/>{ari.heljakka,arno.solin,juho.kannala}aalto.fi +</td><td>('2622083', 'Ari Heljakka', 'ari heljakka')<br/>('1768402', 'Arno Solin', 'arno solin')<br/>('1776374', 'Juho Kannala', 'juho kannala')</td><td></td></tr><tr><td>08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7</td><td>Understanding Kin Relationships in a Photo +</td><td>('2025056', 'Ming Shao', 'ming shao')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')<br/>('1708679', 'Yun Fu', 'yun fu')</td><td></td></tr><tr><td>082ad50ac59fc694ba4369d0f9b87430553b11db</td><td></td><td></td><td></td></tr><tr><td>6d0fe30444c6f4e4db3ad8b02fb2c87e2b33c58d</td><td>Robust Deep Appearance Models +<br/><b>Concordia University, Montreal, Quebec, Canada</b><br/>2 CyLab Biometrics Center and the Department of Electrical and Computer Engineering, +<br/><b>Carnegie Mellon University, Pittsburgh, PA, USA</b><br/>face images. In this approach, +</td><td>('2687827', 'Kha Gia Quach', 'kha gia quach')<br/>('1876581', 'Chi Nhan Duong', 'chi nhan duong')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('1699922', 'Tien D. Bui', 'tien d. bui')</td><td>Email: {k q, c duon, bui}@encs.concordia.ca +<br/>Email: kluu@andrew.cmu.edu +</td></tr><tr><td>6dbdb07ce2991db0f64c785ad31196dfd4dae721</td><td>Seeing Small Faces from Robust Anchor’s Perspective +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Avenue, Pittsburgh, PA 15213, USA +</td><td>('47894545', 'Chenchen Zhu', 'chenchen zhu')<br/>('1794486', 'Marios Savvides', 'marios savvides')<br/>('47599820', 'Ran Tao', 'ran tao')<br/>('1769788', 'Khoa Luu', 'khoa luu')</td><td>{chenchez, rant, kluu, marioss}@andrew.cmu.edu +</td></tr><tr><td>6dd052df6b0e89d394192f7f2af4a3e3b8f89875</td><td>International Journal of Engineering and Advanced Technology (IJEAT) <br/>ISSN: 2249 – 8958, Volume-2, Issue-4, April 2013 <br/>A literature survey on Facial Expression <br/>Recognition using Global Features @@ -23793,7 +29614,10 @@ <br/>and sent to Mechanical Turk for subjective feedback. The objective feedback is then combined with subjective feedback that is <br/>scored based on helpfulness, under which the sentiment is then classified. </td><td>('1825866', 'Michelle Fung', 'michelle fung')<br/>('2961433', 'Yina Jin', 'yina jin')<br/>('2171034', 'RuJie Zhao', 'rujie zhao')</td><td>{mfung, yjin18, rzhao2, mehoque}@cs.rochester.edu -</td></tr><tr><td>6de18708218988b0558f6c2f27050bb4659155e4</td><td></td><td></td><td></td></tr><tr><td>6d97e69bbba5d1f5c353f9a514d62aff63bc0fb1</td><td>Semi-Supervised Learning for Facial Expression +</td></tr><tr><td>6dddf1440617bf7acda40d4d75c7fb4bf9517dbb</td><td>JOURNAL OF LATEX CLASS FILES, VOL. XX, NO. X, MM YY +<br/>Beyond Counting: Comparisons of Density Maps for Crowd +<br/>Analysis Tasks - Counting, Detection, and Tracking +</td><td>('41201301', 'Di Kang', 'di kang')<br/>('1730232', 'Zheng Ma', 'zheng ma')<br/>('3651407', 'Antoni B. Chan', 'antoni b. chan')</td><td></td></tr><tr><td>6de18708218988b0558f6c2f27050bb4659155e4</td><td></td><td></td><td></td></tr><tr><td>6d97e69bbba5d1f5c353f9a514d62aff63bc0fb1</td><td>Semi-Supervised Learning for Facial Expression <br/>Recognition <br/>1HP Labs, Palo Alto, CA, USA <br/><b>Faculty of Science, University of Amsterdam, The Netherlands</b><br/>3Escola Polit´ecnica, Universidade de S˜ao Paulo, Brazil @@ -23801,7 +29625,12 @@ <br/>nicu@science.uva.nl <br/>fgcozman@usp.br <br/>huang@ifp.uiuc.edu -</td></tr><tr><td>6d91da37627c05150cb40cac323ca12a91965759</td><td></td><td></td><td></td></tr><tr><td>6dd2a0f9ca8a5fee12edec1485c0699770b4cfdf</td><td>Webly-supervised Video Recognition by Mutually +</td></tr><tr><td>6d91da37627c05150cb40cac323ca12a91965759</td><td></td><td></td><td></td></tr><tr><td>6d07e176c754ac42773690d4b4919a39df85d7ec</td><td>Face Attribute Prediction Using Off-The-Shelf Deep +<br/>Learning Networks +<br/>Computer Science and Communication +<br/><b>KTH Royal Institute of Technology</b><br/>100 44 Stockholm, Sweden +</td><td>('50262049', 'Yang Zhong', 'yang zhong')<br/>('1736906', 'Josephine Sullivan', 'josephine sullivan')<br/>('40565290', 'Haibo Li', 'haibo li')</td><td>{yzhong, sullivan, haiboli}@kth.se +</td></tr><tr><td>6dd2a0f9ca8a5fee12edec1485c0699770b4cfdf</td><td>Webly-supervised Video Recognition by Mutually <br/>Voting for Relevant Web Images and Web Video Frames <br/><b>IIIS, Tsinghua University</b><br/>2Google Research <br/>3Amazon @@ -23813,11 +29642,19 @@ <br/><b>G.H.Raisoni College of Engg. and Mgmt., Pune, India</b><br/><b>G.H.Raisoni College of Engg. and Mgmt., Pune, India</b><br/><b>G.H.Raisoni College of Engg. and Mgmt., Pune, India</b></td><td>('2671016', 'Snehal M. Gaikwad', 'snehal m. gaikwad')<br/>('40050646', 'Snehal S. Pathare', 'snehal s. pathare')</td><td>*gaikwad.snehal99@gmail.com <br/>*snehalpathare4@gmail.com <br/>*truptijachak311991@gmail.com +</td></tr><tr><td>6d8c9a1759e7204eacb4eeb06567ad0ef4229f93</td><td>Face Alignment Robust to Pose, Expressions and +<br/>Occlusions +</td><td>('2232940', 'Vishnu Naresh Boddeti', 'vishnu naresh boddeti')<br/>('1767616', 'Myung-Cheol Roh', 'myung-cheol roh')<br/>('2526145', 'Jongju Shin', 'jongju shin')<br/>('3149566', 'Takaharu Oguri', 'takaharu oguri')<br/>('1733113', 'Takeo Kanade', 'takeo kanade')</td><td></td></tr><tr><td>6dc1f94b852538d572e4919238ddb10e2ee449a4</td><td>Objects as context for detecting their semantic parts +<br/><b>University of Edinburgh</b></td><td>('20758701', 'Abel Gonzalez-Garcia', 'abel gonzalez-garcia')<br/>('1996209', 'Davide Modolo', 'davide modolo')<br/>('1749692', 'Vittorio Ferrari', 'vittorio ferrari')</td><td>a.gonzalez-garcia@sms.ed.ac.uk +<br/>davide.modolo@gmail.com +<br/>vferrari@staffmail.ed.ac.uk </td></tr><tr><td>6d4e3616d0b27957c4107ae877dc0dd4504b69ab</td><td>Shuffle and Learn: Unsupervised Learning using <br/>Temporal Order Verification <br/><b>The Robotics Institute, Carnegie Mellon University</b><br/>2 Facebook AI Research </td><td>('1806773', 'Ishan Misra', 'ishan misra')<br/>('1699161', 'C. Lawrence Zitnick', 'c. lawrence zitnick')<br/>('1709305', 'Martial Hebert', 'martial hebert')</td><td>{imisra, hebert}@cs.cmu.edu, zitnick@fb.com -</td></tr><tr><td>6d8e3f3a83514381f890ab7cd2a1f1c5be597b69</td><td><b>University of Massachusetts - Amherst</b><br/>Doctoral Dissertations 2014-current +</td></tr><tr><td>6d5125c9407c7762620eeea7570af1a8ee7d76f3</td><td>Video Frame Interpolation by Plug-and-Play +<br/>Deep Locally Linear Embedding +<br/><b>Yonsei University</b></td><td>('1886286', 'Anh-Duc Nguyen', 'anh-duc nguyen')<br/>('47902684', 'Woojae Kim', 'woojae kim')<br/>('2078790', 'Jongyoo Kim', 'jongyoo kim')<br/>('39200200', 'Sanghoon Lee', 'sanghoon lee')</td><td></td></tr><tr><td>6d8e3f3a83514381f890ab7cd2a1f1c5be597b69</td><td><b>University of Massachusetts - Amherst</b><br/>Doctoral Dissertations 2014-current <br/>Dissertations and Theses <br/>2014 <br/>Improving Text Recognition in Images of Natural @@ -24082,11 +29919,18 @@ <br/>SIMPLEX SUBSPACES <br/><b>Aristotle University of Thessaloniki</b><br/>Box 451, Thessaloniki 541 24, Greece </td><td>('1736143', 'Constantine Kotropoulos', 'constantine kotropoulos')<br/>('1762248', 'Vassiliki Moschou', 'vassiliki moschou')</td><td>E-mail: {costas, vmoshou}@aiia.csd.auth.gr -</td></tr><tr><td>017ce398e1eb9f2eed82d0b22fb1c21d3bcf9637</td><td>FACE RECOGNITION WITH HARMONIC DE-LIGHTING +</td></tr><tr><td>01c4cf9c7c08f0ad3f386d88725da564f3c54679</td><td>Interpretability Beyond Feature Attribution: +<br/>Quantitative Testing with Concept Activation Vectors (TCAV) +</td><td>('3351164', 'Been Kim', 'been kim')<br/>('2217654', 'Rory Sayres', 'rory sayres')</td><td></td></tr><tr><td>017ce398e1eb9f2eed82d0b22fb1c21d3bcf9637</td><td>FACE RECOGNITION WITH HARMONIC DE-LIGHTING <br/>2ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080 <br/>1Graduate School, CAS, Beijing, China, 100080 <br/>Emails: {lyqing, sgshan, wgao}jdl.ac.cn -</td><td>('2343895', 'Laiyun Qing', 'laiyun qing')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('40049005', 'Wen Gao', 'wen gao')</td><td></td></tr><tr><td>01125e3c68edb420b8d884ff53fb38d9fbe4f2b8</td><td>Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric +</td><td>('2343895', 'Laiyun Qing', 'laiyun qing')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('40049005', 'Wen Gao', 'wen gao')</td><td></td></tr><tr><td>014e3d0fa5248e6f4634dc237e2398160294edce</td><td>Int J Comput Vis manuscript No. +<br/>(will be inserted by the editor) +<br/>What does 2D geometric information really tell us about +<br/>3D face shape? +<br/>Received: date / Accepted: date +</td><td>('39180407', 'Anil Bas', 'anil bas')</td><td></td></tr><tr><td>01125e3c68edb420b8d884ff53fb38d9fbe4f2b8</td><td>Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric <br/>CNN Regression <br/><b>The University of Nottingham, UK</b><br/><b>Kingston University, UK</b><br/><b>Figure 1: A few results from our VRN - Guided method, on a full range of pose, including large expressions</b></td><td>('34596685', 'Aaron S. Jackson', 'aaron s. jackson')<br/>('3458121', 'Adrian Bulat', 'adrian bulat')<br/>('1689047', 'Vasileios Argyriou', 'vasileios argyriou')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td>1{aaron.jackson, adrian.bulat, yorgos.tzimiropoulos}@nottingham.ac.uk <br/>2 vasileios.argyriou@kingston.ac.uk @@ -24156,7 +30000,13 @@ <br/>{ryanlei, yanying}@cmlab.csie.ntu.edu.tw, </td></tr><tr><td>0697bd81844d54064d992d3229162fe8afcd82cb</td><td>User-driven mobile robot storyboarding: Learning image interest and <br/>saliency from pairwise image comparisons -</td><td>('1699287', 'Michael Burke', 'michael burke')</td><td></td></tr><tr><td>06f8aa1f436a33014e9883153b93581eea8c5c70</td><td>Leaving Some Stones Unturned: +</td><td>('1699287', 'Michael Burke', 'michael burke')</td><td></td></tr><tr><td>06262d6beeccf2784e4e36a995d5ee2ff73c8d11</td><td>Recognize Actions by Disentangling Components of Dynamics +<br/><b>CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong 2Amazon Rekognition</b></td><td>('47827548', 'Yue Zhao', 'yue zhao')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('1807606', 'Dahua Lin', 'dahua lin')</td><td>{zy317,dhlin}@ie.cuhk.edu.hk {yuanjx}@amazon.com +</td></tr><tr><td>06f585a3a05dd3371cd600a40dc35500e2f82f9b</td><td>Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning +<br/>Tasks via Graph Distillation for Video Classification +<br/><b>Institute of Computer Science and Technology, Peking University</b><br/>Beijing 100871, China +</td><td>('2439211', 'Chenrui Zhang', 'chenrui zhang')<br/>('1704081', 'Yuxin Peng', 'yuxin peng')</td><td>pengyuxin@pku.edu.cn +</td></tr><tr><td>06f8aa1f436a33014e9883153b93581eea8c5c70</td><td>Leaving Some Stones Unturned: <br/>Dynamic Feature Prioritization <br/>for Activity Detection in Streaming Video <br/><b>The University of Texas at Austin</b><br/>Current approaches for activity recognition often ignore con- @@ -24410,6 +30260,14 @@ <br/>(cid:6)(cid:11)(cid:1) </td><td></td><td>(cid:18)(cid:8)(cid:24)(cid:8)(cid:10)(cid:8)(cid:11)(cid:4)(cid:11)(cid:1) (cid:16)(cid:8)(cid:29)(cid:4)(cid:1) (cid:10)(cid:4)(cid:4)(cid:12)(cid:1) (cid:27)(cid:15)(cid:5)(cid:5)(cid:4)(cid:27)(cid:24)(cid:4)(cid:18)?(cid:1) (cid:11))(cid:27)(cid:16)(cid:1) (cid:8)(cid:11)(cid:1) (cid:9)!(cid:1) <+=(cid:14)(cid:1) (cid:23)(cid:9)(cid:13)7(cid:9)(cid:1) <@=(cid:14)(cid:1) <br/>(cid:27)(cid:15)(cid:20)(cid:20)(cid:4)(cid:11)((cid:15)(cid:12)(cid:18)(cid:6)(cid:12)-(cid:1) (cid:24)(cid:15)(cid:1) +(cid:2)+(cid:1) ((cid:4)(cid:15)((cid:5)(cid:4)9(cid:11)(cid:1) (cid:25)(cid:8)(cid:27)(cid:4)(cid:11)(cid:1) 4>0@(cid:1) (cid:17)(cid:4)(cid:12)(cid:14)(cid:1) (cid:2)/B(cid:1) .(cid:15)(cid:17)(cid:4)(cid:12)5(cid:21)(cid:1) +</td></tr><tr><td>06560d5721ecc487a4d70905a485e22c9542a522</td><td>SUN, YU: DEEP FACIAL ATTRIBUTE DETECTION IN THE WILD +<br/>Deep Facial Attribute Detection in the Wild: +<br/>From General to Specific +<br/>Department of Automation +<br/><b>University of Science and Technology</b><br/>of China +<br/>Hefei, China +</td><td>('4364455', 'Yuechuan Sun', 'yuechuan sun')<br/>('1720236', 'Jun Yu', 'jun yu')</td><td>ycsun@mail.ustc.edu.cn +<br/>harryjun@ustc.edu.cn </td></tr><tr><td>06526c52a999fdb0a9fd76e84f9795a69480cecf</td><td></td><td></td><td></td></tr><tr><td>06bad0cdda63e3fd054e7b334a5d8a46d8542817</td><td>Sharing Features Between Objects and Their Attributes <br/>1Department of Computer Science <br/><b>University of Texas at Austin</b><br/>2Computer Science Department @@ -24434,6 +30292,9 @@ <br/>Brno, Czech Republic </td><td>('1785162', 'Adam Herout', 'adam herout')</td><td>Graph@FIT, Brno University of Technology <br/>ijuranek,herout,idubska,zemcik@fit.vutbr.cz +</td></tr><tr><td>062c41dad67bb68fefd9ff0c5c4d296e796004dc</td><td>Temporal Generative Adversarial Nets with Singular Value Clipping +<br/>Preferred Networks inc., Japan +</td><td>('49160719', 'Masaki Saito', 'masaki saito')<br/>('8252749', 'Eiichi Matsumoto', 'eiichi matsumoto')<br/>('3083107', 'Shunta Saito', 'shunta saito')</td><td>{msaito, matsumoto, shunta}@preferred.jp </td></tr><tr><td>06400a24526dd9d131dfc1459fce5e5189b7baec</td><td>Event Recognition in Photo Collections with a Stopwatch HMM <br/>1Computer Vision Lab <br/>ETH Z¨urich, Switzerland @@ -24444,6 +30305,19 @@ </td></tr><tr><td>062d67af7677db086ef35186dc936b4511f155d7</td><td>They Are Not Equally Reliable: Semantic Event Search <br/>using Differentiated Concept Classifiers <br/><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney</b><br/><b>Carnegie Mellon University</b></td><td>('1729163', 'Xiaojun Chang', 'xiaojun chang')<br/>('1698559', 'Yi Yang', 'yi yang')<br/>('1752601', 'Eric P. Xing', 'eric p. xing')</td><td>cxj273@gmail.com, yaoliang@cs.cmu.edu, yi.yang@uts.edu.au, epxing@cs.cmu.edu +</td></tr><tr><td>06c2086f7f72536bf970ca629151b16927104df3</td><td>PALMERO ET AL.: MULTI-MODAL RECURRENT CNN FOR 3D GAZE ESTIMATION +<br/>Recurrent CNN for 3D Gaze Estimation +<br/>using Appearance and Shape Cues +<br/>1 Dept. Mathematics and Informatics +<br/>Universitat de Barcelona, Spain +<br/>2 Computer Vision Center +<br/>Campus UAB, Bellaterra, Spain +<br/>3 Dept. Electrical and Computer Eng. +<br/><b>University of Calgary, Canada</b><br/>4 Dept. Engineering +<br/><b>University of Larestan, Iran</b></td><td>('3413560', 'Cristina Palmero', 'cristina palmero')<br/>('38081877', 'Javier Selva', 'javier selva')<br/>('1921285', 'Mohammad Ali Bagheri', 'mohammad ali bagheri')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')</td><td>crpalmec7@alumnes.ub.edu +<br/>javier.selva.castello@est.fib.upc.edu +<br/>mohammadali.bagheri@ucalgary.ca +<br/>sergio@maia.ub.es </td></tr><tr><td>0694b05cbc3ef5d1c5069a4bfb932a5a7b4d5ff0</td><td>Iosifidis, A., Tefas, A., & Pitas, I. (2014). Exploiting Local Class Information <br/>in Extreme Learning Machine. Paper presented at International Joint <br/>Conference on Computational Intelligence (IJCCI), Rome, Italy. @@ -24582,14 +30456,40 @@ <br/><b>Systems and Telematics - Neurolab</b><br/>Via Opera Pia, 13 – I-16145 – Genoa - Italy </td><td>('2231336', 'José Hiroki Saito', 'josé hiroki saito')<br/>('3261775', 'Marcelo Hirakuri', 'marcelo hirakuri')<br/>('2558289', 'André Saunite', 'andré saunite')<br/>('36243877', 'Alessandro Noriaki Ide', 'alessandro noriaki ide')<br/>('40209065', 'Sandra Abib', 'sandra abib')</td><td>{saito,hirakuri,sabib}@dc.ufscar.br, tiagocarvalho@uol.com.br, saunite@fai.com.br <br/>noriaki@dist.unige.it +</td></tr><tr><td>6c66ae815e7e508e852ecb122fb796abbcda16a8</td><td>International Journal of Computer Science & Engineering Survey (IJCSES) Vol.6, No.5, October 2015 +<br/>A SURVEY OF THE TRENDS IN FACIAL AND +<br/>EXPRESSION RECOGNITION DATABASES AND +<br/>METHODS +<br/><b>University of Washington, Bothell, USA</b></td><td>('2971095', 'Sohini Roychowdhury', 'sohini roychowdhury')<br/>('33073434', 'Michelle Emmons', 'michelle emmons')</td><td></td></tr><tr><td>6ca2c5ff41e91c34696f84291a458d1312d15bf2</td><td>LIPNET: SENTENCE-LEVEL LIPREADING +<br/><b>University of Oxford, Oxford, UK</b><br/>Google DeepMind, London, UK 2 +<br/>CIFAR, Canada 3 +<br/>{yannis.assael,brendan.shillingford, +</td><td>('3365565', 'Yannis M. Assael', 'yannis m. assael')<br/>('3144580', 'Brendan Shillingford', 'brendan shillingford')<br/>('1766767', 'Shimon Whiteson', 'shimon whiteson')</td><td>shimon.whiteson,nando.de.freitas}@cs.ox.ac.uk </td></tr><tr><td>6cefb70f4668ee6c0bf0c18ea36fd49dd60e8365</td><td>Privacy-Preserving Deep Inference for Rich User <br/>Data on The Cloud <br/><b>Sharif University of Technology</b><br/><b>Queen Mary University of London</b><br/><b>Nokia Bell Labs and University of Oxford</b></td><td>('9920557', 'Ali Shahin Shamsabadi', 'ali shahin shamsabadi')<br/>('2251846', 'Ali Taheri', 'ali taheri')<br/>('2226725', 'Kleomenis Katevas', 'kleomenis katevas')<br/>('1688652', 'Hamid R. Rabiee', 'hamid r. rabiee')<br/>('2772904', 'Nicholas D. Lane', 'nicholas d. lane')<br/>('1763096', 'Hamed Haddadi', 'hamed haddadi')</td><td></td></tr><tr><td>6c690af9701f35cd3c2f6c8d160b8891ad85822a</td><td>Multi-Task Learning with Low Rank Attribute Embedding for Person <br/>Re-identification -<br/><b>Peking University</b><br/><b>University of Maryland College Park</b><br/><b>University of Texas at San Antonio</b></td><td>('20798990', 'Chi Su', 'chi su')<br/>('1752128', 'Fan Yang', 'fan yang')<br/>('1776581', 'Shiliang Zhang', 'shiliang zhang')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td></td></tr><tr><td>6ce23cf4f440021b7b05aa3c1c2700cc7560b557</td><td>Learning Local Convolutional Features for Face +<br/><b>Peking University</b><br/><b>University of Maryland College Park</b><br/><b>University of Texas at San Antonio</b></td><td>('20798990', 'Chi Su', 'chi su')<br/>('1752128', 'Fan Yang', 'fan yang')<br/>('1776581', 'Shiliang Zhang', 'shiliang zhang')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td></td></tr><tr><td>6c5fbf156ef9fc782be0089309074cc52617b868</td><td>Controllable Video Generation with Sparse Trajectories +<br/><b>Cornell University</b></td><td>('19235216', 'Zekun Hao', 'zekun hao')<br/>('47932904', 'Xun Huang', 'xun huang')<br/>('50172592', 'Serge Belongie', 'serge belongie')</td><td>{hz472,xh258,sjb344}@cornell.edu +</td></tr><tr><td>6c304f3b9c3a711a0cca5c62ce221fb098dccff0</td><td>Attentive Semantic Video Generation using Captions +<br/>IIT Hyderabad +<br/>IIT Hyderabad +</td><td>('8268761', 'Tanya Marwah', 'tanya marwah')<br/>('47351893', 'Gaurav Mittal', 'gaurav mittal')<br/>('1699429', 'Vineeth N. Balasubramanian', 'vineeth n. balasubramanian')</td><td>ee13b1044@iith.ac.in +<br/>gaurav.mittal.191013@gmail.com +<br/>vineethnb@iith.ac.in +</td></tr><tr><td>6ce23cf4f440021b7b05aa3c1c2700cc7560b557</td><td>Learning Local Convolutional Features for Face <br/>Recognition with 2D-Warping <br/>Human Language Technology and Pattern Recognition Group, <br/><b>RWTH Aachen University</b></td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('1685956', 'Hermann Ney', 'hermann ney')</td><td>surname@cs.rwth-aachen.de +</td></tr><tr><td>6c80c834d426f0bc4acd6355b1946b71b50cbc0b</td><td>Pose-Based Two-Stream Relational Networks for +<br/>Action Recognition in Videos +<br/>1Center for Research on Intelligent Perception and Computing (CRIPAC), +<br/>National Laboratory of Pattern Recognition (NLPR) +<br/>2Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), +<br/><b>Institute of Automation, Chinese Academy of Sciences (CASIA</b><br/><b>University of Chinese Academy of Sciences (UCAS</b></td><td>('47824598', 'Wei Wang', 'wei wang')<br/>('47539600', 'Jinjin Zhang', 'jinjin zhang')<br/>('39927579', 'Chenyang Si', 'chenyang si')<br/>('1693997', 'Liang Wang', 'liang wang')</td><td>{wangwei, wangliang}@nlpr.ia.ac.cn, {jinjin.zhang, +<br/>chenyang.si}@cripac.ia.ac.cn +</td></tr><tr><td>6cb7648465ba7757ecc9c222ac1ab6402933d983</td><td>Visual Forecasting by Imitating Dynamics in Natural Sequences +<br/><b>Stanford University National Tsing Hua University</b></td><td>('32970572', 'Kuo-Hao Zeng', 'kuo-hao zeng')</td><td>{khzeng, bshen88, dahuang, jniebles}@cs.stanford.edu sunmin@ee.nthu.edu.tw </td></tr><tr><td>6c2b392b32b2fd0fe364b20c496fcf869eac0a98</td><td>DOI 10.1007/s00138-012-0423-7 <br/>ORIGINAL PAPER <br/>Fully automatic face recognition framework based @@ -24616,7 +30516,26 @@ <br/>vpradeep@microsoft.com </td></tr><tr><td>6cddc7e24c0581c50adef92d01bb3c73d8b80b41</td><td>Face Verification Using the LARK <br/>Representation -</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>6cd96f2b63c6b6f33f15c0ea366e6003f512a951</td><td>A New Approach in Solving Illumination and Facial Expression Problems +</td><td>('3326805', 'Hae Jong Seo', 'hae jong seo')<br/>('1718280', 'Peyman Milanfar', 'peyman milanfar')</td><td></td></tr><tr><td>6cfc337069868568148f65732c52cbcef963f79d</td><td>Audio-Visual Speaker Localization via Weighted +<br/>Clustering +<br/>To cite this version: +<br/>Localization via Weighted Clustering. IEEE Workshop on Machine Learning for Signal Processing, +<br/>Sep 2014, Reims, France. pp.1-6, 2014, <10.1109/MLSP.2014.6958874>. <hal-01053732> +<br/>HAL Id: hal-01053732 +<br/>https://hal.archives-ouvertes.fr/hal-01053732 +<br/>Submitted on 11 Aug 2014 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('1780201', 'Xavier Alameda-Pineda', 'xavier alameda-pineda')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('1785817', 'Florence Forbes', 'florence forbes')<br/>('1780201', 'Xavier Alameda-Pineda', 'xavier alameda-pineda')<br/>('1794229', 'Radu Horaud', 'radu horaud')<br/>('1785817', 'Florence Forbes', 'florence forbes')</td><td></td></tr><tr><td>6cd96f2b63c6b6f33f15c0ea366e6003f512a951</td><td>A New Approach in Solving Illumination and Facial Expression Problems <br/>for Face Recognition <br/><b>a The University of Nottingham Malaysia Campus</b><br/>Tel : 03-89248358, Fax : 03-89248017 <br/>Jalan Broga @@ -24637,7 +30556,10 @@ <br/>Fu-lai Chung (cskchung@comp.polyu.edu.hk) </td></tr><tr><td>390f3d7cdf1ce127ecca65afa2e24c563e9db93b</td><td>Learning Deep Representation for Face <br/>Alignment with Auxiliary Attributes -</td><td>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('1693209', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>3918b425bb9259ddff9eca33e5d47bde46bd40aa</td><td>Copyright +</td><td>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('1693209', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>39ed31ced75e6151dde41944a47b4bdf324f922b</td><td>Pose-Guided Photorealistic Face Rotation +<br/><b>CRIPAC and NLPR and CEBSIT, CASIA 2University of Chinese Academy of Sciences</b><br/>3Noah’s Ark Laboratory, Huawei Technologies Co., Ltd. +</td><td>('49995036', 'Yibo Hu', 'yibo hu')<br/>('47150161', 'Xiang Wu', 'xiang wu')<br/>('46806278', 'Bing Yu', 'bing yu')<br/>('50361927', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>{yibo.hu, xiang.wu}@cripac.ia.ac.cn, yubing5@huawei.com, {rhe, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>3918b425bb9259ddff9eca33e5d47bde46bd40aa</td><td>Copyright <br/>by <br/>David Lieh-Chiang Chen <br/>2012 @@ -24667,7 +30589,8 @@ </td><td>('1898210', 'Golnaz Ghiasi', 'golnaz ghiasi')<br/>('3157443', 'Charless C. Fowlkes', 'charless c. fowlkes')</td><td>gghiasi@ics.uci.edu <br/>fowlkes@ics.uci.edu </td></tr><tr><td>39c48309b930396a5a8903fdfe781d3e40d415d0</td><td>Learning Spatial and Temporal Cues for Multi-label Facial Action Unit Detection -<br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh PA</b><br/><b>University of Pittsburgh, Pittsburgh PA</b></td><td>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>3986161c20c08fb4b9b791b57198b012519ea58b</td><td>International Journal of Soft Computing and Engineering (IJSCE) +<br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh PA</b><br/><b>University of Pittsburgh, Pittsburgh PA</b></td><td>('39336289', 'Wen-Sheng Chu', 'wen-sheng chu')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>39c8b34c1b678235b60b648d0b11d241a34c8e32</td><td>Learning to Deblur Images with Exemplars +</td><td>('9416825', 'Jinshan Pan', 'jinshan pan')<br/>('2776845', 'Wenqi Ren', 'wenqi ren')<br/>('1786024', 'Zhe Hu', 'zhe hu')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>3986161c20c08fb4b9b791b57198b012519ea58b</td><td>International Journal of Soft Computing and Engineering (IJSCE) <br/>ISSN: 2231-2307, Volume-4 Issue-4, September 2014 <br/>An Efficient Method for Face Recognition based on <br/>Fusion of Global and Local Feature Extraction @@ -24695,13 +30618,17 @@ <br/><b>Sabanci University</b><br/>Faculty of <br/>Engineering and Natural Sciences <br/>Orhanli, Istanbul -</td><td>('40322754', 'Esra Vural', 'esra vural')<br/>('21691177', 'Mujdat Cetin', 'mujdat cetin')<br/>('31849282', 'Aytul Ercil', 'aytul ercil')<br/>('2724380', 'Gwen Littlewort', 'gwen littlewort')<br/>('1858421', 'Marian Bartlett', 'marian bartlett')<br/>('29794862', 'Javier Movellan', 'javier movellan')</td><td></td></tr><tr><td>39f03d1dfd94e6f06c1565d7d1bb14ab0eee03bc</td><td>Simultaneous Local Binary Feature Learning and Encoding for Face Recognition +</td><td>('40322754', 'Esra Vural', 'esra vural')<br/>('21691177', 'Mujdat Cetin', 'mujdat cetin')<br/>('31849282', 'Aytul Ercil', 'aytul ercil')<br/>('2724380', 'Gwen Littlewort', 'gwen littlewort')<br/>('1858421', 'Marian Bartlett', 'marian bartlett')<br/>('29794862', 'Javier Movellan', 'javier movellan')</td><td></td></tr><tr><td>3947b64dcac5bcc1d3c8e9dcb50558efbb8770f1</td><td></td><td></td><td></td></tr><tr><td>3965d61c4f3b72044f43609c808f8760af8781a2</td><td></td><td></td><td></td></tr><tr><td>39f03d1dfd94e6f06c1565d7d1bb14ab0eee03bc</td><td>Simultaneous Local Binary Feature Learning and Encoding for Face Recognition <br/><b>Tsinghua University, Beijing, China</b><br/>2Rapid-Rich Object Search (ROSE) Lab, Interdisciplinary Graduate School, <br/><b>Nanyang Technological University, Singapore</b></td><td>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('1754854', 'Venice Erin Liong', 'venice erin liong')<br/>('39491387', 'Jie Zhou', 'jie zhou')</td><td>elujiwen@gmail.com; veniceer001@e.ntu.edu.sg; jzhou@tsinghua.edu.cn -</td></tr><tr><td>3983637022992a329f1d721bed246ae76bc934f7</td><td>Wide-Baseline Stereo for Face Recognition with Large Pose Variation +</td></tr><tr><td>395bf182983e0917f33b9701e385290b64e22f9a</td><td></td><td></td><td></td></tr><tr><td>3983637022992a329f1d721bed246ae76bc934f7</td><td>Wide-Baseline Stereo for Face Recognition with Large Pose Variation <br/>Computer Science Department <br/><b>University of Maryland, College Park</b></td><td>('38171682', 'Carlos D. Castillo', 'carlos d. castillo')<br/>('34734622', 'David W. Jacobs', 'david w. jacobs')</td><td>{carlos,djacobs}@cs.umd.edu -</td></tr><tr><td>3958db5769c927cfc2a9e4d1ee33ecfba86fe054</td><td>Describable Visual Attributes for +</td></tr><tr><td>3933e323653ff27e68c3458d245b47e3e37f52fd</td><td>Evaluation of a 3D-aided Pose Invariant 2D Face Recognition System +<br/>Computational Biomedicine Lab +<br/>4800 Calhoun Rd. Houston, TX, USA +</td><td>('26401746', 'Ha A. Le', 'ha a. le')<br/>('39634395', 'Pengfei Dou', 'pengfei dou')<br/>('2461369', 'Yuhang Wu', 'yuhang wu')<br/>('1706204', 'Ioannis A. Kakadiaris', 'ioannis a. kakadiaris')</td><td>{xxu18, hale4, pdou, ywu35, ikakadia}@central.uh.edu +</td></tr><tr><td>39b452453bea9ce398613d8dd627984fd3a0d53c</td><td></td><td></td><td></td></tr><tr><td>3958db5769c927cfc2a9e4d1ee33ecfba86fe054</td><td>Describable Visual Attributes for <br/>Face Verification and Image Search </td><td>('40631426', 'Neeraj Kumar', 'neeraj kumar')<br/>('39668247', 'Alexander C. Berg', 'alexander c. berg')<br/>('1767767', 'Peter N. Belhumeur', 'peter n. belhumeur')<br/>('1750470', 'Shree K. Nayar', 'shree k. nayar')</td><td></td></tr><tr><td>39ecdbad173e45964ffe589b9ced9f1ebfe2d44e</td><td>Automatic Recognition of Lower Facial Action Units <br/>Joint Research Group on Audio Visual Signal Processing (AVSP), @@ -24716,7 +30643,22 @@ <br/>with Convolutional Neural Networks <br/><b>National Research University Higher School of Economics, Nizhny Novgorod, Russian</b><br/>Federation </td><td>('26376584', 'Anastasiia D. Sokolova', 'anastasiia d. sokolova')<br/>('26427828', 'Angelina S. Kharchevnikova', 'angelina s. kharchevnikova')<br/>('35153729', 'Andrey V. Savchenko', 'andrey v. savchenko')</td><td>adsokolova96@mail.ru -</td></tr><tr><td>9949ac42f39aeb7534b3478a21a31bc37fe2ffe3</td><td>Parametric Stereo for Multi-Pose Face Recognition and +</td></tr><tr><td>994f7c469219ccce59c89badf93c0661aae34264</td><td>1 +<br/>Model Based Face Recognition Across Facial +<br/>Expressions +<br/> +<br/>screens, embedded into mobiles and installed into everyday +<br/>living and working environments they become valuable tools +<br/>for human system interaction. A particular important aspect of +<br/>this interaction is detection and recognition of faces and +<br/>interpretation of facial expressions. These capabilities are +<br/>deeply rooted in the human visual system and a crucial +<br/>building block for social interaction. Consequently, these +<br/>capabilities are an important step towards the acceptance of +<br/>many technical systems. +<br/>trees as a classifier +<br/>lies not only +</td><td>('1725709', 'Zahid Riaz', 'zahid riaz')<br/>('50565622', 'Christoph Mayer', 'christoph mayer')<br/>('32131501', 'Matthias Wimmer', 'matthias wimmer')<br/>('1699132', 'Bernd Radig', 'bernd radig')<br/>('31311898', 'Senior Member', 'senior member')</td><td></td></tr><tr><td>9949ac42f39aeb7534b3478a21a31bc37fe2ffe3</td><td>Parametric Stereo for Multi-Pose Face Recognition and <br/>3D-Face Modeling <br/>PSI ESAT-KUL <br/>Leuven, Belgium @@ -24742,7 +30684,10 @@ <br/>BURLA, ODISHA, INDIA </td><td></td><td>alpesh.d123@gmail.com <br/>nilamanib@gmail.com -</td></tr><tr><td>9931c6b050e723f5b2a189dd38c81322ac0511de</td><td></td><td></td><td></td></tr><tr><td>994b52bf884c71a28b4f5be4eda6baaacad1beee</td><td>Categorizing Big Video Data on the Web: +</td></tr><tr><td>993d189548e8702b1cb0b02603ef02656802c92b</td><td>Highly-Economized Multi-View Binary +<br/>Compression for Scalable Image Clustering +<br/><b>Harbin Institute of Technology (Shenzhen), China</b><br/><b>The University of Queensland, Australia</b><br/><b>Inception Institute of Arti cial Intelligence, UAE</b><br/>4 Computer Vision Laboratory, ETH Zurich, Switzerland +<br/><b>University of Electronic Science and Technology of China, China</b></td><td>('38448016', 'Zheng Zhang', 'zheng zhang')<br/>('40241836', 'Li Liu', 'li liu')<br/>('1747229', 'Jie Qin', 'jie qin')<br/>('39986542', 'Fan Zhu', 'fan zhu')<br/>('2731972', 'Fumin Shen', 'fumin shen')<br/>('1725160', 'Yong Xu', 'yong xu')<br/>('40799321', 'Ling Shao', 'ling shao')<br/>('1724393', 'Heng Tao Shen', 'heng tao shen')</td><td></td></tr><tr><td>9931c6b050e723f5b2a189dd38c81322ac0511de</td><td></td><td></td><td></td></tr><tr><td>994b52bf884c71a28b4f5be4eda6baaacad1beee</td><td>Categorizing Big Video Data on the Web: <br/>Challenges and Opportunities <br/>School of Computer Science <br/><b>Fudan University</b><br/>Shanghai, China @@ -24757,7 +30702,10 @@ <br/>A Simple, Fast and Highly-Accurate Algorithm to <br/>Recover 3D Shape from 2D Landmarks on a Single <br/>Image -</td><td>('39071836', 'Ruiqi Zhao', 'ruiqi zhao')<br/>('1678691', 'Yan Wang', 'yan wang')</td><td></td></tr><tr><td>992ebd81eb448d1eef846bfc416fc929beb7d28b</td><td>Exemplar-Based Face Parsing +</td><td>('39071836', 'Ruiqi Zhao', 'ruiqi zhao')<br/>('1678691', 'Yan Wang', 'yan wang')</td><td></td></tr><tr><td>9901f473aeea177a55e58bac8fd4f1b086e575a4</td><td>Human and Sheep Facial Landmarks Localisation +<br/>by Triplet Interpolated Features +<br/><b>University of Cambridge</b></td><td>('2966679', 'Heng Yang', 'heng yang')<br/>('2271111', 'Renqiao Zhang', 'renqiao zhang')<br/>('39626495', 'Peter Robinson', 'peter robinson')</td><td>hy306, rz264, pr10@cam.ac.uk +</td></tr><tr><td>992ebd81eb448d1eef846bfc416fc929beb7d28b</td><td>Exemplar-Based Face Parsing <br/>Supplementary Material <br/><b>University of Wisconsin Madison</b><br/>Adobe Research <br/>http://www.cs.wisc.edu/~lizhang/projects/face-parsing/ @@ -24780,7 +30728,21 @@ <br/>References <br/>[1] V. Le, J. Brandt, Z. Lin, L. Bourdev, and T. S. Huang. Interactive facial feature localization. In ECCV, 2012. <br/>[2] C. Liu, J. Yuen, and A. Torralba. Nonparametric scene parsing via label transfer. In PAMI, December 2011. -</td><td>('2721523', 'Brandon M. Smith', 'brandon m. smith')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')</td><td></td></tr><tr><td>9990e0b05f34b586ffccdc89de2f8b0e5d427067</td><td>International Journal of Modeling and Optimization, Vol. 3, No. 2, April 2013 +</td><td>('2721523', 'Brandon M. Smith', 'brandon m. smith')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')</td><td></td></tr><tr><td>99c20eb5433ed27e70881d026d1dbe378a12b342</td><td>ISCA Archive +<br/>http://www.isca-speech.org/archive +<br/>First Workshop on Speech, Language +<br/>and Audio in Multimedia +<br/>Marseille, France +<br/>August 22-23, 2013 +<br/>Proceedings of the First Workshop on Speech, Language and Audio in Multimedia (SLAM), Marseille, France, August 22-23, 2013. +<br/>78 +</td><td></td><td></td></tr><tr><td>99facca6fc50cc30f13b7b6dd49ace24bc94f702</td><td>Front.Comput.Sci. +<br/>DOI +<br/>RESEARCH ARTICLE +<br/>VIPLFaceNet: An Open Source Deep Face Recognition SDK +<br/>1 Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), +<br/><b>Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b><br/>c(cid:13) Higher Education Press and Springer-Verlag Berlin Heidelberg 2016 +</td><td>('46522348', 'Xin Liu', 'xin liu')<br/>('1693589', 'Meina Kan', 'meina kan')<br/>('3468240', 'Wanglong Wu', 'wanglong wu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td></td></tr><tr><td>9990e0b05f34b586ffccdc89de2f8b0e5d427067</td><td>International Journal of Modeling and Optimization, Vol. 3, No. 2, April 2013 <br/>Auto-Optimized Multimodal Expression Recognition <br/>Framework Using 3D Kinect Data for ASD Therapeutic <br/>Aid @@ -24790,7 +30752,10 @@ <br/>and <br/>to <br/>recognize -</td><td>('25833279', 'Amira E. Youssef', 'amira e. youssef')<br/>('1720250', 'Ahmed S. Ibrahim', 'ahmed s. ibrahim')<br/>('1731164', 'A. Lynn Abbott', 'a. lynn abbott')</td><td></td></tr><tr><td>52012b4ecb78f6b4b9ea496be98bcfe0944353cd</td><td> +</td><td>('25833279', 'Amira E. Youssef', 'amira e. youssef')<br/>('1720250', 'Ahmed S. Ibrahim', 'ahmed s. ibrahim')<br/>('1731164', 'A. Lynn Abbott', 'a. lynn abbott')</td><td></td></tr><tr><td>99d7678039ad96ee29ab520ff114bb8021222a91</td><td>Political image analysis with deep neural +<br/>networks +<br/>November 28, 2017 +</td><td>('41096358', 'L. Jason Anastasopoulos', 'l. jason anastasopoulos')<br/>('2361255', 'Shiry Ginosar', 'shiry ginosar')<br/>('2007721', 'Dhruvil Badani', 'dhruvil badani')<br/>('2459453', 'Jake Ryland Williams', 'jake ryland williams')<br/>('50521070', 'Crystal Lee', 'crystal lee')</td><td></td></tr><tr><td>52012b4ecb78f6b4b9ea496be98bcfe0944353cd</td><td> <br/> JOURNAL OF COMPUTATION IN BIOSCIENCES AND ENGINEERING <br/> <br/> Journal homepage: http://scienceq.org/Journals/JCLS.php @@ -24802,6 +30767,14 @@ <br/><b>Federal University Technology Akure, PMB 704, Akure, Nigeria</b><br/>2. Department of computer science, Kwara state polytechnic Ilorin, Kwara-State, Nigeria. <br/> Received: September 22, 2015, Accepted: December 14, 2015, Published: December 14, 2015. </td><td>('10698338', 'Alese Boniface Kayode', 'alese boniface kayode')</td><td>. *Corresponding author: Ayeni Olaniyi Abiodun Mail Id: oaayeni@futa.edu.ng +</td></tr><tr><td>523854a7d8755e944bd50217c14481fe1329a969</td><td>A Differentially Private Kernel Two-Sample Test +<br/>MPI-IS +<br/><b>University Of Oxford</b><br/><b>University Of Oxford</b><br/>MPI-IS +<br/>April 17, 2018 +</td><td>('39565862', 'Anant Raj', 'anant raj')<br/>('35142231', 'Ho Chung Leon Law', 'ho chung leon law')<br/>('1698032', 'Dino Sejdinovic', 'dino sejdinovic')<br/>('37292171', 'Mijung Park', 'mijung park')</td><td>anant.raj@tuebingen.mpg.de +<br/>ho.law@stats.ox.ac.uk +<br/>dino.sejdinovic@stats.ox.ac.uk +<br/>mijung.park@tuebingen.mpg.de </td></tr><tr><td>521cfbc1949289a7ffc3ff90af7c55adeb43db2a</td><td>Action Recognition with Coarse-to-Fine Deep Feature Integration and <br/>Asynchronous Fusion <br/><b>Shanghai Jiao Tong University, China</b><br/><b>National Key Laboratory for Novel Software Technology, Nanjing University, China</b><br/><b>University of Chinese Academy of Sciences, China</b></td><td>('8131625', 'Weiyao Lin', 'weiyao lin')<br/>('1926641', 'Yang Mi', 'yang mi')<br/>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('1875882', 'Ke Lu', 'ke lu')<br/>('37028145', 'Hongkai Xiong', 'hongkai xiong')</td><td>{wylin, deyangmiyang, xionghongkai}@sjtu.edu.cn, wujx2001@nju.edu.cn, luk@ucas.ac.cn @@ -24862,6 +30835,10 @@ <br/>Department of Electronic and Computer Engineering <br/><b>The Hong Kong University of Science and Technology</b><br/>HKSAR, China </td><td>('1698743', 'Yuqian Zhou', 'yuqian zhou')</td><td>yzhouas@ust.hk, eebert@ust.hk +</td></tr><tr><td>52472ec859131844f38fc7d57944778f01d109ac</td><td>Improving speaker turn embedding by +<br/>crossmodal transfer learning from face embedding +<br/><b>Idiap Research Institute, Martigny, Switzerland</b><br/>2 ´Ecole Polytechnique F´ed´eral de Lausanne, Switzerland +</td><td>('39560344', 'Nam Le', 'nam le')<br/>('1719610', 'Jean-Marc Odobez', 'jean-marc odobez')</td><td>{nle, odobez}@idiap.ch </td></tr><tr><td>5287d8fef49b80b8d500583c07e935c7f9798933</td><td>Generative Adversarial Text to Image Synthesis <br/><b>University of Michigan, Ann Arbor, MI, USA (UMICH.EDU</b><br/><b>Max Planck Institute for Informatics, Saarbr ucken, Germany (MPI-INF.MPG.DE</b><br/>REEDSCOT1, AKATA2, XCYAN1, LLAJAN1 <br/>HONGLAK1, SCHIELE2 @@ -24903,14 +30880,44 @@ <br/>April 2, 2008 <br/>DRAFT </td><td>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td>email: pitas@zeus.csd.auth.gr -</td></tr><tr><td>52f23e1a386c87b0dab8bfdf9694c781cd0a3984</td><td></td><td></td><td></td></tr><tr><td>528069963f0bd0861f380f53270c96c269a3ea1c</td><td><b>Cardi University</b><br/>School of Computer Science and Informatics +</td></tr><tr><td>52f23e1a386c87b0dab8bfdf9694c781cd0a3984</td><td></td><td></td><td></td></tr><tr><td>52d7eb0fbc3522434c13cc247549f74bb9609c5d</td><td>WIDER FACE: A Face Detection Benchmark +<br/><b>The Chinese University of Hong Kong</b></td><td>('1692609', 'Shuo Yang', 'shuo yang')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{ys014, pluo, ccloy, xtang}@ie.cuhk,edu.hk +</td></tr><tr><td>528069963f0bd0861f380f53270c96c269a3ea1c</td><td><b>Cardi University</b><br/>School of Computer Science and Informatics <br/>Visual Computing Group <br/>4D (3D Dynamic) Statistical Models of <br/>Conversational Expressions and the <br/>Synthesis of Highly-Realistic 4D Facial <br/>Expression Sequences <br/>Submitted in part fulfilment of the requirements for the degree of -<br/><b>Doctor of Philosophy in Computer Science at Cardi University, July 24th</b></td><td>('1812779', 'Jason Vandeventer', 'jason vandeventer')</td><td></td></tr><tr><td>5239001571bc64de3e61be0be8985860f08d7e7e</td><td>SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, JUNE 2016 +<br/><b>Doctor of Philosophy in Computer Science at Cardi University, July 24th</b></td><td>('1812779', 'Jason Vandeventer', 'jason vandeventer')</td><td></td></tr><tr><td>529baf1a79cca813f8c9966ceaa9b3e42748c058</td><td>Triangle Wise Mapping Technique to Transform one Face Image into Another Face Image +<br/> +<br/>{tag} {/tag} +<br/> +<br/> International Journal of Computer Applications +<br/> +<br/> © 2014 by IJCA Journal +<br/> Volume 87 - Number 6 +<br/> +<br/> Year of Publication: 2014 +<br/> +<br/> +<br/> +<br/> Authors: +<br/> +<br/>Bhogeswar Borah +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> 10.5120/15209-3714 +<br/> {bibtex}pxc3893714.bib{/bibtex} +</td><td></td><td></td></tr><tr><td>5239001571bc64de3e61be0be8985860f08d7e7e</td><td>SUBMITTED TO IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, JUNE 2016 <br/>Deep Appearance Models: A Deep Boltzmann <br/>Machine Approach for Face Modeling </td><td>('1876581', 'Chi Nhan Duong', 'chi nhan duong')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('2687827', 'Kha Gia Quach', 'kha gia quach')<br/>('1699922', 'Tien D. Bui', 'tien d. bui')</td><td></td></tr><tr><td>556b9aaf1bc15c928718bc46322d70c691111158</td><td>Exploiting Qualitative Domain Knowledge for Learning Bayesian @@ -24918,11 +30925,15 @@ <br/>Thomson-Reuters Corporation <br/><b>Rensselaer Polytechnic Institute</b></td><td>('2460793', 'Wenhui Liao', 'wenhui liao')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>wenhui.liao@thomsonreuters.com <br/>qji@ecse.rpi.edu -</td></tr><tr><td>550858b7f5efaca2ebed8f3969cb89017bdb739f</td><td></td><td></td><td></td></tr><tr><td>554b9478fd285f2317214396e0ccd81309963efd</td><td>Spatio-Temporal Action Localization For Human Action +</td></tr><tr><td>55ea0c775b25d9d04b5886e322db852e86a556cd</td><td>DOCK: Detecting Objects +<br/>by transferring Common-sense Knowledge +<br/><b>University of California, Davis 2University of Washington 3Allen Institute for AI</b><br/>https://dock-project.github.io +</td><td>('2270286', 'Ali Farhadi', 'ali farhadi')<br/>('19553871', 'Krishna Kumar Singh', 'krishna kumar singh')<br/>('1883898', 'Yong Jae Lee', 'yong jae lee')</td><td></td></tr><tr><td>550858b7f5efaca2ebed8f3969cb89017bdb739f</td><td></td><td></td><td></td></tr><tr><td>554b9478fd285f2317214396e0ccd81309963efd</td><td>Spatio-Temporal Action Localization For Human Action <br/>Recognition in Large Dataset <br/>1L2TI, Institut Galil´ee, Universit´e Paris 13, France; <br/>2SERCOM, Ecole Polytechnique de Tunisie -</td><td>('3240115', 'Sameh MEGRHI', 'sameh megrhi')<br/>('2504338', 'Marwa JMAL', 'marwa jmal')<br/>('1731553', 'Azeddine BEGHDADI', 'azeddine beghdadi')<br/>('14521102', 'Wided Mseddi', 'wided mseddi')</td><td></td></tr><tr><td>558fc9a2bce3d3993a9c1f41b6c7f290cefcf92f</td><td>DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE +</td><td>('3240115', 'Sameh MEGRHI', 'sameh megrhi')<br/>('2504338', 'Marwa JMAL', 'marwa jmal')<br/>('1731553', 'Azeddine BEGHDADI', 'azeddine beghdadi')<br/>('14521102', 'Wided Mseddi', 'wided mseddi')</td><td></td></tr><tr><td>55c68c1237166679d2cb65f266f496d1ecd4bec6</td><td>Learning to Score Figure Skating Sport Videos +</td><td>('2708397', 'Chengming Xu', 'chengming xu')<br/>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('10110775', 'Zitian Chen', 'zitian chen')<br/>('40379722', 'Bing Zhang', 'bing zhang')<br/>('1717861', 'Yu-Gang Jiang', 'yu-gang jiang')<br/>('1713721', 'Xiangyang Xue', 'xiangyang xue')</td><td></td></tr><tr><td>558fc9a2bce3d3993a9c1f41b6c7f290cefcf92f</td><td>DEPARTMENT OF INFORMATION ENGINEERING AND COMPUTER SCIENCE <br/>ICT International Doctoral School <br/>Efficient and Effective Solutions <br/>for Video Classification @@ -24961,7 +30972,12 @@ <br/><b>Massachusetts Institute of Technology</b><br/>Figure 1: Automated facial gesture recognition is a fundamental problem in human computer interaction. While tackling real world tasks of <br/>expression recognition sudden changes in illumination from multiple sources can be expected. We show how to build a robust system to detect <br/>human emotions while showing invariance to illumination. -</td><td>('37381309', 'Otkrist Gupta', 'otkrist gupta')<br/>('2283049', 'Dan Raviv', 'dan raviv')<br/>('1717566', 'Ramesh Raskar', 'ramesh raskar')</td><td></td></tr><tr><td>55c81f15c89dc8f6eedab124ba4ccab18cf38327</td><td></td><td></td><td></td></tr><tr><td>55bc7abcef8266d76667896bbc652d081d00f797</td><td>Impact of Facial Cosmetics on Automatic Gender and Age Estimation +</td><td>('37381309', 'Otkrist Gupta', 'otkrist gupta')<br/>('2283049', 'Dan Raviv', 'dan raviv')<br/>('1717566', 'Ramesh Raskar', 'ramesh raskar')</td><td></td></tr><tr><td>55c81f15c89dc8f6eedab124ba4ccab18cf38327</td><td></td><td></td><td></td></tr><tr><td>5550a6df1b118a80c00a2459bae216a7e8e3966c</td><td>ISSN: 0974-2115 +<br/>www.jchps.com Journal of Chemical and Pharmaceutical Sciences +<br/>A perusal on Facial Emotion Recognition System (FERS) +<br/><b>School of Information Technology and Engineering, VIT University, Vellore, 632014, India</b></td><td></td><td>*Corresponding author: E-Mail: krithika.lb@vit.ac.in +</td></tr><tr><td>55e87050b998eb0a8f0b16163ef5a28f984b01fa</td><td>CAN YOU FIND A FACE IN A HEVC BITSTREAM? +<br/><b>School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada</b></td><td>('3393216', 'Saeed Ranjbar Alvar', 'saeed ranjbar alvar')<br/>('3320198', 'Hyomin Choi', 'hyomin choi')</td><td></td></tr><tr><td>55bc7abcef8266d76667896bbc652d081d00f797</td><td>Impact of Facial Cosmetics on Automatic Gender and Age Estimation <br/>Algorithms <br/><b>Computer Science and Electrical Engineering, West Virginia University, Morgantown, USA</b><br/><b>Computer Science and Engineering, Michigan State University, East Lansing, USA</b><br/>Keywords: <br/>Biometrics, Face Recognition, Facial Cosmetics, Makeup, Gender Spoofing, Age Alteration, Automatic @@ -24992,7 +31008,40 @@ <br/>The Color of the Cat is Gray: <br/><b>The University of Tokyo</b><br/>7 Chome-3-1 Hongo, Bunkyo <br/>Tokyo 113-8654, Japan -</td><td>('2518695', 'Andrew Shin', 'andrew shin')<br/>('3250559', 'Yoshitaka Ushiku', 'yoshitaka ushiku')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td></td></tr><tr><td>973e3d9bc0879210c9fad145a902afca07370b86</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, +</td><td>('2518695', 'Andrew Shin', 'andrew shin')<br/>('3250559', 'Yoshitaka Ushiku', 'yoshitaka ushiku')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td></td></tr><tr><td>55c40cbcf49a0225e72d911d762c27bb1c2d14aa</td><td>Indian Face Age Database: A Database for Face Recognition with Age Variation +<br/>{tag} {/tag} +<br/> International Journal of Computer Applications +<br/> +<br/> Foundation of Computer Science (FCS), NY, USA +<br/> +<br/> +<br/>Volume 126 +<br/>- +<br/>Number 5 +<br/> +<br/> +<br/> Year of Publication: 2015 +<br/> +<br/> +<br/> +<br/> +<br/> Authors: +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> +<br/> 10.5120/ijca2015906055 +<br/> {bibtex}2015906055.bib{/bibtex} +</td><td>('2029759', 'Reecha Sharma', 'reecha sharma')</td><td></td></tr><tr><td>9788b491ddc188941dadf441fc143a4075bff764</td><td>LOGAN: Membership Inference Attacks Against Generative Models∗ +<br/><b>University College London</b></td><td>('9200194', 'Jamie Hayes', 'jamie hayes')<br/>('2008164', 'Luca Melis', 'luca melis')<br/>('1722262', 'George Danezis', 'george danezis')<br/>('1728207', 'Emiliano De Cristofaro', 'emiliano de cristofaro')</td><td>{j.hayes, l.melis, g.danezis, e.decristofaro}@cs.ucl.ac.uk +</td></tr><tr><td>973e3d9bc0879210c9fad145a902afca07370b86</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, <br/>Vol. 7, No. 7, 2016 <br/>From Emotion Recognition to Website <br/>Customizations @@ -25015,7 +31064,17 @@ <br/><b>M.P.M. College, Bhopal, India</b></td><td>('37930830', 'Vijay Shinde', 'vijay shinde')<br/>('9345591', 'Prakash Tanwar', 'prakash tanwar')</td><td></td></tr><tr><td>97032b13f1371c8a813802ade7558e816d25c73f</td><td>Total Recall Final Report <br/>Supervisor: Professor Duncan Gillies <br/>January 11, 2006 -</td><td>('2561350', 'Peter Collingbourne', 'peter collingbourne')<br/>('3036326', 'Khilan Gudka', 'khilan gudka')<br/>('15490561', 'Steve Lovegrove', 'steve lovegrove')<br/>('35260800', 'Jiefei Ma', 'jiefei ma')</td><td></td></tr><tr><td>978a219e07daa046244821b341631c41f91daccd</td><td>Emotional Intelligence: Giving Computers +</td><td>('2561350', 'Peter Collingbourne', 'peter collingbourne')<br/>('3036326', 'Khilan Gudka', 'khilan gudka')<br/>('15490561', 'Steve Lovegrove', 'steve lovegrove')<br/>('35260800', 'Jiefei Ma', 'jiefei ma')</td><td></td></tr><tr><td>97137d5154a9f22a5d9ecc32e8e2b95d07a5a571</td><td>The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-016-3418-y +<br/>Facial Expression Recognition based on Local Region +<br/>Specific Features and Support Vector Machines +<br/>Park1 +<br/><b>Korea Electronics Technology Institute, Jeonju-si, Jeollabuk-do 561-844, Rep. of Korea; E</b><br/><b>Division of Computer Engineering, Jeonbuk National University, Jeonju-si, Jeollabuk-do</b><br/>Tel.: +82-63-270-2406; Fax: +82-63-270-2394. +</td><td>('32322842', 'Deepak Ghimire', 'deepak ghimire')<br/>('31984909', 'SungHwan Jeong', 'sunghwan jeong')<br/>('2034182', 'Joonwhoan Lee', 'joonwhoan lee')</td><td>Mails: (deepak, shjeong, shpark)@keti.re.kr +<br/>756, Rep. of Korea; E-Mail: chlee@jbnu.ac.kr +<br/>♣ Corresponding Author; E-Mail: chlee@jbnu.ac.kr; +</td></tr><tr><td>9730b9cd998c0a549601c554221a596deda8af5b</td><td>Spatio-temporal Person Retrieval via Natural Language Queries +<br/><b>Graduate School of Information Science and Technology, The University of Tokyo</b></td><td>('3369734', 'Masataka Yamaguchi', 'masataka yamaguchi')<br/>('8915348', 'Kuniaki Saito', 'kuniaki saito')<br/>('3250559', 'Yoshitaka Ushiku', 'yoshitaka ushiku')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td>{yamaguchi, ksaito, ushiku, harada}@mi.t.u-tokyo.ac.jp +</td></tr><tr><td>978a219e07daa046244821b341631c41f91daccd</td><td>Emotional Intelligence: Giving Computers <br/>Effective Emotional Skills to Aid Interaction <br/><b>School of Computer Science, University of Birmingham, UK</b><br/>1 Introduction <br/>Why do computers need emotional intelligence? Science fiction often por- @@ -25063,7 +31122,12 @@ <br/><b>Carnegie Mellon University</b></td><td>('2232940', 'Vishnu Naresh Boddeti', 'vishnu naresh boddeti')<br/>('1733113', 'Takeo Kanade', 'takeo kanade')</td><td>naresh@cmu.edu <br/>tk@cs.cmu.edu <br/>kumar@ece.cmu.edu -</td></tr><tr><td>97d1d561362a8b6beb0fdbee28f3862fb48f1380</td><td>1955 +</td></tr><tr><td>97cf04eaf1fc0ac4de0f5ad4a510d57ce12544f5</td><td>manuscript No. +<br/>(will be inserted by the editor) +<br/>Deep Affect Prediction in-the-wild: Aff-Wild Database and Challenge, +<br/>Deep Architectures, and Beyond +<br/>Zafeiriou4 +</td><td>('1811396', 'Dimitrios Kollias', 'dimitrios kollias')<br/>('1757287', 'Guoying Zhao', 'guoying zhao')</td><td></td></tr><tr><td>97d1d561362a8b6beb0fdbee28f3862fb48f1380</td><td>1955 <br/>Age Synthesis and Estimation via Faces: <br/>A Survey </td><td>('1708679', 'Yun Fu', 'yun fu')<br/>('1822413', 'Guodong Guo', 'guodong guo')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>97540905e4a9fdf425989a794f024776f28a3fa9</td><td></td><td></td><td></td></tr><tr><td>97865d31b5e771cf4162bc9eae7de6991ceb8bbf</td><td>Face and Gender Classification in Crowd Video @@ -25076,7 +31140,23 @@ <br/>for the Degree of M.Tech. in Computer Science <br/>c(cid:13) Verma, 2015 <br/>Keywords : Face Recognition, Gender Classification, Crowd database -</td><td>('2578160', 'Priyanka Verma', 'priyanka verma')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td></td></tr><tr><td>9755554b13103df634f9b1ef50a147dd02eab02f</td><td>How Transferable are CNN-based Features for +</td><td>('2578160', 'Priyanka Verma', 'priyanka verma')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td></td></tr><tr><td>975978ee6a32383d6f4f026b944099e7739e5890</td><td>Privacy-Preserving Age Estimation +<br/>for Content Rating +<br/>Binglin Li∗ +<br/><b>University of Manitoba</b><br/><b>Simon Fraser University</b><br/>Winnipeg, Canada +<br/>Burnaby, Canada +<br/>Noman Mohammed +<br/><b>University of Manitoba</b><br/>Winnipeg, Canada +<br/>Yang Wang +<br/>Jie Liang +<br/><b>University of Manitoba</b><br/><b>Simon Fraser University</b><br/>Winnipeg, Canada +<br/>Burnaby, Canada +</td><td>('2373631', 'Linwei Ye', 'linwei ye')</td><td>yel3@cs.umanitoba.ca +<br/>binglinl@sfu.ca +<br/>noman@cs.umanitoba.ca +<br/>ywang@cs.umanitoba.ca +<br/>jiel@sfu.ca +</td></tr><tr><td>9755554b13103df634f9b1ef50a147dd02eab02f</td><td>How Transferable are CNN-based Features for <br/>Age and Gender Classification? <br/> 1 </td><td>('2850086', 'Gökhan Özbulak', 'gökhan özbulak')<br/>('3152281', 'Yusuf Aytar', 'yusuf aytar')</td><td></td></tr><tr><td>635158d2da146e9de559d2742a2fa234e06b52db</td><td></td><td></td><td></td></tr><tr><td>63d8110ac76f57b3ba8a5947bc6bdbb86f25a342</td><td>On Modeling Variations for Face Authentication @@ -25085,7 +31165,10 @@ <br/>Classification in Standard <br/>and Generalized <br/>Dissimilarity Spaces -</td><td></td><td></td></tr><tr><td>6324fada2fb00bd55e7ff594cf1c41c918813030</td><td>Uncertainty Reduction For Active Image Clustering +</td><td></td><td></td></tr><tr><td>632b24ddd42fda4aebc5a8af3ec44f7fd3ecdc6c</td><td>Real-Time Facial Segmentation +<br/>and Performance Capture from RGB Input +<br/>Pinscreen +<br/><b>University of Southern California</b></td><td>('2059597', 'Shunsuke Saito', 'shunsuke saito')<br/>('50290121', 'Tianye Li', 'tianye li')<br/>('1706574', 'Hao Li', 'hao li')</td><td></td></tr><tr><td>6324fada2fb00bd55e7ff594cf1c41c918813030</td><td>Uncertainty Reduction For Active Image Clustering <br/>via a Hybrid Global-Local Uncertainty Model <br/><b>State University of New York at Buffalo</b><br/>Department of Computer Science and Engineering <br/>338 Davis Hall, Buffalo, NY, 14260-2500 @@ -25110,6 +31193,15 @@ <br/><b>Xi an Jiaotong University, China</b><br/><b>University of Tsukuba, Japan</b></td><td>('6916241', 'Xi Li', 'xi li')<br/>('1770128', 'Kazuhiro Fukui', 'kazuhiro fukui')<br/>('1715389', 'Nanning Zheng', 'nanning zheng')</td><td>lxaccv09@yahoo.com, <br/>znn@xjtu.edu.cn <br/>kf@cs.tsukuba.ac.jp +</td></tr><tr><td>631483c15641c3652377f66c8380ff684f3e365c</td><td>Sync-DRAW: Automatic Video Generation using Deep Recurrent +<br/>A(cid:130)entive Architectures +<br/>Gaurav Mi(cid:138)al∗ +<br/>IIT Hyderabad +<br/>Vineeth N Balasubramanian +<br/>IIT Hyderabad +</td><td>('8268761', 'Tanya Marwah', 'tanya marwah')</td><td>gaurav.mi(cid:138)al.191013@gmail.com +<br/>ee13b1044@iith.ac.in +<br/>vineethnb@iith.ac.in </td></tr><tr><td>63a6c256ec2cf2e0e0c9a43a085f5bc94af84265</td><td>Complexity of Multiverse Networks and <br/>their Multilayer Generalization <br/>The Blavatnik School of Computer Science @@ -25118,10 +31210,26 @@ <br/>3INRIA <br/>http://rohitgirdhar.github.io/ActionVLAD </td><td>('3102850', 'Rohit Girdhar', 'rohit girdhar')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')<br/>('1782755', 'Josef Sivic', 'josef sivic')<br/>('2015670', 'Bryan Russell', 'bryan russell')</td><td></td></tr><tr><td>630d1728435a529d0b0bfecb0e7e335f8ea2596d</td><td>Facial Action Unit Detection by Cascade of Tasks -<br/><b>School of Information Science and Engineering, Southeast University, Nanjing, China</b><br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b><br/><b>University of Pittsburgh, Pittsburgh, PA</b></td><td>('2499751', 'Xiaoyu Ding', 'xiaoyu ding')<br/>('18870591', 'Qiao Wang', 'qiao wang')</td><td></td></tr><tr><td>63eefc775bcd8ccad343433fc7a1dd8e1e5ee796</td><td></td><td></td><td></td></tr><tr><td>63340c00896d76f4b728dbef85674d7ea8d5ab26</td><td>1732 +<br/><b>School of Information Science and Engineering, Southeast University, Nanjing, China</b><br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b><br/><b>University of Pittsburgh, Pittsburgh, PA</b></td><td>('2499751', 'Xiaoyu Ding', 'xiaoyu ding')<br/>('18870591', 'Qiao Wang', 'qiao wang')</td><td></td></tr><tr><td>63eefc775bcd8ccad343433fc7a1dd8e1e5ee796</td><td></td><td></td><td></td></tr><tr><td>632fa986bed53862d83918c2b71ab953fd70d6cc</td><td>GÜNEL ET AL.: WHAT FACE AND BODY SHAPES CAN TELL ABOUT HEIGHT +<br/>What Face and Body Shapes Can Tell +<br/>About Height +<br/>CVLab +<br/>EPFL, +<br/>Lausanne, Switzerland +</td><td>('46211822', 'Semih Günel', 'semih günel')<br/>('2933543', 'Helge Rhodin', 'helge rhodin')<br/>('1717736', 'Pascal Fua', 'pascal fua')</td><td>semih.gunel@epfl.ch +<br/>helge.rhodin@epfl.ch +<br/>pascal.fua@epfl.ch +</td></tr><tr><td>63340c00896d76f4b728dbef85674d7ea8d5ab26</td><td>1732 <br/>Discriminant Subspace Analysis: <br/>A Fukunaga-Koontz Approach -</td><td>('40404906', 'Sheng Zhang', 'sheng zhang')<br/>('1715286', 'Terence Sim', 'terence sim')</td><td></td></tr><tr><td>63a2e2155193dc2da9764ae7380cdbd044ff2b94</td><td>A Dense SURF and Triangulation based +</td><td>('40404906', 'Sheng Zhang', 'sheng zhang')<br/>('1715286', 'Terence Sim', 'terence sim')</td><td></td></tr><tr><td>633101e794d7b80f55f466fd2941ea24595e10e6</td><td>In submission to IEEE conference +<br/>Face Attribute Prediction with classification CNN +<br/>FACE ATTRIBUTE PREDICTION WITH +<br/>CLASSIFICATION CNN +<br/>Computer Science and Communication +<br/><b>KTH Royal Institute of Technology</b><br/>100 44 Stockholm, Sweden +</td><td>('50262049', 'Yang Zhong', 'yang zhong')<br/>('1736906', 'Josephine Sullivan', 'josephine sullivan')<br/>('40565290', 'Haibo Li', 'haibo li')</td><td>{yzhong, sullivan, haiboli}@kth.se +</td></tr><tr><td>63a2e2155193dc2da9764ae7380cdbd044ff2b94</td><td>A Dense SURF and Triangulation based <br/>Spatio-Temporal Feature for Action Recognition <br/><b>The University of Electro-Communications</b><br/>Chofu, Tokyo 182-8585 JAPAN </td><td>('2274625', 'Do Hang Nga', 'do hang nga')<br/>('1681659', 'Keiji Yanai', 'keiji yanai')</td><td>fdohang,yanaig@mm.cs.uec.ac.jp @@ -25493,7 +31601,27 @@ <br/><b>Rensselaer Polytechnic Institute</b><br/>Troy, NY 12180 </td><td>('1713712', 'Jixu Chen', 'jixu chen')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>chenj4@rpi.edu <br/>qji@ecse.rpi.edu -</td></tr><tr><td>0faeec0d1c51623a511adb779dabb1e721a6309b</td><td>Seeing is Worse than Believing: Reading +</td></tr><tr><td>0f21a39fa4c0a19c4a5b4733579e393cb1d04f71</td><td>Evaluation of optimization +<br/>components of a 3D to 2D +<br/>landmark fitting algorithm for +<br/>head pose estimation +<br/>11029668 +<br/>Bachelor thesis +<br/>Credits: 18 EC +<br/>Bachelor Opleiding Kunstmatige Intelligentie +<br/><b>University of Amsterdam</b><br/>Faculty of Science +<br/>Science Park 904 +<br/>1098 XH Amsterdam +<br/>Supervisors +<br/>dr. Sezer Karaoglu +<br/>MSc. Minh Ngo +<br/><b>Informatics Institute</b><br/>Faculty of Science +<br/><b>University of Amsterdam</b><br/>Science Park 904 +<br/>1090 GH Amsterdam +<br/>June 29th, 2018 +</td><td></td><td></td></tr><tr><td>0fd1bffb171699a968c700f206665b2f8837d953</td><td>Weakly Supervised Object Localization with +<br/>Multi-fold Multiple Instance Learning +</td><td>('1939006', 'Ramazan Gokberk Cinbis', 'ramazan gokberk cinbis')<br/>('34602236', 'Jakob Verbeek', 'jakob verbeek')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>0faeec0d1c51623a511adb779dabb1e721a6309b</td><td>Seeing is Worse than Believing: Reading <br/>People’s Minds Better than Computer-Vision <br/>Methods Recognize Actions <br/>1 MIT, Cambridge, MA, USA @@ -25522,7 +31650,14 @@ </td></tr><tr><td>0a64f4fec592662316764283575d05913eb2135b</td><td>Joint Pixel and Feature-level Domain Adaptation in the Wild <br/><b>Michigan State University</b><br/>2NEC Labs America <br/>3UC San Diego -</td><td>('1849929', 'Luan Tran', 'luan tran')</td><td></td></tr><tr><td>0a2ddf88bd1a6c093aad87a8c7f4150bfcf27112</td><td>Patch-based Models For Visual Object Classes +</td><td>('1849929', 'Luan Tran', 'luan tran')</td><td></td></tr><tr><td>0a0321785c8beac1cbaaec4d8ad0cfd4a0d6d457</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Learning Invariant Deep Representation +<br/>for NIR-VIS Face Recognition +<br/>National Laboratory of Pattern Recognition, CASIA +<br/>Center for Research on Intelligent Perception and Computing, CASIA +<br/>Center for Excellence in Brain Science and Intelligence Technology, CAS +<br/><b>University of Chinese Academy of Sciences, Beijing 100190, China</b></td><td>('1705643', 'Ran He', 'ran he')<br/>('2225749', 'Xiang Wu', 'xiang wu')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')<br/>('1688870', 'Tieniu Tan', 'tieniu tan')</td><td>{rhe,znsun,tnt}@nlpr.ia.ac.cn, alfredxiangwu@gmail.com +</td></tr><tr><td>0a2ddf88bd1a6c093aad87a8c7f4150bfcf27112</td><td>Patch-based Models For Visual Object Classes <br/>A dissertation submitted in partial fulfilment <br/>of the requirements for the degree of <br/>Doctor of Philosophy @@ -25563,12 +31698,23 @@ </td><td>('2527457', 'Maxime Sangnier', 'maxime sangnier')<br/>('1792962', 'Alain Rakotomamonjy', 'alain rakotomamonjy')</td><td>MAXIME.SANGNIER@TELECOM-PARISTECH.FR <br/>JEROME.GAUTHIER@CEA.FR <br/>ALAIN.RAKOTO@INSA-ROUEN.FR +</td></tr><tr><td>0a60d9d62620e4f9bb3596ab7bb37afef0a90a4f</td><td>Chimpanzee Faces in the Wild: Log-Euclidean CNNs for Predicting Identities and Attributes of Primates. GCPR 2016 +<br/>c(cid:13) Copyright by Springer. The final publication will be available at link.springer.com +<br/>A. Freytag, E. Rodner, M. Simon, A. Loos, H. K¨uhl and J. Denzler +<br/>Chimpanzee Faces in the Wild: +<br/>Log-Euclidean CNNs for Predicting Identities +<br/>and Attributes of Primates +<br/><b>Computer Vision Group, Friedrich Schiller University Jena, Germany</b><br/>2Michael Stifel Center Jena, Germany +<br/><b>Fraunhofer Institute for Digital Media Technology, Germany</b><br/><b>Max Planck Institute for Evolutionary Anthropology, Germany</b><br/>5German Centre for Integrative Biodiversity Research (iDiv), Germany +</td><td>('1720839', 'Alexander Freytag', 'alexander freytag')<br/>('1679449', 'Erik Rodner', 'erik rodner')<br/>('49675890', 'Marcel Simon', 'marcel simon')<br/>('4572597', 'Alexander Loos', 'alexander loos')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td></td></tr><tr><td>0a34fe39e9938ae8c813a81ae6d2d3a325600e5c</td><td>FacePoseNet: Making a Case for Landmark-Free Face Alignment +<br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b></td><td>('1752756', 'Feng-Ju Chang', 'feng-ju chang')<br/>('46634688', 'Anh Tuan Tran', 'anh tuan tran')<br/>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')</td><td>{fengjuch,anhttran,iacopoma,nevatia,medioni}@usc.edu, hassner@isi.edu </td></tr><tr><td>0ad8149318912b5449085187eb3521786a37bc78</td><td>CP-mtML: Coupled Projection multi-task Metric Learning <br/>for Large Scale Face Retrieval <br/>Frederic Jurie1,∗ <br/><b>University of Caen, France</b><br/>2MPI for Informatics, Germany <br/>3IIT Kanpur, India -</td><td>('2078892', 'Binod Bhattarai', 'binod bhattarai')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>0aa9872daf2876db8d8e5d6197c1ce0f8efee4b7</td><td><b>Imperial College of Science, Technology and Medicine</b><br/>Department of Computing +</td><td>('2078892', 'Binod Bhattarai', 'binod bhattarai')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>0a9d204db13d395f024067cf70ac19c2eeb5f942</td><td>Viewpoint-aware Video Summarization +<br/><b>The University of Tokyo, 2RIKEN, 3ETH Z urich, 4KU Leuven</b></td><td>('2551640', 'Atsushi Kanehira', 'atsushi kanehira')<br/>('1681236', 'Luc Van Gool', 'luc van gool')<br/>('3250559', 'Yoshitaka Ushiku', 'yoshitaka ushiku')<br/>('1790553', 'Tatsuya Harada', 'tatsuya harada')</td><td></td></tr><tr><td>0aa9872daf2876db8d8e5d6197c1ce0f8efee4b7</td><td><b>Imperial College of Science, Technology and Medicine</b><br/>Department of Computing <br/>Timing is everything <br/>A spatio-temporal approach to the analysis of facial <br/>actions @@ -25591,6 +31737,100 @@ <br/><b>University of Missouri, Columbia, MO</b></td><td>('2741325', 'K. Stone', 'k. stone')<br/>('9187168', 'J. M. Keller', 'j. m. keller')</td><td></td></tr><tr><td>0ad90118b4c91637ee165f53d557da7141c3fde0</td><td></td><td></td><td></td></tr><tr><td>0a82860d11fcbf12628724333f1e7ada8f3cd255</td><td>Action Temporal Localization in Untrimmed Videos via Multi-stage CNNs <br/><b>Columbia University</b><br/>New York, NY, USA </td><td>('2195345', 'Zheng Shou', 'zheng shou')<br/>('2704179', 'Dongang Wang', 'dongang wang')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>{zs2262,dw2648,sc250}@columbia.edu +</td></tr><tr><td>0a4fc9016aacae9cdf40663a75045b71e64a70c9</td><td>JOURNAL OF INFORMATION SCIENCE AND ENGINEERING XX, XXX-XXX (201X) +<br/> Illumination Normalization Based on +<br/>Homomorphic Wavelet Filtering for Face Recognition +<br/>1School of Electronic and Information Engineering +<br/><b>Beijing Jiaotong University</b><br/>No.3 Shang Yuan Cun,Hai Dian District +<br/>Beijing 100044,China +<br/>2School of Physics Electrical Information Engineering +<br/><b>Ningxia University</b><br/>Yinchuan Ningxia 750021,China +<br/>Phone number: 086-010-51688165 +<br/>The performance of face recognition techniques is greatly challenged by the pose, +<br/>expression and illumination of the image. For most existing systems, the recognition rate +<br/>will decrease due to changes in environmental illumination. In this paper, a +<br/>Homomorphic Wavelet-based Illumination Normalization (HWIN) method is proposed. +<br/>The purpose of this method is to normalize the uneven illumination of the facial image. +<br/>The image is analyzed in the logarithm domain with wavelet transform, the +<br/>approximation coefficients of the image are mapped according to the reference +<br/>illumination map in order to normalize the distribution of illumination energy resulting +<br/>from different lighting effects, and the detail components are enhanced to achieve detail +<br/>information emphasis. Then, a Difference of Gaussian (DoG) filter is also applied to +<br/>reduce the noise resulting from different lighting effects, which exists on detail +<br/>components. The proposed methods are implemented on Yale B and Extended Yale B +<br/>facial databases. The experimental results show that the methods described in this study +<br/>are capable of effectively eliminating the effects of uneven illumination and of greatly +<br/>improving the recognition rate, and are therefore more effective than other popular +<br/>methods. +<br/>Keywords: face recognition; homomorphic filtering; wavelet transfer; illumination +<br/>mapping +<br/>1. INTRODUCTION +<br/>Automatic face recognition has received significant attention over the past several +<br/>decades due to its numerous potential applications, such as human-computer interfaces, +<br/>access control, security and surveillance, e-commerce, entertainment, and so on. Related +<br/>research performed in recent years has made great progress, and a number of face +<br/>recognition systems have achieved strong results, as shown in the latest report of Face +<br/>Recognition Vendor Test (FRVT, 2006). Despite this remarkable progress, face +<br/>recognition still faces a challenging problem, which is its sensitivity to the dramatic +<br/>variations among images of the same face. For example, facial expression, pose, ageing, +<br/>make-up, background and illumination variations are all factors which may result in +<br/>significant variations [1-26]. +<br/>Illumination variation is one of the most significant factors limiting the performance +<br/>of face recognition. Since several images of the same person appear to be dramatically +<br/>1 +</td><td>('2613621', 'Xue Yuan', 'xue yuan')<br/>('47884608', 'Yifei Meng', 'yifei meng')</td><td>E-mail: 10111045@bjtu.edu.cn +</td></tr><tr><td>0a85afebaa19c80fddb660110a4352fd22eb2801</td><td>Neural Animation and Reenactment of Human Actor Videos +<br/>Fig. 1. We propose a novel learning-based approach for the animation and reenactment of human actor videos. The top row shows some frames of the video +<br/>We propose a method for generating (near) video-realistic animations of +<br/>real humans under user control. In contrast to conventional human char- +<br/>acter rendering, we do not require the availability of a production-quality +<br/>photo-realistic 3D model of the human, but instead rely on a video sequence +<br/>in conjunction with a (medium-quality) controllable 3D template model +<br/>of the person. With that, our approach significantly reduces production +<br/>cost compared to conventional rendering approaches based on production- +<br/>quality 3D models, and can also be used to realistically edit existing videos. +<br/>Technically, this is achieved by training a neural network that translates +<br/>simple synthetic images of a human character into realistic imagery. For +<br/>training our networks, we first track the 3D motion of the person in the +<br/>video using the template model, and subsequently generate a synthetically +<br/><b>mpg.de, Max Planck Institute for Informatics</b><br/>Permission to make digital or hard copies of part or all of this work for personal or +<br/>classroom use is granted without fee provided that copies are not made or distributed +<br/>for profit or commercial advantage and that copies bear this notice and the full citation +<br/>on the first page. Copyrights for third-party components of this work must be honored. +<br/>For all other uses, contact the owner/author(s). +<br/>© 2018 Copyright held by the owner/author(s). +<br/>XXXX-XXXX/2018/9-ART282 +<br/>https://doi.org/10.475/123_4 +<br/>rendered version of the video. These images are then used to train a con- +<br/>ditional generative adversarial network that translates synthetic images of +<br/>the 3D model into realistic imagery of the human. We evaluate our method +<br/>for the reenactment of another person that is tracked in order to obtain the +<br/>motion data, and show video results generated from artist-designed skeleton +<br/>motion. Our results outperform the state-of-the-art in learning-based human +<br/>image synthesis. +<br/>CCS Concepts: • Computing methodologies → Computer graphics; +<br/>Neural networks; Appearance and texture representations; Animation; Ren- +<br/>dering; +<br/>Additional Key Words and Phrases: Video-based Characters, Deep Learning, +<br/>Conditional GAN, Rendering-to-Video Translation +<br/>ACM Reference Format: +<br/>Animation and Reenactment of Human Actor Videos. 1, 1, Article 282 +<br/>(September 2018), 13 pages. https://doi.org/10.475/123_4 +<br/>INTRODUCTION +<br/>The creation of realistically rendered and controllable animations +<br/>of human characters is a crucial task in many computer graphics +<br/>applications. Virtual actors play a key role in games and visual ef- +<br/>fects, in telepresence, or in virtual and augmented reality. Today, the +<br/>plausible rendition of video-realistic characters—i.e., animations in- +<br/>distinguishable from a video of a human—under user control is also +<br/>Submission ID: 282. 2018-09-12 00:32. Page 1 of 1–13. +<br/>, Vol. 1, No. 1, Article 282. Publication date: September 2018. +</td><td>('46458089', 'Lingjie Liu', 'lingjie liu')<br/>('9765909', 'Weipeng Xu', 'weipeng xu')<br/>('1699058', 'Michael Zollhöfer', 'michael zollhöfer')<br/>('3022958', 'Hyeongwoo Kim', 'hyeongwoo kim')<br/>('39600032', 'Florian Bernard', 'florian bernard')<br/>('14210288', 'Marc Habermann', 'marc habermann')<br/>('1698520', 'Wenping Wang', 'wenping wang')<br/>('1680185', 'Christian Theobalt', 'christian theobalt')<br/>('3022958', 'Hyeongwoo Kim', 'hyeongwoo kim')<br/>('46458089', 'Lingjie Liu', 'lingjie liu')<br/>('9765909', 'Weipeng Xu', 'weipeng xu')<br/>('1699058', 'Michael Zollhöfer', 'michael zollhöfer')<br/>('3022958', 'Hyeongwoo Kim', 'hyeongwoo kim')<br/>('39600032', 'Florian Bernard', 'florian bernard')<br/>('14210288', 'Marc Habermann', 'marc habermann')<br/>('1698520', 'Wenping Wang', 'wenping wang')<br/>('1680185', 'Christian Theobalt', 'christian theobalt')</td><td>Authors’ addresses: Lingjie Liu, liulingjie0206@gmail.com, University of Hong Kong, +<br/>Max Planck Institute for Informatics; Weipeng Xu, wxu@mpi-inf.mpg.de, Max Planck +<br/>Institute for Informatics; Michael Zollhöfer, zollhoefer@cs.stanford.edu, Stanford +<br/>kim@mpi-inf.mpg.de; Florian Bernard, fbernard@mpi-inf.mpg.de; Marc Habermann, +<br/>mhaberma@mpi-inf.mpg.de, Max Planck Institute for Informatics; Wenping Wang, +<br/>wenping@cs.hku.hk, University of Hong Kong; Christian Theobalt, theobalt@mpi-inf. </td></tr><tr><td>0ac442bb570b086d04c4d51a8410fcbfd0b1779d</td><td>WarpNet: Weakly Supervised Matching for Single-view Reconstruction <br/><b>University of Maryland, College Park</b><br/>Manmohan Chandraker <br/>NEC Labs America @@ -25762,7 +32002,12 @@ <br/>AT <br/><b>CARNEGIE MELLON UNIVERSITY</b><br/>5000 FORBES AVENUE PITTSBURGH PA 15213-3890 <br/>MAY 2004 -</td><td>('3039721', 'Avinash B. Baliga', 'avinash b. baliga')<br/>('3039721', 'Avinash B. Baliga', 'avinash b. baliga')</td><td></td></tr><tr><td>0a11b82aa207d43d1b4c0452007e9388a786be12</td><td>Feature Level Multiple Model Fusion Using Multilinear +</td><td>('3039721', 'Avinash B. Baliga', 'avinash b. baliga')<br/>('3039721', 'Avinash B. Baliga', 'avinash b. baliga')</td><td></td></tr><tr><td>0a7309147d777c2f20f780a696efe743520aa2db</td><td>Stories for Images-in-Sequence by using Visual +<br/>and Narrative Components (cid:63) +<br/><b>Ss. Cyril and Methodius University, Skopje, Macedonia</b><br/>2 Pendulibrium, Skopje, Macedonia +<br/>3 Elevate Global, Skopje, Macedonia +</td><td>('46205557', 'Marko Smilevski', 'marko smilevski')<br/>('46242132', 'Ilija Lalkovski', 'ilija lalkovski')</td><td>{marko.smilevski,ilija}@webfactory.mk, gjorgji.madjarov@finki.ukim.mk +</td></tr><tr><td>0a11b82aa207d43d1b4c0452007e9388a786be12</td><td>Feature Level Multiple Model Fusion Using Multilinear <br/>Subspace Analysis with Incomplete Training Set <br/>and Its Application to Face Image Analysis <br/><b>School of IoT Engineering, Jiangnan University, Wuxi, 214122, China</b><br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, GU2 7XH</b><br/>United Kingdom @@ -25772,7 +32017,7 @@ <br/>The final version of record is available at <br/> http://dx.doi.org/10.1109/TIP.2016.2539502 <br/>Discriminant Incoherent Component Analysis -</td><td>('2812961', 'Christos Georgakis', 'christos georgakis')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>0ae9cc6a06cfd03d95eee4eca9ed77b818b59cb7</td><td>Noname manuscript No. +</td><td>('2812961', 'Christos Georgakis', 'christos georgakis')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>0a6a25ee84fc0bf7284f41eaa6fefaa58b5b329a</td><td></td><td>('1802883', 'Soufiane Belharbi', 'soufiane belharbi')</td><td></td></tr><tr><td>0ae9cc6a06cfd03d95eee4eca9ed77b818b59cb7</td><td>Noname manuscript No. <br/>(will be inserted by the editor) <br/>Multi-task, multi-label and multi-domain learning with <br/>residual convolutional networks for emotion recognition @@ -25824,7 +32069,26 @@ <br/>1Department of Creative IT Engineering, POSTECH, Korea <br/>2Department of Computer Science and Engineering, POSTECH, Korea </td><td>('2794366', 'Bong-Nam Kang', 'bong-nam kang')<br/>('1804861', 'Yonghyun Kim', 'yonghyun kim')<br/>('1695669', 'Daijin Kim', 'daijin kim')</td><td>{bnkang, gkyh0805, dkim}@postech.ac.kr -</td></tr><tr><td>6409b8879c7e61acf3ca17bcc62f49edca627d4c</td><td>Learning Finite Beta-Liouville Mixture Models via +</td></tr><tr><td>641f0989b87bf7db67a64900dcc9568767b7b50f</td><td>Reconstructing Faces from their Signatures using RBF +<br/>Regression +<br/>To cite this version: +<br/>sion. British Machine Vision Conference 2013, Sep 2013, Bristol, United Kingdom. pp.103.1– +<br/>103.12, 2013, <10.5244/C.27.103>. <hal-00943426> +<br/>HAL Id: hal-00943426 +<br/>https://hal.archives-ouvertes.fr/hal-00943426 +<br/>Submitted on 13 Feb 2014 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destin´ee au d´epˆot et `a la diffusion de documents +<br/>scientifiques de niveau recherche, publi´es ou non, +<br/>´emanant des ´etablissements d’enseignement et de +<br/>recherche fran¸cais ou ´etrangers, des laboratoires +<br/>publics ou priv´es. +</td><td>('34723309', 'Alexis Mignon', 'alexis mignon')<br/>('34723309', 'Alexis Mignon', 'alexis mignon')</td><td></td></tr><tr><td>6409b8879c7e61acf3ca17bcc62f49edca627d4c</td><td>Learning Finite Beta-Liouville Mixture Models via <br/>Variational Bayes for Proportional Data Clustering <br/>Electrical and Computer Engineering <br/><b>Institute for Information Systems Engineering</b><br/><b>Concordia University, Canada</b><br/><b>Concordia University, Canada</b></td><td>('2038786', 'Wentao Fan', 'wentao fan')<br/>('1729109', 'Nizar Bouguila', 'nizar bouguila')</td><td>wenta fa@encs.concordia.ca @@ -25833,7 +32097,11 @@ <br/>Faces using Eigenfaces <br/>Department of Informatics <br/><b>Technical University of Munich, Germany</b></td><td>('1725709', 'Zahid Riaz', 'zahid riaz')<br/>('1746229', 'Michael Beetz', 'michael beetz')<br/>('1699132', 'Bernd Radig', 'bernd radig')</td><td>{riaz,beetz,radig}@in.tum.de -</td></tr><tr><td>649eb674fc963ce25e4e8ce53ac7ee20500fb0e3</td><td></td><td></td><td></td></tr><tr><td>642c66df8d0085d97dc5179f735eed82abf110d0</td><td></td><td></td><td></td></tr><tr><td>6459f1e67e1ea701b8f96177214583b0349ed964</td><td>GENERALIZED SUBSPACE BASED HIGH DIMENSIONAL DENSITY ESTIMATION +</td></tr><tr><td>649eb674fc963ce25e4e8ce53ac7ee20500fb0e3</td><td></td><td></td><td></td></tr><tr><td>64ec0c53dd1aa51eb15e8c2a577701e165b8517b</td><td>Online Regression with Feature Selection in +<br/>Stochastic Data Streams +<br/><b>Florida State University</b><br/><b>Florida State University</b></td><td>('5517409', 'Lizhe Sun', 'lizhe sun')<br/>('2455529', 'Adrian Barbu', 'adrian barbu')</td><td>lizhe.sun@stat.fsu.edu +<br/>abarbu@stat.fsu.edu +</td></tr><tr><td>642c66df8d0085d97dc5179f735eed82abf110d0</td><td></td><td></td><td></td></tr><tr><td>6459f1e67e1ea701b8f96177214583b0349ed964</td><td>GENERALIZED SUBSPACE BASED HIGH DIMENSIONAL DENSITY ESTIMATION <br/><b>University of California Santa Barbara</b><br/><b>University of California Santa Barbara</b></td><td>('3231876', 'Karthikeyan Shanmuga Vadivel', 'karthikeyan shanmuga vadivel')</td><td>(cid:63){karthikeyan,msargin,sjoshi,manj}@ece.ucsb.edu <br/>†grafton@psych.ucsb.edu </td></tr><tr><td>64cf86ba3b23d3074961b485c16ecb99584401de</td><td>Single Image 3D Interpreter Network @@ -25902,13 +32170,28 @@ <br/>Program (Grant No. YB20081000401) and the Fundamental Research Funds for the Central Universities <br/>(Grant No. 2011JBM022). <br/>1 -</td><td>('1701978', 'Song Guo', 'song guo')<br/>('1738408', 'Qiuqi Ruan', 'qiuqi ruan')<br/>('1718667', 'Zhan Wang', 'zhan wang')<br/>('1702894', 'Shuai Liu', 'shuai liu')</td><td></td></tr><tr><td>6462ef39ca88f538405616239471a8ea17d76259</td><td></td><td></td><td></td></tr><tr><td>64d5772f44efe32eb24c9968a3085bc0786bfca7</td><td>Morphable Displacement Field Based Image +</td><td>('1701978', 'Song Guo', 'song guo')<br/>('1738408', 'Qiuqi Ruan', 'qiuqi ruan')<br/>('1718667', 'Zhan Wang', 'zhan wang')<br/>('1702894', 'Shuai Liu', 'shuai liu')</td><td></td></tr><tr><td>645de797f936cb19c1b8dba3b862543645510544</td><td>Deep Temporal Linear Encoding Networks +<br/>1ESAT-PSI, KU Leuven, 2CVL, ETH Z¨urich +</td><td>('3310120', 'Ali Diba', 'ali diba')<br/>('50633941', 'Vivek Sharma', 'vivek sharma')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>{firstname.lastname}@esat.kuleuven.be +</td></tr><tr><td>6462ef39ca88f538405616239471a8ea17d76259</td><td></td><td></td><td></td></tr><tr><td>64d5772f44efe32eb24c9968a3085bc0786bfca7</td><td>Morphable Displacement Field Based Image <br/>Matching for Face Recognition across Pose <br/>1 Key Lab of Intelligent Information Processing of Chinese Academy of Sciences <br/><b>CAS), Institute of Computing Technology, CAS, Beijing, 100190, China</b><br/><b>Graduate University of Chinese Academy of Sciences, Beijing 100049, China</b><br/>3 Omron Social Solutions Co., LTD., Kyoto, Japan </td><td>('1688086', 'Shaoxin Li', 'shaoxin li')<br/>('1731144', 'Xin Liu', 'xin liu')<br/>('1695600', 'Xiujuan Chai', 'xiujuan chai')<br/>('1705483', 'Haihong Zhang', 'haihong zhang')<br/>('1710195', 'Shihong Lao', 'shihong lao')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')</td><td>{shaoxin.li,xiujuan.chai,xin.liu,shiguang.shan}@vipl.ict.ac.cn, <br/>lao@ari.ncl.omron.co.jp, angelazhang@ssb.kusatsu.omron.co.jp -</td></tr><tr><td>90d735cffd84e8f2ae4d0c9493590f3a7d99daf1</td><td>Original Research Paper +</td></tr><tr><td>64d7e62f46813b5ad08289aed5dc4825d7ec5cff</td><td>YAMAGUCHI et al.: MIX AND MATCH +<br/>Mix and Match: Joint Model for Clothing and +<br/>Attribute Recognition +<br/>http://vision.is.tohoku.ac.jp/~kyamagu +<br/><b>Tohoku University</b><br/>Sendai, Japan +<br/>2 NTT +<br/>Yokosuka, Japan +<br/><b>Tokyo University of Science</b><br/>Tokyo, Japan +</td><td>('1721910', 'Kota Yamaguchi', 'kota yamaguchi')<br/>('1718872', 'Takayuki Okatani', 'takayuki okatani')<br/>('1745497', 'Kyoko Sudo', 'kyoko sudo')<br/>('2023568', 'Kazuhiko Murasaki', 'kazuhiko murasaki')<br/>('2113938', 'Yukinobu Taniguchi', 'yukinobu taniguchi')</td><td>okatani@vision.is.tohoku.ac.jp +<br/>sudo.kyoko@lab.ntt.co.jp +<br/>murasaki.kazuhiko@lab.ntt.co.jp +<br/>ytaniguti@ms.kagu.tus.ac.jp +</td></tr><tr><td>90ac0f32c0c29aa4545ed3d5070af17f195d015f</td><td></td><td></td><td></td></tr><tr><td>90d735cffd84e8f2ae4d0c9493590f3a7d99daf1</td><td>Original Research Paper <br/>American Journal of Engineering and Applied Sciences <br/>Recognition of Faces using Efficient Multiscale Local Binary <br/>Pattern and Kernel Discriminant Analysis in Varying @@ -25937,7 +32220,14 @@ <br/>of <br/>Doctor of Philosophy <br/>June 2014 -</td><td></td><td></td></tr><tr><td>90fb58eeb32f15f795030c112f5a9b1655ba3624</td><td>INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS +</td><td></td><td></td></tr><tr><td>90498b95fe8b299ce65d5cafaef942aa58bd68b7</td><td>Face Recognition: Primates in the Wild∗ +<br/><b>Michigan State University, East Lansing, MI, USA</b><br/><b>University of Chester, UK, 3Conservation Biologist</b></td><td>('32623642', 'Debayan Deb', 'debayan deb')<br/>('46516859', 'Susan Wiper', 'susan wiper')<br/>('9658130', 'Sixue Gong', 'sixue gong')<br/>('9644181', 'Yichun Shi', 'yichun shi')<br/>('41022894', 'Cori Tymoszek', 'cori tymoszek')</td><td>E-mail: 1{debdebay, gongsixu, shiyichu, tymoszek, jain}@cse.msu.edu, +<br/>2s.wiper@chester.ac.uk, 3alexandra.h.russo@gmail.com +</td></tr><tr><td>90cc2f08a6c2f0c41a9dd1786bae097f9292105e</td><td>Top-down Attention Recurrent VLAD Encoding +<br/>for Action Recognition in Videos +<br/>1 Fondazione Bruno Kessler, Trento, Italy +<br/><b>University of Trento, Trento, Italy</b></td><td>('1756362', 'Swathikiran Sudhakaran', 'swathikiran sudhakaran')<br/>('1717522', 'Oswald Lanz', 'oswald lanz')</td><td>{sudhakaran,lanz}@fbk.eu +</td></tr><tr><td>90fb58eeb32f15f795030c112f5a9b1655ba3624</td><td>INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND ROBOTICS <br/> www.ijrcar.com <br/>Vol.4 Issue 6, Pg.: 12-27 <br/>June 2016 @@ -26035,6 +32325,17 @@ <br/>Frontiers in Robotics and AI | www.frontiersin.org <br/>November 2015 | Volume 2 | Article 28 </td><td>('2045915', 'Michalis Vrigkas', 'michalis vrigkas')<br/>('1727495', 'Christophoros Nikou', 'christophoros nikou')<br/>('1706204', 'Ioannis A. Kakadiaris', 'ioannis a. kakadiaris')<br/>('1727495', 'Christophoros Nikou', 'christophoros nikou')</td><td>cnikou@cs.uoi.gr +</td></tr><tr><td>90d9209d5dd679b159051a8315423a7f796d704d</td><td>Temporal Sequence Distillation: Towards Few-Frame Action +<br/>Recognition in Videos +<br/><b>Wuhan University</b><br/>SenseTime Research +<br/>SenseTime Research +<br/><b>The Chinese University of Hong Kong</b><br/>SenseTime Research +<br/>SenseTime Research +</td><td>('40192003', 'Zhaoyang Zhang', 'zhaoyang zhang')<br/>('1874900', 'Zhanghui Kuang', 'zhanghui kuang')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1739512', 'Litong Feng', 'litong feng')<br/>('1726357', 'Wei Zhang', 'wei zhang')</td><td>zhangzhaoyang@whu.edu.cn +<br/>kuangzhanghui@sensetime.com +<br/>pluo@ie.cuhk.edu.hk +<br/>fenglitong@sensetime.com +<br/>wayne.zhang@sensetime.com </td></tr><tr><td>90dd2a53236b058c79763459b9d8a7ba5e58c4f1</td><td>Capturing Correlations Among Facial Parts for <br/>Facial Expression Analysis <br/>Department of Computer Science @@ -26078,7 +32379,87 @@ <br/>Image processing and computer vision, segmentation, edge detection, facial landmark localization, facial <br/>expressions, action units. </td><td>('2935367', 'Yulia Gizatdinova', 'yulia gizatdinova')<br/>('1718377', 'Veikko Surakka', 'veikko surakka')</td><td>{yulia.gizatdinova, veikko.surakka}@cs.uta.fi -</td></tr><tr><td>bf1e0279a13903e1d43f8562aaf41444afca4fdc</td><td> International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 +</td></tr><tr><td>bf961e4a57a8f7e9d792e6c2513ee1fb293658e9</td><td>EURASIP Journal on Applied Signal Processing 2004:16, 2533–2543 +<br/>c(cid:1) 2004 Hindawi Publishing Corporation +<br/>Robust Face Image Matching under +<br/>Illumination Variations +<br/><b>National Tsing Hua University, 101 Kuang Fu Road, Section 2, Hsinchu 300, Taiwan</b><br/><b>National Tsing Hua University, 101 Kuang Fu Road, Section 2, Hsinchu 300, Taiwan</b><br/><b>National Tsing Hua University, 101 Kuang Fu Road, Section 2, Hsinchu 300, Taiwan</b><br/>Received 1 September 2003; Revised 21 September 2004 +<br/>Face image matching is an essential step for face recognition and face verification. It is difficult to achieve robust face matching +<br/>under various image acquisition conditions. In this paper, a novel face image matching algorithm robust against illumination +<br/>variations is proposed. The proposed image matching algorithm is motivated by the characteristics of high image gradient along +<br/>the face contours. We define a new consistency measure as the inner product between two normalized gradient vectors at the +<br/>corresponding locations in two images. The normalized gradient is obtained by dividing the computed gradient vector by the +<br/>corresponding locally maximal gradient magnitude. Then we compute the average consistency measures for all pairs of the corre- +<br/>sponding face contour pixels to be the robust matching measure between two face images. To alleviate the problem due to shadow +<br/>and intensity saturation, we introduce an intensity weighting function for each individual consistency measure to form a weighted +<br/>average of the consistency measure. This robust consistency measure is further extended to integrate multiple face images of the +<br/>same person captured under different illumination conditions, thus making our robust face matching algorithm. Experimental +<br/>results of applying the proposed face image matching algorithm on some well-known face datasets are given in comparison with +<br/>some existing face recognition methods. The results show that the proposed algorithm consistently outperforms other methods +<br/>and achieves higher than 93% recognition rate with three reference images for different datasets under different lighting condi- +<br/>tions. +<br/>Keywords and phrases: robust image matching, face recognition, illumination variations, normalized gradient. +<br/>INTRODUCTION +<br/>1. +<br/>Face recognition has attracted the attention of a number +<br/>of researchers from academia and industry because of its +<br/>challenges and related applications, such as security access +<br/>control, personal ID verification, e-commerce, video surveil- +<br/>lance, and so forth. The details of these applications are re- +<br/>ferred to in the surveys [1, 2, 3]. Face matching is the most +<br/>important and crucial component in face recognition. Al- +<br/>though there have been many efforts in previous works to +<br/>achieve robust face matching under a wide variety of dif- +<br/>ferent image capturing conditions, such as lighting changes, +<br/>head pose or view angle variations, expression variations, +<br/>and so forth, these problems are still difficult to overcome. +<br/>It is a great challenge to achieve robust face matching under +<br/>all kinds of different face imaging variations. A practical face +<br/>recognition system needs to work under different imaging +<br/>conditions, such as different face poses, or different illumi- +<br/>nation conditions. Therefore, a robust face matching method +<br/>is essential to the development of an illumination-insensitive +<br/>face recognition system. In this paper, we particularly focus +<br/>on robust face matching under different illumination condi- +<br/>tions. +<br/>Many researchers have proposed face recognition meth- +<br/>ods or face verification systems under different illumination +<br/>conditions. Some of these methods extracted representative +<br/>features from face images to compute the distance between +<br/>these features. In general, these methods can be categorized +<br/>into the feature-based approach [4, 5, 6, 7, 8, 9, 10, 11], the +<br/>appearance-based approach [12, 13, 14, 15, 16, 17, 18, 19, 20, +<br/>21, 22, 23], and the hybrid approach [22, 24]. +</td><td>('2393568', 'Chyuan-Huei Thomas Yang', 'chyuan-huei thomas yang')<br/>('1696527', 'Shang-Hong Lai', 'shang-hong lai')<br/>('39505245', 'Long-Wen Chang', 'long-wen chang')</td><td>Email: chyang@cs.nthu.edu.tw +<br/>Email: lai@cs.nthu.edu.tw +<br/>Email: lchang@cs.nthu.edu.tw +</td></tr><tr><td>bf54b5586cdb0b32f6eed35798ff91592b03fbc4</td><td>Journal of Signal and Information Processing, 2017, 8, 78-98 +<br/>http://www.scirp.org/journal/jsip +<br/>ISSN Online: 2159-4481 +<br/>ISSN Print: 2159-4465 +<br/>Methodical Analysis of Western-Caucasian and +<br/>East-Asian Basic Facial Expressions of Emotions +<br/>Based on Specific Facial Regions +<br/><b>The University of Electro-Communications, Tokyo, Japan</b><br/>How to cite this paper: Benitez-Garcia, G., +<br/>Nakamura, T. and Kaneko, M. (2017) Me- +<br/>thodical Analysis of Western-Caucasian and +<br/>East-Asian Basic Facial Expressions of Emo- +<br/>tions Based on Specific Facial Regions. Jour- +<br/>nal of Signal and Information Processing, 8, +<br/>78-98. +<br/>https://doi.org/10.4236/jsip.2017.82006 +<br/>Received: March 30, 2017 +<br/>Accepted: May 15, 2017 +<br/>Published: May 18, 2017 +<br/>Copyright © 2017 by authors and +<br/>Scientific Research Publishing Inc. +<br/>This work is licensed under the Creative +<br/>Commons Attribution International +<br/>License (CC BY 4.0). +<br/>http://creativecommons.org/licenses/by/4.0/ +<br/> +<br/>Open Access +</td><td>('2567776', 'Gibran Benitez-Garcia', 'gibran benitez-garcia')<br/>('1693821', 'Tomoaki Nakamura', 'tomoaki nakamura')<br/>('49061848', 'Masahide Kaneko', 'masahide kaneko')</td><td></td></tr><tr><td>bf1e0279a13903e1d43f8562aaf41444afca4fdc</td><td> International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 <br/> Volume: 04 Issue: 10 | Oct -2017 www.irjet.net p-ISSN: 2395-0072 <br/>Different Viewpoints of Recognizing Fleeting Facial Expressions with <br/>DWT @@ -26122,7 +32503,11 @@ <br/>maziyang08@gmail.com <br/>dcszj@mail.tsinghua.edu.cn <br/>leojia@cse.cuhk.edu.hk -</td></tr><tr><td>bfb98423941e51e3cd067cb085ebfa3087f3bfbe</td><td>Sparseness helps: Sparsity Augmented +</td></tr><tr><td>bf5940d57f97ed20c50278a81e901ae4656f0f2c</td><td>Query-free Clothing Retrieval via Implicit +<br/>Relevance Feedback +</td><td>('26331884', 'Zhuoxiang Chen', 'zhuoxiang chen')<br/>('1691461', 'Zhe Xu', 'zhe xu')<br/>('48380192', 'Ya Zhang', 'ya zhang')<br/>('48531192', 'Xiao Gu', 'xiao gu')</td><td></td></tr><tr><td>bff567c58db554858c7f39870cff7c306523dfee</td><td>Neural Task Graphs: Generalizing to Unseen +<br/>Tasks from a Single Video Demonstration +<br/><b>Stanford University</b></td><td>('38485317', 'De-An Huang', 'de-an huang')<br/>('4734949', 'Suraj Nair', 'suraj nair')<br/>('2068265', 'Danfei Xu', 'danfei xu')<br/>('2117748', 'Yuke Zhu', 'yuke zhu')<br/>('1873736', 'Animesh Garg', 'animesh garg')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')<br/>('1702137', 'Silvio Savarese', 'silvio savarese')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')</td><td></td></tr><tr><td>bfb98423941e51e3cd067cb085ebfa3087f3bfbe</td><td>Sparseness helps: Sparsity Augmented <br/>Collaborative Representation for Classification </td><td>('2941543', 'Naveed Akhtar', 'naveed akhtar')<br/>('1688013', 'Faisal Shafait', 'faisal shafait')</td><td></td></tr><tr><td>bffbd04ee5c837cd919b946fecf01897b2d2d432</td><td><b>Boston University Computer Science Technical Report No</b><br/>Facial Feature Tracking and Occlusion <br/>Recovery in American Sign Language @@ -26153,7 +32538,24 @@ <br/>1 The word “Deaf” is capitalized to designate those individuals who are linguisti- <br/>cally and culturally deaf and who use ASL as their primary language, whereas <br/>“deaf” refers to the status of those who cannot hear [25]. -</td><td>('2313369', 'Thomas J. Castelli', 'thomas j. castelli')<br/>('1723703', 'Margrit Betke', 'margrit betke')<br/>('1732359', 'Carol Neidle', 'carol neidle')</td><td></td></tr><tr><td>d3424761e06a8f5f3c1f042f1f1163a469872129</td><td>Pose-invariant, model-based object +</td><td>('2313369', 'Thomas J. Castelli', 'thomas j. castelli')<br/>('1723703', 'Margrit Betke', 'margrit betke')<br/>('1732359', 'Carol Neidle', 'carol neidle')</td><td></td></tr><tr><td>d35534f3f59631951011539da2fe83f2844ca245</td><td>Published as a conference paper at ICLR 2018 +<br/>SEMANTICALLY DECOMPOSING THE LATENT SPACES +<br/>OF GENERATIVE ADVERSARIAL NETWORKS +<br/>Department of Music +<br/><b>University of California, San Diego</b><br/>Department of Genetics +<br/><b>Stanford University</b><br/>Zachary C. Lipton +<br/><b>Carnegie Mellon University</b><br/>Amazon AI +<br/>Department of Computer Science +<br/><b>University of California, San Diego</b></td><td>('1872307', 'Chris Donahue', 'chris donahue')<br/>('1693411', 'Akshay Balsubramani', 'akshay balsubramani')<br/>('1814008', 'Julian McAuley', 'julian mcauley')</td><td>cdonahue@ucsd.edu +<br/>abalsubr@stanford.edu +<br/>zlipton@cmu.edu +<br/>jmcauley@eng.ucsd.edu +</td></tr><tr><td>d3edbfe18610ce63f83db83f7fbc7634dde1eb40</td><td>Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) +<br/>Large Graph Hashing with Spectral Rotation +<br/>School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), +<br/><b>Northwestern Polytechnical University</b><br/>Xi’an 710072, Shaanxi, P. R. China +</td><td>('1720243', 'Xuelong Li', 'xuelong li')<br/>('48080389', 'Di Hu', 'di hu')<br/>('1688370', 'Feiping Nie', 'feiping nie')</td><td>xuelong li@opt.ac.cn, hdui831@mail.nwpu.edu.cn, feipingnie@gmail.com +</td></tr><tr><td>d3424761e06a8f5f3c1f042f1f1163a469872129</td><td>Pose-invariant, model-based object <br/>recognition, using linear combination of views <br/>and Bayesian statistics. <br/>A dissertation submitted in partial fulfillment @@ -26178,6 +32580,14 @@ <br/>2Universiti Sains Malaysia, Malaysia, heikal@usm.my <br/>3Universiti Sains Malaysia, Malaysia, zarulfitri@usm.my <br/>4Universiti Sains Malaysia, Malaysia, azam@usm.my +</td></tr><tr><td>d3d5d86afec84c0713ec868cf5ed41661fc96edc</td><td>A Comprehensive Analysis of Deep Learning Based Representation +<br/>for Face Recognition +<br/>Mostafa Mehdipour Ghazi +<br/>Faculty of Engineering and Natural Sciences +<br/><b>Sabanci University, Istanbul, Turkey</b><br/>Hazım Kemal Ekenel +<br/>Department of Computer Engineering +<br/><b>Istanbul Technical University, Istanbul, Turkey</b></td><td></td><td>mehdipour@sabanciuniv.edu +<br/>ekenel@itu.edu.tr </td></tr><tr><td>d3e04963ff42284c721f2bc6a90b7a9e20f0242f</td><td>On Forensic Use of Biometrics <br/><b>University of Southampton, UK, 2University of Warwick, UK</b><br/>This chapter discusses the use of biometrics techniques within forensic science. It outlines the <br/>historic connections between the subjects and then examines face and ear biometrics as two @@ -26219,24 +32629,133 @@ <br/>Faculty of Engineering and Physical Sciences <br/><b>University of Surrey</b><br/>Guildford, Surrey GU2 7XH, U.K. <br/>August 2016 -</td><td>('39222045', 'Charles Gray', 'charles gray')<br/>('39222045', 'Charles Gray', 'charles gray')</td><td></td></tr><tr><td>d394bd9fbaad1f421df8a49347d4b3fca307db83</td><td>Recognizing Facial Expressions at Low Resolution +</td><td>('39222045', 'Charles Gray', 'charles gray')<br/>('39222045', 'Charles Gray', 'charles gray')</td><td></td></tr><tr><td>d3b18ba0d9b247bfa2fb95543d172ef888dfff95</td><td>Learning and Using the Arrow of Time +<br/><b>Harvard University 2University of Southern California</b><br/><b>University of Oxford 4Massachusetts Institute of Technology 5Google Research</b><br/>(a) +<br/>(c) +<br/>(b) +<br/>(d) +<br/>Figure 1: Seeing these ordered frames from videos, can you tell whether each video is playing forward or backward? (answer +<br/>below1). Depending on the video, solving the task may require (a) low-level understanding (e.g. physics), (b) high-level +<br/>reasoning (e.g. semantics), or (c) familiarity with very subtle effects or with (d) camera conventions. In this work, we learn +<br/>and exploit several types of knowledge to predict the arrow of time automatically with neural network models trained on +<br/>large-scale video datasets. +</td><td>('1766333', 'Donglai Wei', 'donglai wei')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')<br/>('1768236', 'William T. Freeman', 'william t. freeman')</td><td>donglai@seas.harvard.edu, limjj@usc.edu, az@robots.ox.ac.uk, billf@mit.edu +</td></tr><tr><td>d309e414f0d6e56e7ba45736d28ee58ae2bad478</td><td>Efficient Two-Stream Motion and Appearance 3D CNNs for +<br/>Video Classification +<br/>Ali Diba +<br/>ESAT-KU Leuven +<br/>Ali Pazandeh +<br/>Sharif UTech +<br/>Luc Van Gool +<br/>ESAT-KU Leuven, ETH Zurich +</td><td></td><td>ali.diba@esat.kuleuven.be +<br/>pazandeh@ee.sharif.ir +<br/>luc.vangool@esat.kuleuven.be +</td></tr><tr><td>d394bd9fbaad1f421df8a49347d4b3fca307db83</td><td>Recognizing Facial Expressions at Low Resolution <br/><b>Deparment of Computer Science, Queen Mary, University of London, London, E1 4NS, UK</b></td><td>('10795229', 'Caifeng Shan', 'caifeng shan')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('2803283', 'Peter W. McOwan', 'peter w. mcowan')</td><td>{cfshan, sgg, pmco}@dcs.qmul.ac.uk -</td></tr><tr><td>d3b550e587379c481392fb07f2cbbe11728cf7a6</td><td>Small Sample Size Face Recognition using Random Quad-Tree based +</td></tr><tr><td>d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9</td><td></td><td></td><td></td></tr><tr><td>d3b550e587379c481392fb07f2cbbe11728cf7a6</td><td>Small Sample Size Face Recognition using Random Quad-Tree based <br/>Ensemble Algorithm <br/><b>Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan</b></td><td>('7923772', 'Cuicui Zhang', 'cuicui zhang')<br/>('2735528', 'Xuefeng Liang', 'xuefeng liang')<br/>('1731351', 'Takashi Matsuyama', 'takashi matsuyama')</td><td>zhang@vision.kuee.kyoto-u.ac.jp, fxliang, tmg@i.kyoto-u.ac.jp -</td></tr><tr><td>d30050cfd16b29e43ed2024ae74787ac0bbcf2f7</td><td>Facial Expression Classification Using +</td></tr><tr><td>d307a766cc9c728a24422313d4c3dcfdb0d16dd5</td><td>Deep Keyframe Detection in Human Action Videos +<br/><b>School of Physics and Optoelectronic Engineering, Xidian University, China</b><br/><b>School of Computer Science and Software Engineering, University of Western Australia</b><br/><b>College of Electrical and Information Engineering, Hunan University, China</b><br/><b>School of Software, Xidian University, China</b></td><td>('46580760', 'Xiang Yan', 'xiang yan')<br/>('1746166', 'Syed Zulqarnain Gilani', 'syed zulqarnain gilani')<br/>('2404621', 'Hanlin Qin', 'hanlin qin')<br/>('3446916', 'Mingtao Feng', 'mingtao feng')<br/>('48570713', 'Liang Zhang', 'liang zhang')<br/>('46332747', 'Ajmal Mian', 'ajmal mian')</td><td>xyan@stu.xidian.edu.cn, hlqin@mail.xidian.edu.cn +<br/>{zulqarnain.gilani, ajmal.mian}@uwa.edu.au +<br/>mintfeng@hnu.edu.cn +<br/>liangzhang@xidian.edu.cn +</td></tr><tr><td>d31af74425719a3840b496b7932e0887b35e9e0d</td><td>Article +<br/>A Multimodal Deep Log-Based User Experience (UX) +<br/>Platform for UX Evaluation +<br/><b>Ubiquitous Computing Lab, Kyung Hee University</b><br/><b>College of Electronics and Information Engineering, Sejong University</b><br/>Received: 16 March 2018; Accepted: 15 May 2018; Published: 18 May 2018 +</td><td>('33081617', 'Jamil Hussain', 'jamil hussain')<br/>('2794241', 'Wajahat Ali Khan', 'wajahat ali khan')<br/>('27531310', 'Anees Ul Hassan', 'anees ul hassan')<br/>('1765947', 'Muhammad Afzal', 'muhammad afzal')<br/>('1700806', 'Sungyoung Lee', 'sungyoung lee')</td><td>Giheung-gu, Yongin-si, Gyeonggi-do, Seoul 446-701, Korea; jamil@oslab.khu.ac.kr (J.H.); +<br/>wajahat.alikhan@oslab.khu.ac.kr (W.A.K.); hth@oslab.khu.ac.kr (T.H.); bilalrizvi@oslab.khu.ac.kr (H.S.M.B.); +<br/>jhb@oslab.khu.ac.kr (J.B.); anees@oslab.khu.ac.kr (A.U.H.) +<br/>Seoul 05006, Korea; mafzal@sejong.ac.kr +<br/>* Correspondence: sylee@oslab.khu.ac.kr; Tel.: +82-31-201-2514 +</td></tr><tr><td>d3b0839324d0091e70ce34f44c979b9366547327</td><td>Precise Box Score: Extract More Information from Datasets to Improve the +<br/>Performance of Face Detection +<br/>1School of Information and Communication Engineering +<br/>2Beijing Key Laboratory of Network System and Network Culture +<br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>('49712251', 'Ce Qi', 'ce qi')<br/>('1684263', 'Fei Su', 'fei su')<br/>('8120542', 'Pingyu Wang', 'pingyu wang')</td><td></td></tr><tr><td>d30050cfd16b29e43ed2024ae74787ac0bbcf2f7</td><td>Facial Expression Classification Using <br/>Convolutional Neural Network and Support Vector <br/>Machine <br/>Graduate Program in Electrical and Computer Engineering <br/><b>Federal University of Technology - Paran a</b><br/>Department of Electrical and Computer Engineering <br/><b>Opus College of Engineering</b><br/><b>Marquette University</b></td><td>('11857183', 'Cristian Bortolini', 'cristian bortolini')<br/>('2357308', 'Humberto R. Gamba', 'humberto r. gamba')<br/>('2432946', 'Gustavo Benvenutti Borba', 'gustavo benvenutti borba')<br/>('2767912', 'Henry Medeiros', 'henry medeiros')</td><td>Email: vpillajr@mail.com -</td></tr><tr><td>d3c004125c71942846a9b32ae565c5216c068d1e</td><td>RESEARCH ARTICLE +</td></tr><tr><td>d3faed04712b4634b47e1de0340070653546deb2</td><td>Neural Best-Buddies: Sparse Cross-Domain Correspondence +<br/>Fig. 1. Top 5 Neural Best-Buddies for two cross-domain image pairs. Using deep features of a pre-trained neural network, our coarse-to-fine sparse +<br/>correspondence algorithm first finds high-level, low resolution, semantically matching areas (indicated by the large blue circles), then narrows down the search +<br/>area to intermediate levels (middle green circles), until precise localization on well-defined edges in the pixel space (colored in corresponding unique colors). +<br/>Correspondence between images is a fundamental problem in computer +<br/>vision, with a variety of graphics applications. This paper presents a novel +<br/>method for sparse cross-domain correspondence. Our method is designed for +<br/>pairs of images where the main objects of interest may belong to different +<br/>semantic categories and differ drastically in shape and appearance, yet still +<br/>contain semantically related or geometrically similar parts. Our approach +<br/>operates on hierarchies of deep features, extracted from the input images +<br/>by a pre-trained CNN. Specifically, starting from the coarsest layer in both +<br/>hierarchies, we search for Neural Best Buddies (NBB): pairs of neurons +<br/>that are mutual nearest neighbors. The key idea is then to percolate NBBs +<br/>through the hierarchy, while narrowing down the search regions at each +<br/>level and retaining only NBBs with significant activations. Furthermore, in +<br/>order to overcome differences in appearance, each pair of search regions is +<br/>transformed into a common appearance. +<br/>We evaluate our method via a user study, in addition to comparisons +<br/>with alternative correspondence approaches. The usefulness of our method +<br/><b>is demonstrated using a variety of graphics applications, including cross</b><br/>domain image alignment, creation of hybrid images, automatic image mor- +<br/>phing, and more. +<br/>CCS Concepts: • Computing methodologies → Interest point and salient +<br/>region detections; Matching; Image manipulation; +<br/><b>University</b><br/>© 2018 Association for Computing Machinery. +<br/>This is the author’s version of the work. It is posted here for your personal use. Not for +<br/>redistribution. The definitive Version of Record was published in ACM Transactions on +<br/>Graphics, https://doi.org/10.1145/3197517.3201332. +<br/>Additional Key Words and Phrases: cross-domain correspondence, image +<br/>hybrids, image morphing +<br/>ACM Reference Format: +<br/>Cohen-Or. 2018. Neural Best-Buddies: Sparse Cross-Domain Correspon- +<br/>//doi.org/10.1145/3197517.3201332 +<br/>INTRODUCTION +<br/>Finding correspondences between a pair of images has been a long +<br/>standing problem, with a multitude of applications in computer +<br/>vision and graphics. In particular, sparse sets of corresponding point +<br/>pairs may be used for tasks such as template matching, image align- +<br/>ment, and image morphing, to name a few. Over the years, a variety +<br/>of dense and sparse correspondence methods have been developed, +<br/>most of which assume that the input images depict the same scene +<br/>or object (with differences in viewpoint, lighting, object pose, etc.), +<br/>or a pair of objects from the same class. +<br/>In this work, we are concerned with sparse cross-domain corre- +<br/>spondence: a more general and challenging version of the sparse +<br/>correspondence problem, where the object of interest in the two +<br/>input images can differ more drastically in their shape and appear- +<br/>ance, such as objects belonging to different semantic categories +<br/>(domains). It is, however, assumed that the objects contain at least +<br/>some semantically related parts or geometrically similar regions, oth- +<br/>erwise the correspondence task cannot be considered well-defined. +<br/>Two examples of cross-domain scenarios and the results of our ap- +<br/>proach are shown in Figure 1. We focus on sparse correspondence, +<br/>since in many cross-domain image pairs, dense correspondence +<br/>ACM Transactions on Graphics, Vol. 37, No. 4, Article 69. Publication date: August 2018. +</td><td>('3451442', 'Kfir Aberman', 'kfir aberman')<br/>('39768043', 'Jing Liao', 'jing liao')<br/>('5807605', 'Mingyi Shi', 'mingyi shi')<br/>('1684384', 'Dani Lischinski', 'dani lischinski')<br/>('1748939', 'Baoquan Chen', 'baoquan chen')<br/>('1701009', 'Daniel Cohen-Or', 'daniel cohen-or')<br/>('3451442', 'Kfir Aberman', 'kfir aberman')<br/>('39768043', 'Jing Liao', 'jing liao')<br/>('5807605', 'Mingyi Shi', 'mingyi shi')<br/>('1684384', 'Dani Lischinski', 'dani lischinski')<br/>('1748939', 'Baoquan Chen', 'baoquan chen')<br/>('1701009', 'Daniel Cohen-Or', 'daniel cohen-or')<br/>('3451442', 'Kfir Aberman', 'kfir aberman')<br/>('39768043', 'Jing Liao', 'jing liao')<br/>('5807605', 'Mingyi Shi', 'mingyi shi')<br/>('1684384', 'Dani Lischinski', 'dani lischinski')<br/>('1748939', 'Baoquan Chen', 'baoquan chen')</td><td></td></tr><tr><td>d3c004125c71942846a9b32ae565c5216c068d1e</td><td>RESEARCH ARTICLE <br/>Recognizing Age-Separated Face Images: <br/>Humans and Machines <br/><b>West Virginia University, Morgantown, West Virginia, United States of America, 2. IIIT Delhi, New Delhi</b><br/>Delhi, India </td><td>('3017294', 'Daksha Yadav', 'daksha yadav')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('2487227', 'Afzel Noore', 'afzel noore')</td><td>*mayank@iiitd.ac.in </td></tr><tr><td>d350a9390f0818703f886138da27bf8967fe8f51</td><td>LIGHTING DESIGN FOR PORTRAITS WITH A VIRTUAL LIGHT STAGE -<br/><b>Institute for Vision and Graphics, University of Siegen, Germany</b></td><td>('1967283', 'Davoud Shahlaei', 'davoud shahlaei')<br/>('2712313', 'Marcel Piotraschke', 'marcel piotraschke')<br/>('2880906', 'Volker Blanz', 'volker blanz')</td><td></td></tr><tr><td>d41c11ebcb06c82b7055e2964914b9af417abfb2</td><td>CDI-Type I: Unsupervised and Weakly-Supervised +<br/><b>Institute for Vision and Graphics, University of Siegen, Germany</b></td><td>('1967283', 'Davoud Shahlaei', 'davoud shahlaei')<br/>('2712313', 'Marcel Piotraschke', 'marcel piotraschke')<br/>('2880906', 'Volker Blanz', 'volker blanz')</td><td></td></tr><tr><td>d33fcdaf2c0bd0100ec94b2c437dccdacec66476</td><td>Neurons with Paraboloid Decision Boundaries for +<br/>Improved Neural Network Classification +<br/>Performance +</td><td>('2320550', 'Nikolaos Tsapanos', 'nikolaos tsapanos')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td></td></tr><tr><td>d4a5eaf2e9f2fd3e264940039e2cbbf08880a090</td><td>An Occluded Stacked Hourglass Approach to Facial +<br/>Landmark Localization and Occlusion Estimation +<br/><b>University of California San Diego</b></td><td>('2812409', 'Kevan Yuen', 'kevan yuen')</td><td>kcyuen@eng.ucsd.edu, mtrivedi@eng.ucsd.edu +</td></tr><tr><td>d46b790d22cb59df87f9486da28386b0f99339d3</td><td>Learning Face Deblurring Fast and Wide +<br/><b>University of Bern</b><br/>Switzerland +<br/>Amazon Research +<br/>Germany +<br/><b>University of Bern</b><br/>Switzerland +</td><td>('39866194', 'Meiguang Jin', 'meiguang jin')<br/>('36266446', 'Michael Hirsch', 'michael hirsch')<br/>('1739080', 'Paolo Favaro', 'paolo favaro')</td><td>jin@inf.unibe.ch +<br/>hirsch@amazon.com +<br/>favaro@inf.unibe.ch +</td></tr><tr><td>d41c11ebcb06c82b7055e2964914b9af417abfb2</td><td>CDI-Type I: Unsupervised and Weakly-Supervised <br/>1 Introduction <br/>Discovery of Facial Events <br/>The face is one of the most powerful channels of nonverbal communication. Facial expression has been a @@ -26276,14 +32795,29 @@ <br/>2) At present, taxonomies of facial expression are based on FACS or other observer-based schemes. <br/>Consequently, approaches to automatic facial expression recognition are dependent on access to cor- <br/>puses of FACS or similarly labeled video. In the proposed work we raise the question of whether -</td><td></td><td></td></tr><tr><td>d46fda4b49bbc219e37ef6191053d4327e66c74b</td><td>Facial Expression Recognition Based on Complexity Perception Classification +</td><td></td><td></td></tr><tr><td>d444e010049944c1b3438c9a25ae09b292b17371</td><td>Structure Preserving Video Prediction +<br/><b>Shanghai Institute for Advanced Communication and Data Science</b><br/>Shanghai Key Laboratory of Digital Media Processing and Transmission +<br/><b>Shanghai Jiao Tong University, Shanghai 200240, China</b></td><td>('47882735', 'Jingwei Xu', 'jingwei xu')<br/>('47889348', 'Shuo Cheng', 'shuo cheng')</td><td>{xjwxjw,nibingbing,Leezf,xkyang}@sjtu.edu.cn, acccheng94@gmail.com +</td></tr><tr><td>d46fda4b49bbc219e37ef6191053d4327e66c74b</td><td>Facial Expression Recognition Based on Complexity Perception Classification <br/>Algorithm <br/><b>School of Computer Science and Engineering, South China University of Technology, Guangzhou, China</b></td><td>('36047279', 'Tianyuan Chang', 'tianyuan chang')<br/>('9725901', 'Guihua Wen', 'guihua wen')<br/>('39946628', 'Yang Hu', 'yang hu')<br/>('35847383', 'JiaJiong Ma', 'jiajiong ma')</td><td>tianyuan_chang@163.com, crghwen@scut.edu.cn </td></tr><tr><td>d448d67c6371f9abf533ea0f894ef2f022b12503</td><td>Weakly Supervised Collective Feature Learning from Curated Media <br/>1. NTT Communication Science Laboratories, Japan. <br/><b>University of Cambridge, United Kingdom</b><br/><b>The University of Tokyo, Japan</b><br/><b>Technical University of Munich, Germany</b><br/>5. Uber AI Labs, USA. </td><td>('2374364', 'Yusuke Mukuta', 'yusuke mukuta')<br/>('34454585', 'Akisato Kimura', 'akisato kimura')<br/>('2584289', 'David B. Adrian', 'david b. adrian')<br/>('1983575', 'Zoubin Ghahramani', 'zoubin ghahramani')</td><td>mukuta@mi.t.u-tokyo.ac.jp, akisato@ieee.org, david.adrian@tum.de, zoubin@eng.cam.ac.uk -</td></tr><tr><td>d4c7d1a7a03adb2338704d2be7467495f2eb6c7b</td><td></td><td></td><td></td></tr><tr><td>d4001826cc6171c821281e2771af3a36dd01ffc0</td><td>Modélisation de contextes pour l’annotation sémantique +</td></tr><tr><td>d492dbfaa42b4f8b8a74786d7343b3be6a3e9a1d</td><td>Deep Cost-Sensitive and Order-Preserving Feature Learning for +<br/>Cross-Population Age Estimation +<br/><b>National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences</b><br/><b>University of Chinese Academy of Sciences</b><br/>3 KingSoft Ltd. +<br/>4 CAS Center for Excellence in Brain Science and Intelligence Technology +<br/>5 Vimicro AI Chip Technology Corporation +<br/><b>Birkbeck University of London</b></td><td>('2168945', 'Kai Li', 'kai li')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('49734675', 'Chi Su', 'chi su')<br/>('40506509', 'Weiming Hu', 'weiming hu')<br/>('2373307', 'Yundong Zhang', 'yundong zhang')</td><td>{kai.li,jlxing,wmhu}@nlpr.ia.ac.cn suchi@kingsoft.com raymond@vimicro.com sjmaybank@dcs.bbk.ac.uk +</td></tr><tr><td>d444368421f456baf8c3cb089244e017f8d32c41</td><td>CNN for IMU Assisted Odometry Estimation using Velodyne LiDAR +</td><td>('3414588', 'Martin Velas', 'martin velas')<br/>('2131298', 'Michal Spanel', 'michal spanel')<br/>('1700956', 'Michal Hradis', 'michal hradis')<br/>('1785162', 'Adam Herout', 'adam herout')</td><td></td></tr><tr><td>d4885ca24189b4414031ca048a8b7eb2c9ac646c</td><td>Efficient Facial Representations for Age, Gender +<br/>and Identity Recognition in Organizing Photo +<br/>Albums using Multi-output CNN +<br/><b>Samsung-PDMI Joint AI Center</b><br/>Mathematics +<br/><b>National Research University Higher School of Economics</b><br/>Nizhny Novgorod, Russia +</td><td>('35153729', 'Andrey V. Savchenko', 'andrey v. savchenko')</td><td></td></tr><tr><td>d4c7d1a7a03adb2338704d2be7467495f2eb6c7b</td><td></td><td></td><td></td></tr><tr><td>d4001826cc6171c821281e2771af3a36dd01ffc0</td><td>Modélisation de contextes pour l’annotation sémantique <br/>de vidéos <br/>To cite this version: <br/>Ecole Nationale Supérieure des Mines de Paris, 2013. Français. <NNT : 2013ENMP0051>. <pastel- @@ -26306,18 +32840,31 @@ <br/>under Varying Illumination <br/><b>Mahanakorn University of Technology</b><br/>51 Cheum-Sampan Rd., Nong Chok, Bangkok, THAILAND 10530 </td><td>('1805935', 'Sanun Srisuk', 'sanun srisuk')<br/>('2337544', 'Amnart Petpon', 'amnart petpon')</td><td>sanun@mut.ac.th, amnartpe@dtac.co.th +</td></tr><tr><td>d458c49a5e34263c95b3393386b5d76ba770e497</td><td>Middle-East Journal of Scientific Research 20 (1): 01-13, 2014 +<br/>ISSN 1990-9233 +<br/>© IDOSI Publications, 2014 +<br/>DOI: 10.5829/idosi.mejsr.2014.20.01.11434 +<br/>A Comparative Analysis of Gender Classification Techniques +<br/><b>Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad, Pakistan</b></td><td>('46883468', 'Sajid Ali Khan', 'sajid ali khan')<br/>('48767110', 'Maqsood Ahmad', 'maqsood ahmad')<br/>('2521631', 'Naveed Riaz', 'naveed riaz')</td><td></td></tr><tr><td>d454ad60b061c1a1450810a0f335fafbfeceeccc</td><td>Deep Regression Forests for Age Estimation +<br/>1 Key Laboratory of Specialty Fiber Optics and Optical Access Networks, +<br/><b>Shanghai Institute for Advanced Communication and Data Science</b><br/><b>School of Communication and Information Engineering, Shanghai University</b><br/><b>Johns Hopkins University</b><br/><b>College of Computer and Control Engineering, Nankai University 4 Hikvision Research</b></td><td>('41187410', 'Wei Shen', 'wei shen')<br/>('9544564', 'Yilu Guo', 'yilu guo')<br/>('47906413', 'Yan Wang', 'yan wang')<br/>('1681247', 'Kai Zhao', 'kai zhao')<br/>('49292319', 'Bo Wang', 'bo wang')</td><td>{shenwei1231,gyl.luan0,wyanny.9,zhaok1206,wangbo.yunze,alan.l.yuille}@gmail.com </td></tr><tr><td>d40cd10f0f3e64fd9b0c2728089e10e72bea9616</td><td>Article <br/>Enhancing Face Identification Using Local Binary <br/>Patterns and K-Nearest Neighbors <br/><b>School of Communication Engineering, Hangzhou Dianzi University, Xiasha Higher Education Zone</b><br/>Received: 21 March 2017; Accepted: 29 August 2017; Published: 5 September 2017 </td><td>('11249315', 'Idelette Laure Kambi Beli', 'idelette laure kambi beli')<br/>('2826297', 'Chunsheng Guo', 'chunsheng guo')</td><td>Hangzhou 310018, China; guo.chsh@gmail.com <br/>* Correspondence: kblaure@yahoo.fr -</td></tr><tr><td>d4ebf0a4f48275ecd8dbc2840b2a31cc07bd676d</td><td></td><td></td><td></td></tr><tr><td>d46e793b945c4f391031656357625e902c4405e8</td><td>Face-off: Automatic Alteration of Facial Features +</td></tr><tr><td>d4ebf0a4f48275ecd8dbc2840b2a31cc07bd676d</td><td></td><td></td><td></td></tr><tr><td>d4e669d5d35fa0ca9f8d9a193c82d4153f5ffc4e</td><td>A Lightened CNN for Deep Face Representation +<br/>School of Computer and Communication Engineering +<br/><b>University of Science and Technology Beijing, Beijing, China</b><br/>National Laboratory of Pattern Recognition +<br/><b>Institute of Automation Chinese Academy of Sciences, Beijing, China</b></td><td>('2225749', 'Xiang Wu', 'xiang wu')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>aflredxiangwu@gmail.com +<br/>{rhe, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>d46e793b945c4f391031656357625e902c4405e8</td><td>Face-off: Automatic Alteration of Facial Features <br/>Department of Information Management <br/><b>National Taiwan University of Science and Technology</b><br/>No. 43, Sec. 4, Keelung Road <br/>Taipei, 106, Taiwan, ROC </td><td>('40119465', 'Jia-Kai Chou', 'jia-kai chou')<br/>('2241272', 'Chuan-Kai Yang', 'chuan-kai yang')<br/>('2553196', 'Sing-Dong Gong', 'sing-dong gong')</td><td>A9409004@mail.ntust.edu.tw,ckyang@cs.ntust.edu.tw,hgznrn@uj.com.tw -</td></tr><tr><td>d4c2d26523f577e2d72fc80109e2540c887255c8</td><td>Face-space Action Recognition by Face-Object Interactions +</td></tr><tr><td>d44a93027208816b9e871101693b05adab576d89</td><td></td><td></td><td></td></tr><tr><td>d4c2d26523f577e2d72fc80109e2540c887255c8</td><td>Face-space Action Recognition by Face-Object Interactions <br/><b>Weizmann Institute of Science</b><br/>Rehovot, 7610001, Israel </td><td>('32928116', 'Amir Rosenfeld', 'amir rosenfeld')<br/>('1743045', 'Shimon Ullman', 'shimon ullman')</td><td>{amir.rosenfeld,shimon.ullman}@weizmann.ac.il </td></tr><tr><td>d4b88be6ce77164f5eea1ed2b16b985c0670463a</td><td>TECHNICAL REPORT JAN.15.2016 @@ -26364,7 +32911,14 @@ </td><td>('1939861', 'Jorge A. Vanegas', 'jorge a. vanegas')</td><td>fmpaezri@unal.edu.co <br/>javanegasr@unal.edu.co <br/>fagonzalezo@unal.edu.co -</td></tr><tr><td>badcfb7d4e2ef0d3e332a19a3f93d59b4f85668e</td><td>The Application of Extended Geodesic Distance +</td></tr><tr><td>badcd992266c6813063c153c41b87babc0ba36a3</td><td>Recent Advances in Object Detection in the Age +<br/>of Deep Convolutional Neural Networks +<br/>,1,2), Fr´ed´eric Jurie(1) +<br/>(∗) equal contribution +<br/>(1)Normandie Univ, UNICAEN, ENSICAEN, CNRS +<br/>(2)Safran Electronics and Defense +<br/>September 11, 2018 +</td><td>('51443250', 'Shivang Agarwal', 'shivang agarwal')<br/>('35527701', 'Jean Ogier Du Terrail', 'jean ogier du terrail')</td><td></td></tr><tr><td>ba788365d70fa6c907b71a01d846532ba3110e31</td><td></td><td></td><td></td></tr><tr><td>badcfb7d4e2ef0d3e332a19a3f93d59b4f85668e</td><td>The Application of Extended Geodesic Distance <br/>in Head Poses Estimation <br/><b>Institute of Computing Technology</b><br/>Chinese Academy of Sciences, Beijing 100080, China <br/>2 Department of Computer Science and Engineering, @@ -26454,14 +33008,62 @@ <br/>Concepts in Videos <br/>Larry Davis1 <br/><b>University of Maryland, College Park; 2Arizona State University; 3Xerox Research Centre</b><br/>India -</td><td>('36861219', 'Sohil Shah', 'sohil shah')<br/>('40222634', 'Kuldeep Kulkarni', 'kuldeep kulkarni')<br/>('2221075', 'Arijit Biswas', 'arijit biswas')<br/>('2757149', 'Ankit Gandhi', 'ankit gandhi')<br/>('2116262', 'Om Deshmukh', 'om deshmukh')</td><td></td></tr><tr><td>ba29ba8ec180690fca702ad5d516c3e43a7f0bb8</td><td></td><td></td><td></td></tr><tr><td>bab88235a30e179a6804f506004468aa8c28ce4f</td><td></td><td></td><td></td></tr><tr><td>a065080353d18809b2597246bb0b48316234c29a</td><td>FHEDN: A based on context modeling Feature Hierarchy +</td><td>('36861219', 'Sohil Shah', 'sohil shah')<br/>('40222634', 'Kuldeep Kulkarni', 'kuldeep kulkarni')<br/>('2221075', 'Arijit Biswas', 'arijit biswas')<br/>('2757149', 'Ankit Gandhi', 'ankit gandhi')<br/>('2116262', 'Om Deshmukh', 'om deshmukh')</td><td></td></tr><tr><td>ba29ba8ec180690fca702ad5d516c3e43a7f0bb8</td><td></td><td></td><td></td></tr><tr><td>ba7b12c8e2ff3c5e4e0f70b58215b41b18ff8feb</td><td>Natural and Effective Obfuscation by Head Inpainting +<br/><b>Max Planck Institute for Informatics, Saarland Informatics Campus</b><br/>2KU-Leuven/PSI, Toyota Motor Europe (TRACE) +<br/>3ETH Zurich +</td><td>('32222907', 'Qianru Sun', 'qianru sun')<br/>('1681236', 'Luc Van Gool', 'luc van gool')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td>{qsun, joon, schiele, mfritz}@mpi-inf.mpg.de +<br/>{liqian.ma, luc.vangool}@esat.kuleuven.be +<br/>vangool@vision.ee.ethz.ch +</td></tr><tr><td>bab88235a30e179a6804f506004468aa8c28ce4f</td><td></td><td></td><td></td></tr><tr><td>badd371a49d2c4126df95120902a34f4bee01b00</td><td>GONDA, WEI, PARAG, PFISTER: PARALLEL SEPARABLE 3D CONVOLUTION +<br/>Parallel Separable 3D Convolution for Video +<br/>and Volumetric Data Understanding +<br/>Harvard John A. Paulson School of +<br/>Engineering and Applied Sciences +<br/>Camabridge MA, USA +<br/>Toufiq Parag +<br/>Hanspeter Pfister +</td><td>('49147616', 'Felix Gonda', 'felix gonda')<br/>('1766333', 'Donglai Wei', 'donglai wei')</td><td>fgonda@g.harvard.edu +<br/>donglai@seas.harvard.edu +<br/>paragt@seas.harvard.edu +<br/>pfister@g.harvard.edu +</td></tr><tr><td>a065080353d18809b2597246bb0b48316234c29a</td><td>FHEDN: A based on context modeling Feature Hierarchy <br/>Encoder-Decoder Network for face detection <br/><b>College of Computer Science, Chongqing University, Chongqing, China</b><br/><b>College of Medical Informatics, Chongqing Medical University, Chongqing, China</b><br/><b>Sichuan Fine Arts Institute, Chongqing, China</b></td><td>('6030130', 'Zexun Zhou', 'zexun zhou')<br/>('7686690', 'Zhongshi He', 'zhongshi he')<br/>('2685579', 'Ziyu Chen', 'ziyu chen')<br/>('33458882', 'Yuanyuan Jia', 'yuanyuan jia')<br/>('1768826', 'Haiyan Wang', 'haiyan wang')<br/>('8784203', 'Jinglong Du', 'jinglong du')<br/>('2961485', 'Dingding Chen', 'dingding chen')</td><td>{zexunzhou,zshe,chenziyu,yyjia,jldu,dingding}@cqu.edu.cn;{why}@scfai.edu.cn </td></tr><tr><td>a0f94e9400938cbd05c4b60b06d9ed58c3458303</td><td>1118 <br/>Value-Directed Human Behavior Analysis <br/>from Video Using Partially Observable <br/>Markov Decision Processes -</td><td>('1773895', 'Jesse Hoey', 'jesse hoey')<br/>('1710980', 'James J. Little', 'james j. little')</td><td></td></tr><tr><td>a0f193c86e3dd7e0020c0de3ec1e24eaff343ce4</td><td>JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 21, 819-828 (2005) +</td><td>('1773895', 'Jesse Hoey', 'jesse hoey')<br/>('1710980', 'James J. Little', 'james j. little')</td><td></td></tr><tr><td>a022eff5470c3446aca683eae9c18319fd2406d5</td><td>2017-ENST-0071 +<br/>EDITE - ED 130 +<br/>Doctorat ParisTech +<br/>T H È S E +<br/>pour obtenir le grade de docteur délivré par +<br/>TÉLÉCOM ParisTech +<br/>Spécialité « SIGNAL et IMAGES » +<br/>présentée et soutenue publiquement par +<br/>le 15 décembre 2017 +<br/>Apprentissage Profond pour la Description Sémantique des Traits +<br/>Visuels Humains +<br/>Directeur de thèse : Jean-Luc DUGELAY +<br/>Co-encadrement de la thèse : Moez BACCOUCHE +<br/>Jury +<br/>Mme Bernadette DORIZZI, PRU, Télécom SudParis +<br/>Mme Jenny BENOIS-PINEAU, PRU, Université de Bordeaux +<br/>M. Christian WOLF, MC/HDR, INSA de Lyon +<br/>M. Patrick PEREZ, Chercheur/HDR, Technicolor Rennes +<br/>M. Moez BACCOUCHE, Chercheur/Docteur, Orange Labs Rennes +<br/>M. Jean-Luc DUGELAY, PRU, Eurecom Sophia Antipolis +<br/>M. Sid-Ahmed BERRANI, Directeur de l’Innovation/HDR, Algérie Télécom +<br/>Présidente +<br/>Rapporteur +<br/>Rapporteur +<br/>Examinateur +<br/>Encadrant +<br/>Directeur de Thèse +<br/>Invité +<br/>TÉLÉCOM ParisTech +<br/>école de l’Institut Télécom - membre de ParisTech +<br/>N°: 2009 ENAM XXXX T H È S E </td><td>('3116433', 'Grigory Antipov', 'grigory antipov')</td><td></td></tr><tr><td>a0f193c86e3dd7e0020c0de3ec1e24eaff343ce4</td><td>JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 21, 819-828 (2005) <br/>Short Paper_________________________________________________ <br/>A New Classification Approach using <br/>Discriminant Functions @@ -26496,7 +33098,7 @@ <br/>Communicated by H. Y. Mark Liao. <br/>819 </td><td>('7605725', 'Zafer Demir', 'zafer demir')<br/>('2279264', 'Erol Emre', 'erol emre')</td><td>E-mail: {askind, zdemir, eemre}@sakarya.edu.tr -</td></tr><tr><td>a0dc68c546e0fc72eb0d9ca822cf0c9ccb4b4c4f</td><td>Fusing with Context: a Bayesian Approach to Combining Descriptive Attributes +</td></tr><tr><td>a0c37f07710184597befaa7e6cf2f0893ff440e9</td><td></td><td></td><td></td></tr><tr><td>a0dc68c546e0fc72eb0d9ca822cf0c9ccb4b4c4f</td><td>Fusing with Context: a Bayesian Approach to Combining Descriptive Attributes <br/><b>University of Colorado at Colorado Springs and Securics, Inc., Colorado Springs, CO, USA</b><br/><b>Columbia University, New York, NY, USA</b><br/><b>University of North Carolina Wilmington, Wilmington, NC, USA</b></td><td>('2613438', 'Walter J. Scheirer', 'walter j. scheirer')<br/>('1767767', 'Peter N. Belhumeur', 'peter n. belhumeur')<br/>('1760117', 'Terrance E. Boult', 'terrance e. boult')</td><td></td></tr><tr><td>a0021e3bbf942a88e13b67d83db7cf52e013abfd</td><td>Human concerned object detecting in video <br/><b>School of Computer Science and Technology, Shandong Institute of Business and Technology</b><br/>Yantai, Shandong, 264005, China <br/><b>School of Computer Science and Technology, Shandong University</b><br/>Jinan, Shandong, 250101, China @@ -26507,7 +33109,9 @@ </td><td>('39447786', 'Dong Chen', 'dong chen')<br/>('2032273', 'Xudong Cao', 'xudong cao')<br/>('34508239', 'Liwei Wang', 'liwei wang')<br/>('1716835', 'Fang Wen', 'fang wen')<br/>('40055995', 'Jian Sun', 'jian sun')</td><td>chendong@mail.ustc.edu.cn <br/>lwwang@cse.cuhk.edu.hk <br/>{xudongca,fangwen,jiansun}@microsoft.com -</td></tr><tr><td>a0fb5b079dd1ee5ac6ac575fe29f4418fdb0e670</td><td></td><td></td><td></td></tr><tr><td>a0dfb8aae58bd757b801e2dcb717a094013bc178</td><td>Reconocimiento de expresiones faciales con base +</td></tr><tr><td>a0fb5b079dd1ee5ac6ac575fe29f4418fdb0e670</td><td></td><td></td><td></td></tr><tr><td>a0fd85b3400c7b3e11122f44dc5870ae2de9009a</td><td>Learning Deep Representation for Face +<br/>Alignment with Auxiliary Attributes +</td><td>('3152448', 'Zhanpeng Zhang', 'zhanpeng zhang')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td></td></tr><tr><td>a0dfb8aae58bd757b801e2dcb717a094013bc178</td><td>Reconocimiento de expresiones faciales con base <br/>en la din´amica de puntos de referencia faciales <br/>Instituto Nacional de Astrof´ısica ´Optica y Electr´onica, <br/>Divisi´on de Ciencias Computacionales, Tonantzintla, Puebla, @@ -26526,6 +33130,9 @@ <br/>Facial Expressions Recognition Based on Facial <br/>Landmarks Dynamics </td><td>('40452660', 'E. Morales-Vargas', 'e. morales-vargas')<br/>('2737777', 'Hayde Peregrina-Barreto', 'hayde peregrina-barreto')</td><td>emoralesv@inaoep.mx, kargaxxi@inaoep.mx, hperegrina@inaoep.mx +</td></tr><tr><td>a0aa32bb7f406693217fba6dcd4aeb6c4d5a479b</td><td>Cascaded Regressor based 3D Face Reconstruction +<br/>from a Single Arbitrary View Image +<br/><b>College of Computer Science, Sichuan University, Chengdu, China</b></td><td>('50207647', 'Feng Liu', 'feng liu')<br/>('39422721', 'Dan Zeng', 'dan zeng')<br/>('1723081', 'Jing Li', 'jing li')<br/>('7345195', 'Qijun Zhao', 'qijun zhao')</td><td>qjzhao@scu.edu.cn </td></tr><tr><td>a03cfd5c0059825c87d51f5dbf12f8a76fe9ff60</td><td>Simultaneous Learning and Alignment: <br/>Multi-Instance and Multi-Pose Learning? <br/>1 Comp. Science & Eng. @@ -26540,6 +33147,14 @@ </td></tr><tr><td>a06b6d30e2b31dc600f622ab15afe5e2929581a7</td><td>Robust Joint and Individual Variance Explained <br/><b>Imperial College London, UK</b><br/>2Onfido, UK <br/><b>Middlesex University London, UK</b></td><td>('3320415', 'Christos Sagonas', 'christos sagonas')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('28943361', 'Alina Leidinger', 'alina leidinger')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td>christos.sagonas@onfido.com, {i.panagakis, s.zafeiriou}@imperial.ac.uk +</td></tr><tr><td>a0b1990dd2b4cd87e4fd60912cc1552c34792770</td><td>Deep Constrained Local Models for Facial Landmark Detection +<br/><b>Carnegie Mellon University</b><br/>Tadas Baltruaitis +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +<br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave, Pittsburgh, PA 15213, USA +</td><td>('1783029', 'Amir Zadeh', 'amir zadeh')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')</td><td>abagherz@cs.cmu.edu +<br/>tbaltrus@cs.cmu.edu +<br/>morency@cs.cmu.edu </td></tr><tr><td>a090d61bfb2c3f380c01c0774ea17929998e0c96</td><td>On the Dimensionality of Video Bricks under Varying Illumination <br/>Beijing Lab of Intelligent Information Technology, School of Computer Science, <br/><b>Beijing Institute of Technology, Beijing 100081, PR China</b></td><td>('2852150', 'Youdong Zhao', 'youdong zhao')<br/>('38150687', 'Xi Song', 'xi song')<br/>('7415267', 'Yunde Jia', 'yunde jia')</td><td>{zyd458, songxi, jiayunde}@bit.edu.cn @@ -26665,14 +33280,19 @@ </td><td>('2794259', 'Eirikur Agustsson', 'eirikur agustsson')<br/>('1732855', 'Radu Timofte', 'radu timofte')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>aeirikur@vision.ee.ethz.ch <br/>timofter@vision.ee.ethz.ch <br/>vangool@vision.ee.ethz.ch -</td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td></td><td></td><td></td></tr><tr><td>a7d23c699a5ae4ad9b8a5cbb8c38e5c3b5f5fb51</td><td>Postgraduate Annual Research Seminar 2007 (3-4 July 2007) +</td></tr><tr><td>a77e9f0bd205a7733431a6d1028f09f57f9f73b0</td><td>Multimodal feature fusion for CNN-based gait recognition: an +<br/>empirical comparison +<br/>F.M. Castroa,, M.J. Mar´ın-Jim´enezb, N. Guila, N. P´erez de la Blancac +<br/><b>University of Malaga, Spain</b><br/><b>University of Cordoba, Spain</b><br/><b>University of Granada, Spain</b></td><td></td><td></td></tr><tr><td>a74251efa970b92925b89eeef50a5e37d9281ad0</td><td></td><td></td><td></td></tr><tr><td>a7d23c699a5ae4ad9b8a5cbb8c38e5c3b5f5fb51</td><td>Postgraduate Annual Research Seminar 2007 (3-4 July 2007) <br/>A Summary of literature review : Face Recognition <br/>Faculty of Computer Science & Information System, <br/><b>University Technology of Malaysia, 81310 Skudai, Johor, Malaysia</b></td><td></td><td>kittmee@yahoo.com; dzulkifli@fsksm.utm.my </td></tr><tr><td>a70e36daf934092f40a338d61e0fe27be633f577</td><td>Enhanced Facial Feature Tracking of Spontaneous and Continuous Expressions <br/>A.Goneid and R. El Kaliouby <br/><b>The American University in Cairo, Egypt</b></td><td></td><td>goneid@aucegypt.edu, ranak@aucegypt.edu -</td></tr><tr><td>a7191958e806fce2505a057196ccb01ea763b6ea</td><td>Convolutional Neural Network based +</td></tr><tr><td>a7664247a37a89c74d0e1a1606a99119cffc41d4</td><td>Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +<br/>3287 +</td><td></td><td></td></tr><tr><td>a7191958e806fce2505a057196ccb01ea763b6ea</td><td>Convolutional Neural Network based <br/>Age Estimation from Facial Image and <br/>Depth Prediction from Single Image <br/>B. Eng. (Honours) @@ -26694,7 +33314,105 @@ <br/>Corporate Research and Development Center, TOSHIBA Corporation <br/>1, KomukaiToshiba-cho, Saiwai-ku, Kawasaki 212-8582 Japan </td><td>('1770128', 'Kazuhiro Fukui', 'kazuhiro fukui')<br/>('1708862', 'Osamu Yamaguchi', 'osamu yamaguchi')</td><td>kazuhiro.fukui@toshiba.co.jp / osamu1.yamaguchi@toshiba.co.jp -</td></tr><tr><td>a7c39a4e9977a85673892b714fc9441c959bf078</td><td>Automated Individualization of Deformable Eye Region Model and Its +</td></tr><tr><td>a758b744a6d6962f1ddce6f0d04292a0b5cf8e07</td><td> +<br/>ISSN XXXX XXXX © 2017 IJESC +<br/> +<br/> +<br/>Research Article Volume 7 Issue No.4 +<br/>Study on Human Face Recognition under Invariant Pose, Illumination +<br/>and Expression using LBP, LoG and SVM +<br/>Amrutha +<br/>Depart ment of Co mputer Science & Engineering +<br/><b>Mangalore Institute of Technology and Engineering, Moodabidri, Mangalore, India</b><br/>INTRODUCTION +<br/>RELATED WORK +<br/>Abstrac t: +<br/>Face recognition system uses human face for the identification of the user. Face recognition is a difficu lt task there is no unique +<br/>method that provide accurate an accurate and effic ient solution in all the situations like the face image with differen t pose , +<br/>illu mination and exp ression. Local Binary Pattern (LBP) and Laplac ian of Gaussian (Lo G) operators. Support Vector Machine +<br/>classifier is used to recognize the human face. The Lo G algorith m is used to preprocess the image to detect the edges of the face +<br/>image to get the image information. The LBP operator divides the face image into several blocks to generate the features informat ion +<br/>on pixe l level by creating LBP labels for all the blocks of image is obtained by concatenating all the individual local histo grams. +<br/>Support Vector Machine classifier (SVM ) is used to classify t he image. The a lgorith m performances is verified under the constraints +<br/>like illu mination, e xp ression and pose variation +<br/>Ke ywor ds: Face Recognition, Local Binary Pattern, Laplac ian of Gaussian, histogram, illu mination, pose angle, exp ression +<br/>variations, SVM . +<br/>1. +<br/>The Technology used for recognizing the face under security +<br/>systems works on the bio metric principles. There are many +<br/>human characteristics which can be used +<br/>for biometric +<br/>identification such that palm, finger print, face, and iris etc. one +<br/>of these biometrics methods face recognition is advantageous +<br/>because of it can be detected fro m much more d istance without +<br/>need of scanning devices this provides easy observation to +<br/>identify indiv iduals in group of persons. Most of the military +<br/>application security systems, attendance systems, authentication, +<br/>criminal identity etc. are performed using this technology. The +<br/>computer uses this recognition technology to identify or to +<br/>compare the person with same person or with some other person. +<br/>The human faces are very important factor to identify who the +<br/>person is and how the people will ma ke out his/her face. The +<br/>images of faces are taken fro m the distance without having +<br/>contact with a person, capturing the face images. Verification +<br/>and Identification s teps are used for comparison. The first +<br/>method is verification wh ich co mpares the face image with +<br/>his/her image wh ich is a lready stored in database. It is one to one +<br/>matching because it tries to match individual against same +<br/>person's image stored in database. The second method is +<br/>called one to n matching because it matches individual person's +<br/>face image with every person's face images. If the face images +<br/>are effected by lightning condition, different posing angle or +<br/>diffe rent expression then it is difficult to identify the human +<br/>face. Many algorithms are used to extract features of face and to +<br/>match the face images such as Principal Co mponent Analysis +<br/>(PCA) and Independent Component Analysis (ICA) [1], Elastic +<br/>Bunch Graph Matching (EBGM) [2], K -nearest neighbor +<br/>algorith m classifier and Linear Discriminant Analysis (LDA) +<br/>[3]. Th is paper is organized as fo llo ws: Section II revie ws the +<br/>related works done on data security in cloud. Section III +<br/>describes the proposed system and assumptions. Section IV +<br/>provides the conclusion of the paper +<br/>2. +<br/>the most biometrics +<br/>Face Recognition becomes one of +<br/>authentication +<br/>the past few years. Face +<br/>recognition is an interesting and successful application of Pattern +<br/>recognition and Image analysis. It co mpares a query face image +<br/>against all image te mplates in a face database. Face recognition +<br/>is very important due to its wide range of commercia l and law +<br/>enforcement applicat ions, which include forensic identificat ion, +<br/>access control, border surveillance and human interactions and +<br/>availability of low cost recording devices. Principa l Co mponent +<br/>Analysis and Independent Component Analysis [1], Elastic +<br/>Bunch Graph Matching [2], K-nearest neighbor algorithm +<br/>classifier and Linear Discriminant Analysis [3], Loca l Derivative +<br/>pattern and Local Binary Pattern [4]. These algorithms are still +<br/>having some proble ms +<br/>the +<br/>constraints like variations in pose, expression and illu mination. +<br/>This variation in the image degrades the performance of +<br/>recognition rate. Local Binary Pattern (LBP) and Laplac ian of +<br/>Gaussian (Lo G) is used to reduce the illu mination effects by +<br/>increasing the contrast of the image which does not effect to the +<br/>original +<br/>image and diffe rential e xc itation pixe l used for +<br/>preprocessing which is to make the algorithm invariant to the +<br/>illu mination changes +<br/>[4]. The Local Direct ional Pattern +<br/>descriptor (LDP) uses the edge values of surrounding pixe l of +<br/>the center pixe l and Two Dimensional Principal Analysis (2D- +<br/>PCA) is used for feature extraction which uses Euclidean +<br/>distance to measure the simila rity between tra ining database +<br/>images and test image features. The nearest neighbor classifier is +<br/>used to classify the images [5]. To reduce the influence of +<br/>illu mination fro m an input image an adaptive homo morphic +<br/>filtering is used in adaptive homo morphic eight local d irectional +<br/>to recognize +<br/>the face under +<br/>techniques from +<br/>International Journal of Engineering Science and Computing, April 2017 10081 http://ije sc.org/ +</td><td></td><td></td></tr><tr><td>a7c39a4e9977a85673892b714fc9441c959bf078</td><td>Automated Individualization of Deformable Eye Region Model and Its <br/>Application to Eye Motion Analysis <br/>Dept. of Media and Image Technology, <br/><b>Tokyo Polytechnic University</b><br/>1583 Iiyama, Atsugi, @@ -26709,7 +33427,15 @@ <br/>Human face attributes prediction with Deep <br/>Learning </td><td></td><td>moaah@kth.se -</td></tr><tr><td>a703d51c200724517f099ee10885286ddbd8b587</td><td>Fuzzy Neural Networks(FNN)-based Approach for +</td></tr><tr><td>a775da3e6e6ea64bffab7f9baf665528644c7ed3</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 142 – No.9, May 2016 +<br/>Human Face Pose Estimation based on Feature +<br/>Extraction Points +<br/>Research scholar, +<br/> Department of ECE +<br/>SBSSTC, Moga Road, +<br/> Ferozepur, Punjab, India +</td><td></td><td></td></tr><tr><td>a703d51c200724517f099ee10885286ddbd8b587</td><td>Fuzzy Neural Networks(FNN)-based Approach for <br/>Personalized Facial Expression Recognition with <br/>Novel Feature Selection Method <br/>Div. of EE, Dept. of EECS, KAIST @@ -26723,7 +33449,13 @@ </td></tr><tr><td>b871d1b8495025ff8a6255514ed39f7765415935</td><td>Application of Completed Local Binary Pattern for Facial Expression <br/>Recognition on Gabor Filtered Facial Images <br/><b>University of Ulsan, Ulsan, Republic of Korea</b></td><td>('2288674', 'Tanveer Ahsan', 'tanveer ahsan')</td><td>1tanveerahsan@gmail.com, 2rsbdce@yahoo.com, *3upchong@ulsan.ac.kr -</td></tr><tr><td>b88d5e12089f6f598b8c72ebeffefc102cad1fc0</td><td>Robust 2DPCA and Its Application +</td></tr><tr><td>b8375ff50b8a6f1a10dd809129a18df96888ac8b</td><td>Published as a conference paper at ICLR 2017 +<br/>DECOMPOSING MOTION AND CONTENT FOR +<br/>NATURAL VIDEO SEQUENCE PREDICTION +<br/><b>University of Michigan, Ann Arbor, USA</b><br/>2Adobe Research, San Jose, CA 95110 +<br/>3POSTECH, Pohang, Korea +<br/><b>Beihang University, Beijing, China</b><br/>5Google Brain, Mountain View, CA 94043 +</td><td>('2241528', 'Seunghoon Hong', 'seunghoon hong')<br/>('10668384', 'Xunyu Lin', 'xunyu lin')<br/>('1697141', 'Honglak Lee', 'honglak lee')<br/>('1768964', 'Jimei Yang', 'jimei yang')<br/>('1711926', 'Ruben Villegas', 'ruben villegas')</td><td></td></tr><tr><td>b88d5e12089f6f598b8c72ebeffefc102cad1fc0</td><td>Robust 2DPCA and Its Application <br/><b>Xidian University</b><br/>Xi’an China <br/><b>Xidian University</b><br/>Xi’an China </td><td>('40326660', 'Qianqian Wang', 'qianqian wang')<br/>('38469552', 'Quanxue Gao', 'quanxue gao')</td><td>610887187@qq.com @@ -26754,7 +33486,12 @@ <br/>xgwang@ee.cuhk.edu.hk <br/>liangding@sensetime.com <br/>xtang@ie.cuhk.edu.hk -</td></tr><tr><td>b8378ab83bc165bc0e3692f2ce593dcc713df34a</td><td></td><td></td><td></td></tr><tr><td>b85580ff2d8d8be0a2c40863f04269df4cd766d9</td><td>HCMUS team at the Multimodal Person Discovery in +</td></tr><tr><td>b8378ab83bc165bc0e3692f2ce593dcc713df34a</td><td></td><td></td><td></td></tr><tr><td>b8f3f6d8f188f65ca8ea2725b248397c7d1e662d</td><td>Selfie Detection by Synergy-Constriant Based +<br/>Convolutional Neural Network +<br/>Electrical and Electronics Engineering, NITK-Surathkal, India. +</td><td>('7245071', 'Yashas Annadani', 'yashas annadani')<br/>('8341302', 'Akshay Kumar Jagadish', 'akshay kumar jagadish')<br/>('2139966', 'Krishnan Chemmangat', 'krishnan chemmangat')</td><td></td></tr><tr><td>b8ebda42e272d3617375118542d4675a0c0e501d</td><td>Deep Hashing Network for Unsupervised Domain Adaptation +<br/><b>Center for Cognitive Ubiquitous Computing, Arizona State University, Tempe, AZ, USA</b></td><td>('3151995', 'Hemanth Venkateswara', 'hemanth venkateswara')<br/>('30443430', 'Jose Eusebio', 'jose eusebio')<br/>('2471253', 'Shayok Chakraborty', 'shayok chakraborty')<br/>('1743991', 'Sethuraman Panchanathan', 'sethuraman panchanathan')</td><td>{hemanthv, jeusebio, shayok.chakraborty, panch}@asu.edu +</td></tr><tr><td>b85580ff2d8d8be0a2c40863f04269df4cd766d9</td><td>HCMUS team at the Multimodal Person Discovery in <br/>Broadcast TV Task of MediaEval 2016 <br/>Faculty of Information Technology <br/><b>University of Science, Vietnam National University-Ho Chi Minh city</b></td><td>('34453615', 'Vinh-Tiep Nguyen', 'vinh-tiep nguyen')<br/>('30097677', 'Manh-Tien H. Nguyen', 'manh-tien h. nguyen')<br/>('8176737', 'Quoc-Huu Che', 'quoc-huu che')<br/>('7736164', 'Van-Tu Ninh', 'van-tu ninh')<br/>('38994364', 'Tu-Khiem Le', 'tu-khiem le')<br/>('7213584', 'Thanh-An Nguyen', 'thanh-an nguyen')<br/>('1780348', 'Minh-Triet Tran', 'minh-triet tran')</td><td>nvtiep@fit.hcmus.edu.vn, {nhmtien, cqhuu, nvtu, ltkhiem}@apcs.vn, @@ -26772,7 +33509,10 @@ </td><td>('2811524', 'Md. Kamrul Hasan', 'md. kamrul hasan')</td><td></td></tr><tr><td>b8a829b30381106b806066d40dd372045d49178d</td><td>1872 <br/>A Probabilistic Framework for Joint Pedestrian Head <br/>and Body Orientation Estimation -</td><td>('2869660', 'Fabian Flohr', 'fabian flohr')<br/>('1898318', 'Madalin Dumitru-Guzu', 'madalin dumitru-guzu')<br/>('34846285', 'Julian F. P. Kooij', 'julian f. p. kooij')</td><td></td></tr><tr><td>b191aa2c5b8ece06c221c3a4a0914e8157a16129</td><td>: DEEP SPATIO-TEMPORAL MANIFOLD NETWORK FOR ACTION RECOGNITION +</td><td>('2869660', 'Fabian Flohr', 'fabian flohr')<br/>('1898318', 'Madalin Dumitru-Guzu', 'madalin dumitru-guzu')<br/>('34846285', 'Julian F. P. Kooij', 'julian f. p. kooij')</td><td></td></tr><tr><td>b1d89015f9b16515735d4140c84b0bacbbef19ac</td><td>Too Far to See? Not Really! +<br/>— Pedestrian Detection with Scale-aware +<br/>Localization Policy +</td><td>('47957574', 'Xiaowei Zhang', 'xiaowei zhang')<br/>('50791064', 'Li Cheng', 'li cheng')<br/>('49729740', 'Bo Li', 'bo li')<br/>('2938403', 'Hai-Miao Hu', 'hai-miao hu')</td><td></td></tr><tr><td>b191aa2c5b8ece06c221c3a4a0914e8157a16129</td><td>: DEEP SPATIO-TEMPORAL MANIFOLD NETWORK FOR ACTION RECOGNITION <br/>Deep Spatio-temporal Manifold Network for <br/>Action Recognition <br/>Department of Computer Science @@ -26810,7 +33550,7 @@ <br/>Shaohua K. Zhou <br/>Siemens Research <br/>Princeton, NJ 08540 -</td><td>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('1688416', 'Amit K. Roy-Chowdhury', 'amit k. roy-chowdhury')</td><td></td></tr><tr><td>b1665e1ddf9253dcaebecb48ac09a7ab4095a83e</td><td>EMOTION RECOGNITION USING FACIAL EXPRESSIONS WITH ACTIVE +</td><td>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('1688416', 'Amit K. Roy-Chowdhury', 'amit k. roy-chowdhury')</td><td></td></tr><tr><td>b14b672e09b5b2d984295dfafb05604492bfaec5</td><td>LearningImageClassificationandRetrievalModelsThomasMensink </td><td></td><td></td></tr><tr><td>b1665e1ddf9253dcaebecb48ac09a7ab4095a83e</td><td>EMOTION RECOGNITION USING FACIAL EXPRESSIONS WITH ACTIVE <br/>APPEARANCE MODELS <br/>Department of Computer Science <br/><b>University of North Carolina Wilmington</b><br/><b>South College Road</b><br/>Wilmington, NC, USA @@ -26824,6 +33564,9 @@ <br/><b>RWTH Aachen University, Aachen, Germany</b><br/>2 Robert Bosch GmbH, Hildesheim, Germany </td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('1685956', 'Hermann Ney', 'hermann ney')<br/>('1967060', 'Philippe Dreuw', 'philippe dreuw')</td><td><surname>@cs.rwth-aachen.de <br/>philippe.dreuw@de.bosch.com +</td></tr><tr><td>b1b993a1fbcc827bcb99c4cc1ba64ae2c5dcc000</td><td>Deep Variation-structured Reinforcement Learning for Visual Relationship and +<br/>Attribute Detection +<br/><b>School of Computer Science, Carnegie Mellon University</b></td><td>('40250403', 'Xiaodan Liang', 'xiaodan liang')<br/>('1752601', 'Eric P. Xing', 'eric p. xing')<br/>('49441821', 'Lisa Lee', 'lisa lee')</td><td>{xiaodan1,lslee,epxing}@cs.cmu.edu </td></tr><tr><td>b11bb6bd63ee6f246d278dd4edccfbe470263803</td><td>Joint Voxel and Coordinate Regression for Accurate <br/>3D Facial Landmark Localization <br/>†Center for Research on Intelligent Perception and Computing (CRIPAC) @@ -26835,7 +33578,45 @@ <br/>JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 <br/>Automatic Analysis of Facial Actions: A Survey <br/>and Maja Pantic, Fellow, IEEE -</td><td>('1680608', 'Brais Martinez', 'brais martinez')<br/>('1795528', 'Michel F. Valstar', 'michel f. valstar')<br/>('39532631', 'Bihan Jiang', 'bihan jiang')</td><td></td></tr><tr><td>b1301c722886b6028d11e4c2084ee96466218be4</td><td></td><td></td><td></td></tr><tr><td>b1c5581f631dba78927aae4f86a839f43646220c</td><td></td><td></td><td></td></tr><tr><td>b18858ad6ec88d8b443dffd3e944e653178bc28b</td><td><b>Purdue University</b><br/>Purdue e-Pubs +</td><td>('1680608', 'Brais Martinez', 'brais martinez')<br/>('1795528', 'Michel F. Valstar', 'michel f. valstar')<br/>('39532631', 'Bihan Jiang', 'bihan jiang')</td><td></td></tr><tr><td>b166ce267ddb705e6ed855c6b679ec699d62e9cb</td><td>Turk J Elec Eng & Comp Sci +<br/>(2017) 25: 4421 { 4430 +<br/>c⃝ T (cid:127)UB_ITAK +<br/>doi:10.3906/elk-1702-49 +<br/>Sample group and misplaced atom dictionary learning for face recognition +<br/><b>Faculty of Electronics and Communication, Yanshan University</b><br/><b>Faculty of Electronics and Communication, Taishan University</b><br/>Qinhuangdao, P.R. China +<br/>Tai’an, P.R. China +<br/>Received: 04.02.2017 +<br/>(cid:15) +<br/>Accepted/Published Online: 01.06.2017 +<br/>(cid:15) +<br/>Final Version: 05.10.2017 +</td><td>('39980529', 'Meng Wang', 'meng wang')<br/>('49576759', 'Zhe Sun', 'zhe sun')<br/>('6410069', 'Mei Zhu', 'mei zhu')<br/>('49632877', 'Mei Sun', 'mei sun')</td><td></td></tr><tr><td>b13e2e43672e66ba45d1b852a34737e4ce04226b</td><td>CROWLEY, PARKHI, ZISSERMAN: FACE PAINTING +<br/>Face Painting: querying art with photos +<br/>Elliot J. Crowley +<br/>Visual Geometry Group +<br/>Department of Engineering Science +<br/><b>University of Oxford</b></td><td>('3188342', 'Omkar M. Parkhi', 'omkar m. parkhi')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>elliot@robots.ox.ac.uk +<br/>omkar@robots.ox.ac.uk +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>b1e4f8c15ff30cc7d35ab25ff3eddaf854e0a87c</td><td>RESEARCH ARTICLE +<br/>Conveying facial expressions to blind and +<br/>visually impaired persons through a wearable +<br/>vibrotactile device +<br/><b>MIRA Institute, University of Twente, Enschede, The</b><br/><b>Netherlands, Donders Institute, Radboud University, Nijmegen, The</b><br/>Netherlands, 3 VicarVision, Amsterdam, The Netherlands, 4 Department of Media, Communication, & +<br/><b>Organization, University of Twente, Enschede, The Netherlands, HAN</b><br/><b>University of Applied Sciences, Arnhem, The Netherlands</b></td><td>('1950480', 'Hendrik P. Buimer', 'hendrik p. buimer')<br/>('25188062', 'Marian Bittner', 'marian bittner')<br/>('3427220', 'Tjerk Kostelijk', 'tjerk kostelijk')<br/>('49432294', 'Abdellatif Nemri', 'abdellatif nemri')<br/>('2968885', 'Richard J. A. van Wezel', 'richard j. a. van wezel')</td><td>* h.buimer@donders.ru.nl +</td></tr><tr><td>b1301c722886b6028d11e4c2084ee96466218be4</td><td></td><td></td><td></td></tr><tr><td>b15a06d701f0a7f508e3355a09d0016de3d92a6d</td><td>Running head: FACIAL CONTRAST LOOKS HEALTHY +<br/>1 +<br/>Facial contrast is a cue for perceiving health from the face +<br/>Mauger2, Frederique Morizot2 +<br/><b>Gettysburg College, Gettysburg, PA, USA</b><br/>2 CHANEL Recherche et Technologie, Chanel PB +<br/>3 Université Grenoble Alpes +<br/>Author Note +<br/>Psychologie et NeuroCognition, Université Grenoble Alpes. +<br/>This is a prepublication copy. This article may not exactly replicate the authoritative document +<br/>published in the APA journal. It is not the copy of record. The authoritative document can be +<br/>found through this DOI: http://psycnet.apa.org/doi/10.1037/xhp0000219 +</td><td>('40482411', 'Richard Russell', 'richard russell')<br/>('4556101', 'Aurélie Porcheron', 'aurélie porcheron')<br/>('40482411', 'Richard Russell', 'richard russell')<br/>('4556101', 'Aurélie Porcheron', 'aurélie porcheron')<br/>('6258499', 'Emmanuelle Mauger', 'emmanuelle mauger')<br/>('4556101', 'Aurélie Porcheron', 'aurélie porcheron')<br/>('40482411', 'Richard Russell', 'richard russell')</td><td>College, Gettysburg, PA 17325, USA. Email: rrussell@gettysburg.edu +</td></tr><tr><td>b1c5581f631dba78927aae4f86a839f43646220c</td><td></td><td></td><td></td></tr><tr><td>b18858ad6ec88d8b443dffd3e944e653178bc28b</td><td><b>Purdue University</b><br/>Purdue e-Pubs <br/>Department of Computer Science Technical <br/>Reports <br/>Department of Computer Science @@ -26861,7 +33642,9 @@ <br/><b>Graduate School of System Informatics, Kobe University</b><br/><b>Center for Information and Neural Networks, National Institute of Information and Communications Technology (NICT</b><br/><b>Pattern Recognition Group, University of Siegen</b></td><td>('2240008', 'Zhenying He', 'zhenying he')<br/>('8183718', 'Takashi Shinozaki', 'takashi shinozaki')<br/>('1707938', 'Kimiaki Shirahama', 'kimiaki shirahama')<br/>('1727057', 'Marcin Grzegorzek', 'marcin grzegorzek')<br/>('1711781', 'Kuniaki Uehara', 'kuniaki uehara')</td><td>jennyhe@ai.cs.kobe-u.ac.jp, uehara@kobe-u.ac.jp <br/>tshino@nict.go.jp <br/>kimiaki.shirahama@uni-siegen.de, marcin.grzegorzek@uni-siegen.de -</td></tr><tr><td>b1df214e0f1c5065f53054195cd15012e660490a</td><td>Supplementary Material to Sparse Coding and Dictionary Learning with Linear +</td></tr><tr><td>b1451721864e836069fa299a64595d1655793757</td><td>Criteria Sliders: Learning Continuous +<br/>Database Criteria via Interactive Ranking +<br/><b>Brown University 2University of Bath</b><br/><b>Harvard University 4Max Planck Institute for Informatics</b></td><td>('1854493', 'James Tompkin', 'james tompkin')<br/>('1808255', 'Kwang In Kim', 'kwang in kim')<br/>('1680185', 'Christian Theobalt', 'christian theobalt')</td><td></td></tr><tr><td>b1df214e0f1c5065f53054195cd15012e660490a</td><td>Supplementary Material to Sparse Coding and Dictionary Learning with Linear <br/>Dynamical Systems∗ <br/><b>Tsinghua University, State Key Lab. of Intelligent</b><br/>Technology and Systems, Tsinghua National Lab. for Information Science and Technology (TNList); <br/><b>Australian National University and NICTA, Australia</b><br/>In this supplementary material, we present the proofs of Theorems (1-3), the algorithm for learning the transition matrix @@ -26937,12 +33720,31 @@ </td><td>('37287044', 'Anirban Chakraborty', 'anirban chakraborty')<br/>('1709001', 'Bappaditya Mandal', 'bappaditya mandal')<br/>('2860592', 'Hamed Kiani Galoogahi', 'hamed kiani galoogahi')</td><td>a.chakraborty@ntu.edu.sg <br/>bmandal@i2r.a-star.edu.sg <br/>kiani.galoogahi@iit.it +</td></tr><tr><td>b1fdd4ae17d82612cefd4e78b690847b071379d3</td><td>Supervised Descent Method +<br/>CMU-RI-TR-15-28 +<br/>September 2015 +<br/><b>The Robotics Institute</b><br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA 15213 +<br/>Thesis Committee: +<br/>Fernando De la Torre, Chair +<br/>Srinivasa Narasimhan +<br/>Kris Kitani +<br/>Aleix Martinez +<br/>Submitted in partial fulfillment of the requirements +<br/>for the degree of Doctor of Philosophy in Robotics. +</td><td>('3182065', 'Xuehan Xiong', 'xuehan xiong')<br/>('3182065', 'Xuehan Xiong', 'xuehan xiong')</td><td></td></tr><tr><td>dde5125baefa1141f1ed50479a3fd67c528a965f</td><td>Synthesizing Normalized Faces from Facial Identity Features +<br/><b>Google, Inc. 2University of Massachusetts Amherst 3MIT CSAIL</b></td><td>('39578349', 'Forrester Cole', 'forrester cole')<br/>('1707347', 'Dilip Krishnan', 'dilip krishnan')</td><td>{fcole, dbelanger, dilipkay, sarna, inbarm, wfreeman}@google.com +</td></tr><tr><td>dd8084b2878ca95d8f14bae73e1072922f0cc5da</td><td>Model Distillation with Knowledge Transfer from +<br/>Face Classification to Alignment and Verification +<br/>Beijing Orion Star Technology Co., Ltd. Beijing, China +</td><td>('1747751', 'Chong Wang', 'chong wang')<br/>('26403761', 'Xipeng Lan', 'xipeng lan')</td><td>{chongwang.nlpr, xipeng.lan, caveman1984}@gmail.com </td></tr><tr><td>ddf55fc9cf57dabf4eccbf9daab52108df5b69aa</td><td>International Journal of Grid and Distributed Computing <br/>Vol. 4, No. 3, September, 2011 <br/>Methodology and Performance Analysis of 3-D Facial Expression <br/>Recognition Using Statistical Shape Representation <br/><b>ADSIP Research Centre, University of Central Lancashire</b><br/><b>School of Psychology, University of Central Lancashire</b></td><td>('2343120', 'Wei Quan', 'wei quan')<br/>('2647218', 'Bogdan J. Matuszewski', 'bogdan j. matuszewski')<br/>('2550166', 'Lik-Kwan Shark', 'lik-kwan shark')<br/>('2942330', 'Charlie Frowd', 'charlie frowd')</td><td>{WQuan, BMatuszewski1, LShark}@uclan.ac.uk <br/>CFrowd@uclan.ac.uk +</td></tr><tr><td>dd85b6fdc45bf61f2b3d3d92ce5056c47bd8d335</td><td>Unsupervised Learning and Segmentation of Complex Activities from Video +<br/><b>University of Bonn, Germany</b></td><td>('34678431', 'Fadime Sener', 'fadime sener')<br/>('2569989', 'Angela Yao', 'angela yao')</td><td>{sener,yao}@cs.uni-bonn.de </td></tr><tr><td>dda35768681f74dafd02a667dac2e6101926a279</td><td>MULTI-LAYER TEMPORAL GRAPHICAL MODEL <br/>FOR HEAD POSE ESTIMATION IN REAL-WORLD VIDEOS <br/><b>McGill University</b><br/>Centre for Intelligent Machines, @@ -26953,7 +33755,11 @@ <br/>Facial Expression Recognition Using New Feature Extraction <br/>Algorithm <br/><b>National Cheng Kung University, Tainan, Taiwan</b><br/> Received 10th Oct. 2011; accepted 5th Sep. 2012 -</td><td>('2499819', 'Hung-Fu Huang', 'hung-fu huang')<br/>('1751725', 'Shen-Chuan Tai', 'shen-chuan tai')</td><td></td></tr><tr><td>ddf099f0e0631da4a6396a17829160301796151c</td><td>IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY +</td><td>('2499819', 'Hung-Fu Huang', 'hung-fu huang')<br/>('1751725', 'Shen-Chuan Tai', 'shen-chuan tai')</td><td></td></tr><tr><td>ddbd24a73ba3d74028596f393bb07a6b87a469c0</td><td>Multi-region two-stream R-CNN +<br/>for action detection +<br/>Inria(cid:63) +</td><td>('1766837', 'Xiaojiang Peng', 'xiaojiang peng')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td>{xiaojiang.peng,cordelia.schmid}@inria.fr +</td></tr><tr><td>ddf099f0e0631da4a6396a17829160301796151c</td><td>IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY <br/>Learning Face Image Quality from <br/>Human Assessments </td><td>('2180413', 'Lacey Best-Rowden', 'lacey best-rowden')<br/>('40217643', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>dd0a334b767e0065c730873a95312a89ef7d1c03</td><td>Eigenexpressions: Emotion Recognition using Multiple @@ -26972,7 +33778,21 @@ </td><td>('2606260', 'Pascal Mettes', 'pascal mettes')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td></td></tr><tr><td>dd8d53e67668067fd290eb500d7dfab5b6f730dd</td><td>69 <br/>A Parameter-Free Framework for General <br/>Supervised Subspace Learning -</td><td>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('7137861', 'Jianzhuang Liu', 'jianzhuang liu')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>dd600e7d6e4443ebe87ab864d62e2f4316431293</td><td></td><td></td><td></td></tr><tr><td>dcb44fc19c1949b1eda9abe998935d567498467d</td><td>Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) +</td><td>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('7137861', 'Jianzhuang Liu', 'jianzhuang liu')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>ddbb6e0913ac127004be73e2d4097513a8f02d37</td><td>264 +<br/>IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 1, NO. 3, SEPTEMBER 1999 +<br/>Face Detection Using Quantized Skin Color +<br/>Regions Merging and Wavelet Packet Analysis +</td><td>('34798028', 'Christophe Garcia', 'christophe garcia')<br/>('2441655', 'Georgios Tziritas', 'georgios tziritas')</td><td></td></tr><tr><td>dd600e7d6e4443ebe87ab864d62e2f4316431293</td><td></td><td></td><td></td></tr><tr><td>dc550f361ae82ec6e1a0cf67edf6a0138163382e</td><td> +<br/>ISSN XXXX XXXX © 2018 IJESC +<br/> +<br/> +<br/>Research Article Volume 8 Issue No.3 +<br/>Emotion Based Music Player +<br/>Professor1, UG Student2, 3, 4, 5, 6 +<br/>Department of Electronics Engineering +<br/><b>K.D.K. College of Engineering Nagpur, India</b></td><td>('9217928', 'Vijay Chakole', 'vijay chakole')<br/>('48228560', 'Kalyani Trivedi', 'kalyani trivedi')</td><td></td></tr><tr><td>dcf71245addaf66a868221041aabe23c0a074312</td><td>S3FD: Single Shot Scale-invariant Face Detector +<br/><b>CBSR and NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('3220556', 'Shifeng Zhang', 'shifeng zhang')</td><td>{shifeng.zhang,xiangyu.zhu,zlei,hailin.shi,xiaobo.wang,szli}@nlpr.ia.ac.cn +</td></tr><tr><td>dcb44fc19c1949b1eda9abe998935d567498467d</td><td>Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) <br/>1916 </td><td></td><td></td></tr><tr><td>dcc38db6c885444694f515d683bbb50521ff3990</td><td>Learning to hallucinate face images via Component Generation and Enhancement <br/><b>City University of Hong Kong</b><br/><b>South China University of Technology</b><br/>3Tencent AI Lab @@ -27004,13 +33824,27 @@ <br/><b>Kwangwoon University, 447-1 Wolge-dong, Nowon-Gu, Seoul 139-701, Korea</b></td><td>('1727735', 'Changhan Park', 'changhan park')<br/>('1722181', 'Myungseok Ki', 'myungseok ki')<br/>('1723542', 'Jaechan Namkung', 'jaechan namkung')<br/>('1684329', 'Joonki Paik', 'joonki paik')</td><td>initialchp@wm.cau.ac.kr, http://ipis.cau.ac.kr, <br/>kkim@etri.re.kr, http://www.etri.re.kr, <br/>namjc@daisy.kw.ac.kr, http://vision.kw.ac.kr. +</td></tr><tr><td>dce5e0a1f2cdc3d4e0e7ca0507592860599b0454</td><td>Facelet-Bank for Fast Portrait Manipulation +<br/><b>The Chinese University of Hong Kong</b><br/>2Tencent Youtu Lab +<br/><b>Johns Hopkins University</b></td><td>('2070527', 'Ying-Cong Chen', 'ying-cong chen')<br/>('40898180', 'Yangang Ye', 'yangang ye')<br/>('1729056', 'Jiaya Jia', 'jiaya jia')</td><td>{ycchen, linhj, ryli, xtao}@cse.cuhk.edu.hk +<br/>goodshenxy@gmail.com +<br/>Mshu1@jhu.edu +<br/>yangangye@tecent.com +<br/>leojia9@gmail.com +</td></tr><tr><td>dc9d62087ff93a821e6bb8a15a8ae2da3e39dcdd</td><td>Learning with Confident Examples: +<br/>Rank Pruning for Robust Classification with Noisy Labels +<br/><b>Massachusetts Institute of Technology</b><br/>Cambridge, MA 02139 +</td><td>('39972987', 'Curtis G. Northcutt', 'curtis g. northcutt')<br/>('3716141', 'Tailin Wu', 'tailin wu')<br/>('1706040', 'Isaac L. Chuang', 'isaac l. chuang')</td><td>{cgn, tailin, ichuang}@mit.edu </td></tr><tr><td>dcce3d7e8d59041e84fcdf4418702fb0f8e35043</td><td>Probabilistic Identity Characterization for Face Recognition∗ <br/>Center for Automation Research (CfAR) and <br/>Department of Electrical and Computer Engineering <br/><b>University of Maryland, College Park, MD</b></td><td>('1682187', 'Shaohua Kevin Zhou', 'shaohua kevin zhou')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{shaohua, rama}@cfar.umd.edu </td></tr><tr><td>dce3dff9216d63c4a77a2fcb0ec1adf6d2489394</td><td>Manifold Learning for Gender Classification <br/>from Face Sequences -<br/><b>Machine Vision Group, P.O. Box 4500, FI-90014, University of Oulu, Finland</b></td><td>('1751372', 'Abdenour Hadid', 'abdenour hadid')</td><td></td></tr><tr><td>b6f758be954d34817d4ebaa22b30c63a4b8ddb35</td><td>A Proximity-Aware Hierarchical Clustering of Faces +<br/><b>Machine Vision Group, P.O. Box 4500, FI-90014, University of Oulu, Finland</b></td><td>('1751372', 'Abdenour Hadid', 'abdenour hadid')</td><td></td></tr><tr><td>dc974c31201b6da32f48ef81ae5a9042512705fe</td><td>Am I done? Predicting Action Progress in Video +<br/>1 Media Integration and Communication Center, Univ. of Florence, Italy +<br/>2 Department of Mathematics “Tullio Levi-Civita”, Univ. of Padova, Italy +</td><td>('41172759', 'Federico Becattini', 'federico becattini')<br/>('1789269', 'Tiberio Uricchio', 'tiberio uricchio')<br/>('2831602', 'Lorenzo Seidenari', 'lorenzo seidenari')<br/>('8196487', 'Alberto Del Bimbo', 'alberto del bimbo')<br/>('1795847', 'Lamberto Ballan', 'lamberto ballan')</td><td></td></tr><tr><td>b6f758be954d34817d4ebaa22b30c63a4b8ddb35</td><td>A Proximity-Aware Hierarchical Clustering of Faces <br/><b>University of Maryland, College Park</b></td><td>('3329881', 'Wei-An Lin', 'wei-an lin')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>walin@terpmail.umd.edu, pullpull@cs.umd.edu, rama@umiacs.umd.edu </td></tr><tr><td>b62571691a23836b35719fc457e093b0db187956</td><td> Volume 3, Issue 5, May 2013 ISSN: 2277 128X <br/>International Journal of Advanced Research in @@ -27036,7 +33870,26 @@ <br/>Face Recognition Using the Discrete Cosine Transform <br/><b>Center for Intelligent Machines, McGill University, 3480 University Street, Montreal, Canada H3A 2A</b></td><td>('1693521', 'Ziad M. Hafed', 'ziad m. hafed')<br/>('3631473', 'Martin D. Levine', 'martin d. levine')</td><td>zhafed@cim.mcgill.ca <br/>levine@cim.mcgill.ca -</td></tr><tr><td>b6c53891dff24caa1f2e690552a1a5921554f994</td><td></td><td></td><td></td></tr><tr><td>b613b30a7cbe76700855479a8d25164fa7b6b9f1</td><td>1 +</td></tr><tr><td>b6c53891dff24caa1f2e690552a1a5921554f994</td><td></td><td></td><td></td></tr><tr><td>b6ef158d95042f39765df04373c01546524c9ccd</td><td>Im2vid: Future Video Prediction for Static Image Action +<br/>Recognition +<br/>Badour Ahmad AlBahar +<br/>Thesis submitted to the Faculty of the +<br/><b>Virginia Polytechnic Institute and State University</b><br/>in partial fulfillment of the requirements for the degree of +<br/>Master of Science +<br/>in +<br/>Computer Engineering +<br/>Jia-Bin Huang, Chair +<br/>A. Lynn Abbott +<br/>Pratap Tokekar +<br/>May 9, 2018 +<br/>Blacksburg, Virginia +<br/>Keywords: Human Action Recognition, Static Image Action Recognition, Video Action +<br/>Recognition, Future Video Prediction. +<br/>Copyright 2018, Badour Ahmad AlBahar +</td><td></td><td></td></tr><tr><td>b68150bfdec373ed8e025f448b7a3485c16e3201</td><td>Adversarial Image Perturbation for Privacy Protection +<br/>A Game Theory Perspective +<br/><b>Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbr cken, Germany</b></td><td>('2390510', 'Seong Joon Oh', 'seong joon oh')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td>{joon,mfritz,schiele}@mpi-inf.mpg.de +</td></tr><tr><td>b613b30a7cbe76700855479a8d25164fa7b6b9f1</td><td>1 <br/>Identifying User-Specific Facial Affects from <br/>Spontaneous Expressions with Minimal Annotation </td><td>('23417737', 'Michael Xuelin Huang', 'michael xuelin huang')<br/>('1706729', 'Grace Ngai', 'grace ngai')<br/>('1730455', 'Kien A. Hua', 'kien a. hua')<br/>('1714454', 'Hong Va Leong', 'hong va leong')</td><td></td></tr><tr><td>b64cfb39840969b1c769e336a05a30e7f9efcd61</td><td>ORIGINAL RESEARCH @@ -27104,7 +33957,8 @@ <br/>Frontiers in ICT | www.frontiersin.org <br/>June 2016 | Volume 3 | Article 9 </td><td>('14556501', 'Paul Gay', 'paul gay')<br/>('2446815', 'Sylvain Meignier', 'sylvain meignier')<br/>('1682046', 'Paul Deléglise', 'paul deléglise')<br/>('1719610', 'Jean-Marc Odobez', 'jean-marc odobez')<br/>('1719610', 'Jean-Marc Odobez', 'jean-marc odobez')</td><td>odobez@idiap.ch -</td></tr><tr><td>b689d344502419f656d482bd186a5ee6b0140891</td><td>2009, Vol. 9, No. 2, 260 –264 +</td></tr><tr><td>b6f682648418422e992e3ef78a6965773550d36b</td><td>February 8, 2017 +</td><td></td><td></td></tr><tr><td>b689d344502419f656d482bd186a5ee6b0140891</td><td>2009, Vol. 9, No. 2, 260 –264 <br/>© 2009 American Psychological Association <br/>1528-3542/09/$12.00 DOI: 10.1037/a0014681 <br/>CORRECTED JULY 1, 2009; SEE LAST PAGE @@ -27160,6 +34014,15 @@ <br/>dominance and the lower on affiliation (Montepare & Dobish, <br/>2003). One interpretation of these findings is that people misat- </td><td>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('2913698', 'Alexander Todorov', 'alexander todorov')<br/>('2913698', 'Alexander Todorov', 'alexander todorov')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td>csaid@princeton.edu +</td></tr><tr><td>b6d3caccdcb3fbce45ce1a68bb5643f7e68dadb3</td><td>Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks ∗ +<br/><b>University of Science and Technology of China, Hefei, China</b><br/>‡ Microsoft Research, Beijing, China +</td><td>('3430743', 'Zhaofan Qiu', 'zhaofan qiu')<br/>('2053452', 'Ting Yao', 'ting yao')<br/>('1724211', 'Tao Mei', 'tao mei')</td><td>zhaofanqiu@gmail.com, {tiyao, tmei}@microsoft.com +</td></tr><tr><td>b6d0e461535116a675a0354e7da65b2c1d2958d4</td><td>Deep Directional Statistics: +<br/>Pose Estimation with +<br/>Uncertainty Quantification +<br/><b>Max Planck Institute for Intelligent Systems, T ubingen, Germany</b><br/>2 Amazon, T¨ubingen, Germany +<br/>3 Microsoft Research, Cambridge, UK +</td><td>('15968671', 'Sergey Prokudin', 'sergey prokudin')<br/>('2388416', 'Sebastian Nowozin', 'sebastian nowozin')</td><td>sergey.prokudin@tuebingen.mpg.de </td></tr><tr><td>b656abc4d1e9c8dc699906b70d6fcd609fae8182</td><td></td><td></td><td></td></tr><tr><td>b6a01cd4572b5f2f3a82732ef07d7296ab0161d3</td><td>Kernel-Based Supervised Discrete Hashing for <br/>Image Retrieval <br/><b>University of Florida, Gainesville, FL, 32611, USA</b></td><td>('2766473', 'Xiaoshuang Shi', 'xiaoshuang shi')<br/>('2082604', 'Fuyong Xing', 'fuyong xing')<br/>('3457945', 'Jinzheng Cai', 'jinzheng cai')<br/>('2476328', 'Zizhao Zhang', 'zizhao zhang')<br/>('1877955', 'Yuanpu Xie', 'yuanpu xie')<br/>('1705066', 'Lin Yang', 'lin yang')</td><td>xsshi2015@ufl.edu @@ -27202,6 +34065,10 @@ <br/>Electrical and Computer Engineering Department <br/><b>ShahidBeheshti University</b><br/>Tehran, Iran </td><td></td><td>J_Mazloum@sbu.ac.ir, A_Jalali@sbu.ac.ir, Amiryan.j@robocyrus.ir +</td></tr><tr><td>a92adfdd8996ab2bd7cdc910ea1d3db03c66d34f</td><td></td><td></td><td></td></tr><tr><td>a98316980b126f90514f33214dde51813693fe0d</td><td>Collaborations on YouTube: From Unsupervised Detection to the +<br/>Impact on Video and Channel Popularity +<br/>Multimedia Communications Lab (KOM), Technische Universität Darmstadt, Germany +</td><td>('49495293', 'Christian Koch', 'christian koch')<br/>('46203604', 'Moritz Lode', 'moritz lode')<br/>('2214486', 'Denny Stohr', 'denny stohr')<br/>('2869441', 'Amr Rizk', 'amr rizk')<br/>('1725298', 'Ralf Steinmetz', 'ralf steinmetz')</td><td>E-Mail: {Christian.Koch | Denny.Stohr | Amr.Rizk | Ralf.Steinmetz}@kom.tu-darmstadt.de </td></tr><tr><td>a93781e6db8c03668f277676d901905ef44ae49f</td><td>Recent Datasets on Object Manipulation: A Survey </td><td>('3112203', 'Yongqiang Huang', 'yongqiang huang')<br/>('39545911', 'Matteo Bianchi', 'matteo bianchi')<br/>('2646612', 'Minas Liarokapis', 'minas liarokapis')<br/>('1681376', 'Yu Sun', 'yu sun')</td><td></td></tr><tr><td>a9fc23d612e848250d5b675e064dba98f05ad0d9</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, <br/>Vol. 9, No. 2, 2018 @@ -27253,12 +34120,19 @@ </td></tr><tr><td>a967426ec9b761a989997d6a213d890fc34c5fe3</td><td>Relative Ranking of Facial Attractiveness <br/>Department of Computer Science and Engineering <br/><b>University of California, San Diego</b></td><td>('3079766', 'Hani Altwaijry', 'hani altwaijry')</td><td>{haltwaij,sjb}@cs.ucsd.edu -</td></tr><tr><td>a9286519e12675302b1d7d2fe0ca3cc4dc7d17f6</td><td>Learning to Succeed while Teaching to Fail: +</td></tr><tr><td>a95dc0c4a9d882a903ce8c70e80399f38d2dcc89</td><td> TR-IIS-14-003 +<br/>Review and Implementation of +<br/>High-Dimensional Local Binary +<br/>Patterns and Its Application to +<br/>Face Recognition +<br/>July. 24, 2014 || Technical Report No. TR-IIS-14-003 +<br/>http://www.iis.sinica.edu.tw/page/library/TechReport/tr2014/tr14.html +</td><td>('33970300', 'Bor-Chun Chen', 'bor-chun chen')<br/>('1720473', 'Chu-Song Chen', 'chu-song chen')</td><td></td></tr><tr><td>a9286519e12675302b1d7d2fe0ca3cc4dc7d17f6</td><td>Learning to Succeed while Teaching to Fail: <br/>Privacy in Closed Machine Learning Systems </td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('4838771', 'Miguel R. D. Rodrigues', 'miguel r. d. rodrigues')<br/>('1699339', 'Guillermo Sapiro', 'guillermo sapiro')</td><td></td></tr><tr><td>a949b8700ca6ba96ee40f75dfee1410c5bbdb3db</td><td>Instance-weighted Transfer Learning of Active Appearance Models <br/><b>Computer Vision Group, Friedrich Schiller University of Jena, Germany</b><br/>Ernst-Abbe-Platz 2-4, 07743 Jena, Germany </td><td>('1708249', 'Daniel Haase', 'daniel haase')<br/>('1679449', 'Erik Rodner', 'erik rodner')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td>{daniel.haase,erik.rodner,joachim.denzler}@uni-jena.de -</td></tr><tr><td>a9be20954e9177d8b2bc39747acdea4f5496f394</td><td>Event-specific Image Importance +</td></tr><tr><td>a92b5234b8b73e06709dd48ec5f0ec357c1aabed</td><td></td><td></td><td></td></tr><tr><td>a9be20954e9177d8b2bc39747acdea4f5496f394</td><td>Event-specific Image Importance <br/><b>University of California, San Diego</b><br/>2Adobe Research </td><td>('35259685', 'Yufei Wang', 'yufei wang')</td><td>{yuw176, gary}@ucsd.edu <br/>{zlin, xshen, rmech, gmiller}@adobe.com @@ -27278,6 +34152,16 @@ </td></tr><tr><td>d5375f51eeb0c6eff71d6c6ad73e11e9353c1f12</td><td>Manifold Ranking-Based Locality Preserving Projections <br/><b>School of Computer Science and Engineering, South China University of Technology</b><br/>Guangzhou 510006, Guangdong, China </td><td>('2132230', 'Jia Wei', 'jia wei')<br/>('3231018', 'Zewei Chen', 'zewei chen')<br/>('1837988', 'Pingyang Niu', 'pingyang niu')<br/>('2524825', 'Yishun Chen', 'yishun chen')<br/>('7307608', 'Wenhui Chen', 'wenhui chen')</td><td>csjwei@scut.edu.cn +</td></tr><tr><td>d5d7e89e6210fcbaa52dc277c1e307632cd91dab</td><td>DOTA: A Large-scale Dataset for Object Detection in Aerial Images∗ +<br/><b>State Key Lab. LIESMARS, Wuhan University, China</b><br/>2EIS, Huazhong Univ. Sci. and Tech., China +<br/><b>Computer Science Depart., Cornell University, USA</b><br/><b>Computer Science Depart., Rochester University, USA</b><br/>5German Aerospace Center (DLR), Germany +<br/><b>DAIS, University of Venice, Italy</b><br/>January 30, 2018 +</td><td>('39943835', 'Gui-Song Xia', 'gui-song xia')<br/>('1686737', 'Xiang Bai', 'xiang bai')<br/>('1749386', 'Jian Ding', 'jian ding')<br/>('48148046', 'Zhen Zhu', 'zhen zhu')<br/>('33642939', 'Jiebo Luo', 'jiebo luo')<br/>('1777167', 'Mihai Datcu', 'mihai datcu')<br/>('8111020', 'Marcello Pelillo', 'marcello pelillo')<br/>('1733213', 'Liangpei Zhang', 'liangpei zhang')</td><td>{guisong.xia, jding, zlp62}@whu.edu.cn +<br/>{xbai, zzhu}@hust.edu.cn +<br/>sjb344@cornell.edu +<br/>jiebo.luo@gmail.com +<br/>mihai.datcu@dlr.de +<br/>pelillo@dsi.unive.it </td></tr><tr><td>d50c6d22449cc9170ab868b42f8c72f8d31f9b6c</td><td>Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) <br/>1668 </td><td></td><td></td></tr><tr><td>d522c162bd03e935b1417f2e564d1357e98826d2</td><td>He et al. EURASIP Journal on Advances in Signal Processing 2013, 2013:19 @@ -27366,7 +34250,12 @@ <br/>in <br/>illumination based <br/>is developed with the objective to -</td><td>('1968167', 'Yee Wan Wong', 'yee wan wong')</td><td></td></tr><tr><td>d5ab6aa15dad26a6ace5ab83ce62b7467a18a88e</td><td>World Journal of Computer Application and Technology 2(7): 133-138, 2014 +</td><td>('1968167', 'Yee Wan Wong', 'yee wan wong')</td><td></td></tr><tr><td>d5444f9475253bbcfef85c351ea9dab56793b9ea</td><td>IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS +<br/>BoxCars: Improving Fine-Grained Recognition +<br/>of Vehicles using 3D Bounding Boxes +<br/>in Traffic Surveillance +<br/>in contrast +</td><td>('34891870', 'Jakub Sochor', 'jakub sochor')<br/>('1785162', 'Adam Herout', 'adam herout')</td><td></td></tr><tr><td>d5ab6aa15dad26a6ace5ab83ce62b7467a18a88e</td><td>World Journal of Computer Application and Technology 2(7): 133-138, 2014 <br/>DOI: 10.13189/wjcat.2014.020701 <br/>http://www.hrpub.org <br/>Optimized Structure for Facial Action Unit Relationship @@ -27392,7 +34281,9 @@ </td></tr><tr><td>d56fe69cbfd08525f20679ffc50707b738b88031</td><td>Training of multiple classifier systems utilizing <br/>partially labelled sequences <br/><b></b><br/>89069 Ulm - Germany -</td><td>('3037635', 'Martin Schels', 'martin schels')<br/>('2307794', 'Patrick Schillinger', 'patrick schillinger')<br/>('1685857', 'Friedhelm Schwenker', 'friedhelm schwenker')</td><td></td></tr><tr><td>d50751da2997e7ebc89244c88a4d0d18405e8507</td><td></td><td></td><td></td></tr><tr><td>d511e903a882658c9f6f930d6dd183007f508eda</td><td></td><td></td><td></td></tr><tr><td>d50a40f2d24363809a9ac57cf7fbb630644af0e5</td><td>END-TO-END TRAINED CNN ENCODER-DECODER NETWORKS FOR IMAGE +</td><td>('3037635', 'Martin Schels', 'martin schels')<br/>('2307794', 'Patrick Schillinger', 'patrick schillinger')<br/>('1685857', 'Friedhelm Schwenker', 'friedhelm schwenker')</td><td></td></tr><tr><td>d5de42d37ee84c86b8f9a054f90ddb4566990ec0</td><td>Asynchronous Temporal Fields for Action Recognition +<br/><b>Carnegie Mellon University 2University of Washington 3Allen Institute for Arti cial Intelligence</b><br/>github.com/gsig/temporal-fields/ +</td><td>('34280810', 'Gunnar A. Sigurdsson', 'gunnar a. sigurdsson')<br/>('2270286', 'Ali Farhadi', 'ali farhadi')<br/>('1737809', 'Abhinav Gupta', 'abhinav gupta')</td><td></td></tr><tr><td>d50751da2997e7ebc89244c88a4d0d18405e8507</td><td></td><td></td><td></td></tr><tr><td>d511e903a882658c9f6f930d6dd183007f508eda</td><td></td><td></td><td></td></tr><tr><td>d50a40f2d24363809a9ac57cf7fbb630644af0e5</td><td>END-TO-END TRAINED CNN ENCODER-DECODER NETWORKS FOR IMAGE <br/>STEGANOGRAPHY <br/><b>National University of Computer and Emerging Sciences (NUCES-FAST), Islamabad, Pakistan</b><br/>Reveal.ai (Recognition, Vision & Learning) Lab </td><td>('9205693', 'Atique ur Rehman', 'atique ur rehman')<br/>('2695106', 'Sibt ul Hussain', 'sibt ul hussain')</td><td></td></tr><tr><td>d5b5c63c5611d7b911bc1f7e161a0863a34d44ea</td><td>Extracting Scene-dependent Discriminant @@ -27434,7 +34325,16 @@ <br/>local <br/>INTRODUCTION <br/> -</td><td>('2890210', 'Ramchand Hablani', 'ramchand hablani')</td><td></td></tr><tr><td>d24dafe10ec43ac8fb98715b0e0bd8e479985260</td><td>J Nonverbal Behav (2018) 42:81–99 +</td><td>('2890210', 'Ramchand Hablani', 'ramchand hablani')</td><td></td></tr><tr><td>d2eb1079552fb736e3ba5e494543e67620832c52</td><td>ANNUNZIATA, SAGONAS, CALÌ: DENSELY FUSED SPATIAL TRANSFORMER NETWORKS1 +<br/>DeSTNet: Densely Fused Spatial +<br/>Transformer Networks1 +<br/>Onfido Research +<br/>3 Finsbury Avenue +<br/>London, UK +</td><td>('31336510', 'Roberto Annunziata', 'roberto annunziata')<br/>('3320415', 'Christos Sagonas', 'christos sagonas')<br/>('1997807', 'Jacques Calì', 'jacques calì')</td><td>roberto.annunziata@onfido.com +<br/>christos.sagonas@onfido.com +<br/>jacques.cali@onfido.com +</td></tr><tr><td>d24dafe10ec43ac8fb98715b0e0bd8e479985260</td><td>J Nonverbal Behav (2018) 42:81–99 <br/>https://doi.org/10.1007/s10919-017-0266-z <br/>O R I G I N A L P A P E R <br/>Effects of Social Anxiety on Emotional Mimicry @@ -27448,7 +34348,42 @@ <br/><b>Michigan State University, NEC Laboratories America</b></td><td>('39708770', 'Xi Yin', 'xi yin')<br/>('15644381', 'Xiang Yu', 'xiang yu')<br/>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')<br/>('40022363', 'Xiaoming Liu', 'xiaoming liu')<br/>('2099305', 'Manmohan Chandraker', 'manmohan chandraker')</td><td>{yinxi1,liuxm}@cse.msu.edu,{xiangyu,ksohn,manu}@nec-labs.com </td></tr><tr><td>d280bcbb387b1d548173917ae82cb6944e3ceca6</td><td>FACIAL GRID TRANSFORMATION: A NOVEL FACE REGISTRATION APPROACH FOR <br/>IMPROVING FACIAL ACTION UNIT RECOGNITION -<br/><b>University of South Carolina, Columbia, USA</b></td><td>('3225915', 'Shizhong Han', 'shizhong han')<br/>('3091647', 'Zibo Meng', 'zibo meng')<br/>('40205868', 'Ping Liu', 'ping liu')<br/>('1686235', 'Yan Tong', 'yan tong')</td><td></td></tr><tr><td>d2cd9a7f19600370bce3ea29aba97d949fe0ceb9</td><td>Separability Oriented Preprocessing for +<br/><b>University of South Carolina, Columbia, USA</b></td><td>('3225915', 'Shizhong Han', 'shizhong han')<br/>('3091647', 'Zibo Meng', 'zibo meng')<br/>('40205868', 'Ping Liu', 'ping liu')<br/>('1686235', 'Yan Tong', 'yan tong')</td><td></td></tr><tr><td>d278e020be85a1ccd90aa366b70c43884dd3f798</td><td>Learning From Less Data: Diversified Subset Selection and +<br/>Active Learning in Image Classification Tasks +<br/>IIT Bombay +<br/>Mumbai, Maharashtra, India +<br/>AITOE Labs +<br/>Mumbai, Maharashtra, India +<br/>AITOE Labs +<br/>Mumbai, Maharashtra, India +<br/>Rishabh Iyer +<br/>AITOE Labs +<br/>Seattle, Washington, USA +<br/>AITOE Labs +<br/>Seattle, Washington, USA +<br/>Narsimha Raju +<br/>IIT Bombay +<br/>Mumbai, Maharashtra, India +<br/>IIT Bombay +<br/>Mumbai, Maharashtra, India +<br/>IIT Bombay +<br/>Mumbai, Maharashtra, India +<br/>May 30, 2018 +</td><td>('3333118', 'Vishal Kaushal', 'vishal kaushal')<br/>('40224337', 'Khoshrav Doctor', 'khoshrav doctor')<br/>('33911191', 'Suyash Shetty', 'suyash shetty')<br/>('10710354', 'Anurag Sahoo', 'anurag sahoo')<br/>('49613683', 'Pankaj Singh', 'pankaj singh')<br/>('1697088', 'Ganesh Ramakrishnan', 'ganesh ramakrishnan')</td><td>vkaushal@cse.iitb.ac.in +<br/>khoshrav@gmail.com +<br/>suyashshetty29@gmail.com +<br/>rishabh@aitoelabs.com +<br/>anurag@aitoelabs.com +<br/>uavnraju@cse.iitb.ac.in +<br/>pr.pankajsingh@gmail.com +<br/>ganesh@cse.iitb.ac.in +</td></tr><tr><td>d26b443f87df76034ff0fa9c5de9779152753f0c</td><td>A GPU-Oriented Algorithm Design for +<br/>Secant-Based Dimensionality Reduction +<br/>Department of Mathematics +<br/><b>Colorado State University</b><br/>Fort Collins, CO 80523-1874 +<br/>tool +<br/>for extracting useful +</td><td>('51042250', 'Henry Kvinge', 'henry kvinge')<br/>('51121534', 'Elin Farnell', 'elin farnell')<br/>('41211081', 'Michael Kirby', 'michael kirby')<br/>('30383278', 'Chris Peterson', 'chris peterson')</td><td></td></tr><tr><td>d2cd9a7f19600370bce3ea29aba97d949fe0ceb9</td><td>Separability Oriented Preprocessing for <br/>Illumination-Insensitive Face Recognition <br/>1 Key Lab of Intelligent Information Processing <br/>of Chinese Academy of Sciences (CAS), @@ -27475,10 +34410,20 @@ <br/>Visual Geometry Group <br/>Department of Engineering Science <br/><b>University of Oxford</b><br/><b>Wolfson College</b><br/>April 2015 -</td><td></td><td></td></tr><tr><td>aafb271684a52a0b23debb3a5793eb618940c5dd</td><td></td><td></td><td></td></tr><tr><td>aa8ef6ba6587c8a771ec4f91a0dd9099e96f6d52</td><td>Improved Face Tracking Thanks to Local Features +</td><td></td><td></td></tr><tr><td>aafb271684a52a0b23debb3a5793eb618940c5dd</td><td></td><td></td><td></td></tr><tr><td>aae742779e8b754da7973949992d258d6ca26216</td><td>Robust Facial Expression Classification Using Shape +<br/>and Appearance Features +<br/>Department of Electrical Engineering, +<br/><b>Indian Institute of Technology Kharagpur, India</b></td><td>('2680543', 'Aurobinda Routray', 'aurobinda routray')</td><td></td></tr><tr><td>aa8ef6ba6587c8a771ec4f91a0dd9099e96f6d52</td><td>Improved Face Tracking Thanks to Local Features <br/>Correspondence <br/>Department of Information Engineering -<br/><b>University of Brescia</b></td><td>('3134795', 'Alberto Piacenza', 'alberto piacenza')<br/>('1806359', 'Fabrizio Guerrini', 'fabrizio guerrini')<br/>('1741369', 'Riccardo Leonardi', 'riccardo leonardi')</td><td></td></tr><tr><td>aa912375eaf50439bec23de615aa8a31a3395ad3</td><td>International Journal on Cryptography and Information Security(IJCIS),Vol.2, No.2, June 2012 +<br/><b>University of Brescia</b></td><td>('3134795', 'Alberto Piacenza', 'alberto piacenza')<br/>('1806359', 'Fabrizio Guerrini', 'fabrizio guerrini')<br/>('1741369', 'Riccardo Leonardi', 'riccardo leonardi')</td><td></td></tr><tr><td>aab3561acbd19f7397cbae39dd34b3be33220309</td><td>Quantization Mimic: Towards Very Tiny CNN +<br/>for Object Detection +<br/><b>Tsinghua University, Beijing, China</b><br/><b>The Chinese University of Hong Kong, Hong Kong, China</b><br/>3SenseTime, Beijing, China +<br/><b>The University of Sydney, SenseTime Computer Vision Research Group, Sydney</b><br/>New South Wales, Australia +</td><td>('49019561', 'Yi Wei', 'yi wei')<br/>('7418754', 'Xinyu Pan', 'xinyu pan')<br/>('46636770', 'Hongwei Qin', 'hongwei qin')<br/>('1721677', 'Junjie Yan', 'junjie yan')</td><td>wei-y15@mails.tsinghua.edu.cn,THUSEpxy@gmail.com +<br/>qinhongwei@sensetime.com,wanli.ouyang@sydney.edu.au +<br/>yanjunjie@sensetime.com +</td></tr><tr><td>aa912375eaf50439bec23de615aa8a31a3395ad3</td><td>International Journal on Cryptography and Information Security(IJCIS),Vol.2, No.2, June 2012 <br/>Implementation of a New Methodology to Reduce <br/>the Effects of Changes of Illumination in Face <br/>Recognition-based Authentication @@ -27499,9 +34444,18 @@ <br/>International Journal of Computational Engineering Research (IJCER) <br/>Facial Expression Recognition System: A Digital Printing <br/>Application -<br/><b>Jadavpur University, India</b><br/><b>Jadavpur University, India</b></td><td>('2226316', 'Somnath Banerjee', 'somnath banerjee')</td><td></td></tr><tr><td>aa0c30bd923774add6e2f27ac74acd197b9110f2</td><td>DYNAMIC PROBABILISTIC LINEAR DISCRIMINANT ANALYSIS FOR VIDEO +<br/><b>Jadavpur University, India</b><br/><b>Jadavpur University, India</b></td><td>('2226316', 'Somnath Banerjee', 'somnath banerjee')</td><td></td></tr><tr><td>aafb8dc8fda3b13a64ec3f1ca7911df01707c453</td><td>Excitation Backprop for RNNs +<br/><b>Boston University 2Pattern Analysis and Computer Vision (PAVIS</b><br/>Istituto Italiano di Tecnologia 3Adobe Research 4Computer Science Department, Universit`a di Verona +<br/>Figure 1: Our proposed framework spatiotemporally highlights/grounds the evidence that an RNN model used in producing a class label +<br/>or caption for a given input video. In this example, by using our proposed back-propagation method, the evidence for the activity class +<br/>CliffDiving is highlighted in a video that contains CliffDiving and HorseRiding. Our model employs a single backward pass to produce +<br/>saliency maps that highlight the evidence that a given RNN used in generating its outputs. +</td><td>('3298267', 'Sarah Adel Bargal', 'sarah adel bargal')<br/>('40063519', 'Andrea Zunino', 'andrea zunino')<br/>('40622560', 'Donghyun Kim', 'donghyun kim')<br/>('1701293', 'Jianming Zhang', 'jianming zhang')<br/>('1727204', 'Vittorio Murino', 'vittorio murino')<br/>('1749590', 'Stan Sclaroff', 'stan sclaroff')</td><td>{sbargal,donhk,sclaroff}@bu.edu, {andrea.zunino,vittorio.murino}@iit.it, jianmzha@adobe.com +</td></tr><tr><td>aa0c30bd923774add6e2f27ac74acd197b9110f2</td><td>DYNAMIC PROBABILISTIC LINEAR DISCRIMINANT ANALYSIS FOR VIDEO <br/>CLASSIFICATION -<br/><b>Deparment of Computing, Imperial College London, UK</b><br/><b>Deparment of Computing, Goldsmiths, University of London, UK</b><br/><b>Middlesex University London, 4International Hellenic University</b><br/><b>Center for Machine Vision and Signal Analysis, University of Oulu, Finland</b></td><td>('35340264', 'Alessandro Fabris', 'alessandro fabris')<br/>('1752913', 'Mihalis A. Nicolaou', 'mihalis a. nicolaou')<br/>('1754270', 'Irene Kotsia', 'irene kotsia')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td></td></tr><tr><td>aaa4c625f5f9b65c7f3df5c7bfe8a6595d0195a5</td><td>Biometrics in Ambient Intelligence +<br/><b>Deparment of Computing, Imperial College London, UK</b><br/><b>Deparment of Computing, Goldsmiths, University of London, UK</b><br/><b>Middlesex University London, 4International Hellenic University</b><br/><b>Center for Machine Vision and Signal Analysis, University of Oulu, Finland</b></td><td>('35340264', 'Alessandro Fabris', 'alessandro fabris')<br/>('1752913', 'Mihalis A. Nicolaou', 'mihalis a. nicolaou')<br/>('1754270', 'Irene Kotsia', 'irene kotsia')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td></td></tr><tr><td>aadfcaf601630bdc2af11c00eb34220da59b7559</td><td>Multi-view Hybrid Embedding: +<br/>A Divide-and-Conquer Approach +</td><td>('30443690', 'Jiamiao Xu', 'jiamiao xu')<br/>('2462771', 'Shujian Yu', 'shujian yu')<br/>('1744228', 'Xinge You', 'xinge you')<br/>('3381421', 'Mengjun Leng', 'mengjun leng')<br/>('15132338', 'Xiao-Yuan Jing', 'xiao-yuan jing')<br/>('1697202', 'C. L. Philip Chen', 'c. l. philip chen')</td><td></td></tr><tr><td>aaa4c625f5f9b65c7f3df5c7bfe8a6595d0195a5</td><td>Biometrics in Ambient Intelligence </td><td>('1725688', 'Massimo Tistarelli', 'massimo tistarelli')</td><td></td></tr><tr><td>aac934f2eed758d4a27562dae4e9c5415ff4cdb7</td><td>TS-LSTM and Temporal-Inception: <br/>Exploiting Spatiotemporal Dynamics for Activity Recognition <br/><b>Georgia Institute of Technology</b><br/>2Georgia Tech Research Institution @@ -27521,6 +34475,10 @@ <br/>iamdh@kaist.ac.kr <br/>minerrba@kaist.ac.kr <br/>cdyoo@ee.kaist.ac.kr +</td></tr><tr><td>aa3c9de34ef140ec812be85bb8844922c35eba47</td><td>Reducing Gender Bias Amplification using Corpus-level Constraints +<br/>Men Also Like Shopping: +<br/><b>University of Virginia</b><br/><b>University of Washington</b></td><td>('3456473', 'Tianlu Wang', 'tianlu wang')<br/>('2064210', 'Mark Yatskar', 'mark yatskar')<br/>('33524946', 'Jieyu Zhao', 'jieyu zhao')<br/>('2782886', 'Kai-Wei Chang', 'kai-wei chang')<br/>('2004053', 'Vicente Ordonez', 'vicente ordonez')</td><td>{jz4fu, tw8cb, vicente, kc2wc}@virginia.edu +<br/>my89@cs.washington.edu </td></tr><tr><td>aa94f214bb3e14842e4056fdef834a51aecef39c</td><td>Reconhecimento de padrões faciais: Um estudo <br/>Universidade Federal <br/>Rural do Semi-Árido @@ -27618,7 +34576,10 @@ <br/>at <br/><b>University College London</b><br/>Department of Computer Science <br/><b>University College London</b><br/>May 26, 2015 -</td><td>('38098063', 'Yun Fu', 'yun fu')</td><td></td></tr><tr><td>af13c355a2a14bb74847aedeafe990db3fc9cbd4</td><td>Happy and Agreeable? Multi-Label Classification of +</td><td>('38098063', 'Yun Fu', 'yun fu')</td><td></td></tr><tr><td>aff8705fb2f2ae460cb3980b47f2e85c2e6dd41a</td><td>Attributes in Multiple Facial Images +<br/><b>West Virginia University, Morgantown</b><br/>WV 26506, USA +</td><td>('1767347', 'Xudong Liu', 'xudong liu')<br/>('1822413', 'Guodong Guo', 'guodong guo')</td><td>xdliu@mix.wvu.edu, guodong.guo@mail.wvu.edu +</td></tr><tr><td>af13c355a2a14bb74847aedeafe990db3fc9cbd4</td><td>Happy and Agreeable? Multi-Label Classification of <br/>Impressions in Social Video <br/><b>Idiap Research Institute</b><br/>Switzerland <br/>Instituto Potosino de @@ -27631,7 +34592,7 @@ </td><td>('2389354', 'Gilberto Chávez-Martínez', 'gilberto chávez-martínez')<br/>('1934619', 'Salvador Ruiz-Correa', 'salvador ruiz-correa')<br/>('1698682', 'Daniel Gatica-Perez', 'daniel gatica-perez')</td><td>gchavez@idiap.ch <br/>src@cmls.pw <br/>gatica@idiap.ch -</td></tr><tr><td>af62621816fbbe7582a7d237ebae1a4d68fcf97d</td><td>International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 +</td></tr><tr><td>af6cae71f24ea8f457e581bfe1240d5fa63faaf7</td><td></td><td></td><td></td></tr><tr><td>af62621816fbbe7582a7d237ebae1a4d68fcf97d</td><td>International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 <br/>International Conference on Humming Bird ( 01st March 2014) <br/>RESEARCH ARTICLE <br/> OPEN ACCESS @@ -27639,19 +34600,56 @@ <br/>AncyRija V , Gayathri. S2 <br/><b>AncyRijaV, Author is currently pursuing M.E (Software Engineering) in Vins Christian College of</b><br/>Engineering, <br/><b>Gayathri.S, M.E., Vins Christian college of Engineering</b></td><td></td><td>e-mail: ancyrija@gmail.com. -</td></tr><tr><td>af54dd5da722e104740f9b6f261df9d4688a9712</td><td></td><td></td><td></td></tr><tr><td>afe9cfba90d4b1dbd7db1cf60faf91f24d12b286</td><td>Principal Directions of Synthetic Exact Filters +</td></tr><tr><td>afdf9a3464c3b015f040982750f6b41c048706f5</td><td>A Recurrent Encoder-Decoder Network for Sequential Face Alignment +<br/><b>Rutgers University</b><br/>Rogerio Feris +<br/>IBM T. J. Watson +<br/>Snapchat Research +<br/>Dimitris Metaxas +<br/><b>Rutgers University</b></td><td>('4340744', 'Xi Peng', 'xi peng')<br/>('48631738', 'Xiaoyu Wang', 'xiaoyu wang')</td><td>xipeng.cs@rutgers.edu +<br/>rsferis@us.ibm.com +<br/>fanghuaxue@gmail.com +<br/>dnm@cs.rutgers.edu +</td></tr><tr><td>af54dd5da722e104740f9b6f261df9d4688a9712</td><td></td><td></td><td></td></tr><tr><td>afa57e50570a6599508ee2d50a7b8ca6be04834a</td><td>Motion in action : optical flow estimation and action +<br/>localization in videos +<br/>To cite this version: +<br/>Computer Vision and Pattern Recognition [cs.CV]. Université Grenoble Alpes, 2016. English. <NNT : +<br/>2016GREAM013>. <tel-01407258> +<br/>HAL Id: tel-01407258 +<br/>https://tel.archives-ouvertes.fr/tel-01407258 +<br/>Submitted on 1 Dec 2016 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')<br/>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')</td><td></td></tr><tr><td>afe9cfba90d4b1dbd7db1cf60faf91f24d12b286</td><td>Principal Directions of Synthetic Exact Filters <br/>for Robust Real-Time Eye Localization <br/>Vitomir ˇStruc1;2, Jerneja ˇZganec Gros1, and Nikola Paveˇsi´c2 <br/>1 Alpineon Ltd, Ulica Iga Grudna 15, SI-1000 Ljubljana, Slovenia, <br/><b>Faculty of Electrical Engineering, University of Ljubljana, Tr za ska cesta</b><br/>SI-1000 Ljubljana, Slovenia, </td><td></td><td>fvitomir.struc, jerneja.grosg@alpineon.com, <br/>fvitomir.struc, nikola.pavesicg@fe.uni-lj.si +</td></tr><tr><td>afa84ff62c9f5b5c280de2996b69ad9fa48b7bc3</td><td>Two-stream Flow-guided Convolutional Attention Networks for Action +<br/>Recognition +<br/><b>National University of Singapore</b><br/>Loong-Fah Cheong +</td><td>('25205026', 'An Tran', 'an tran')</td><td>an.tran@u.nus.edu +<br/>eleclf@nus.edu.sg </td></tr><tr><td>af278274e4bda66f38fd296cfa5c07804fbc26ee</td><td>RESEARCH ARTICLE <br/>A Novel Maximum Entropy Markov Model for <br/>Human Facial Expression Recognition <br/><b>College of Information and Communication Engineering, Sungkyunkwan University, Suwon-si, Gyeonggi</b><br/><b>do, Rep. of Korea, Kyung Hee University, Suwon, Rep. of Korea</b><br/><b>Innopolis University, Kazan, Russia</b><br/>a11111 <br/>☯ These authors contributed equally to this work. </td><td>('1711083', 'Muhammad Hameed Siddiqi', 'muhammad hameed siddiqi')<br/>('2401685', 'Md. Golam Rabiul Alam', 'md. golam rabiul alam')<br/>('1683244', 'Choong Seon Hong', 'choong seon hong')<br/>('1734679', 'Hyunseung Choo', 'hyunseung choo')</td><td>* choo@skku.edu +</td></tr><tr><td>af654a7ec15168b16382bd604889ea07a967dac6</td><td>FACE RECOGNITION COMMITTEE MACHINE +<br/>Department of Computer Science and Engineering +<br/><b>The Chinese University of Hong Kong</b><br/>Shatin, Hong Kong +</td><td>('2899702', 'Ho-Man Tang', 'ho-man tang')<br/>('1681775', 'Michael R. Lyu', 'michael r. lyu')<br/>('1706259', 'Irwin King', 'irwin king')</td><td> </td></tr><tr><td>afc7092987f0d05f5685e9332d83c4b27612f964</td><td>Person-Independent Facial Expression Detection using Constrained <br/>Local Models </td><td>('1713496', 'Patrick Lucey', 'patrick lucey')<br/>('1820249', 'Simon Lucey', 'simon lucey')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('1729760', 'Sridha Sridharan', 'sridha sridharan')</td><td></td></tr><tr><td>b730908bc1f80b711c031f3ea459e4de09a3d324</td><td>2024 @@ -27717,6 +34715,25 @@ <br/>ities that involve two or more persons and objects. The <br/>additional person or object is an important characteristic of </td><td>('7671146', 'Shugang Zhang', 'shugang zhang')<br/>('39868595', 'Zhiqiang Wei', 'zhiqiang wei')<br/>('2896895', 'Jie Nie', 'jie nie')<br/>('40284611', 'Lei Huang', 'lei huang')<br/>('40658604', 'Shuang Wang', 'shuang wang')<br/>('40166799', 'Zhen Li', 'zhen li')<br/>('7671146', 'Shugang Zhang', 'shugang zhang')</td><td>Correspondence should be addressed to Zhen Li; lizhen0130@gmail.com +</td></tr><tr><td>b73795963dc623a634d218d29e4a5b74dfbc79f1</td><td>ZHAO, YANG: IDENTITY PRESERVING FACE COMPLETION FOR LARGE OCULAR RO +<br/>Identity Preserving Face Completion for +<br/>Large Ocular Region Occlusion +<br/>1 Computer Science Department +<br/><b>University of Kentucky</b><br/>Lexington, KY, USA +<br/><b>Institute for Creative Technologies</b><br/><b>University of Southern California</b><br/>Playa Vista, California, USA +<br/>3 School of Computer Science and +<br/>Technology +<br/><b>Harbin Institute of Technology</b><br/>Harbin, China +<br/><b>Hangzhou Institute of Service</b><br/>Engineering +<br/><b>Hangzhou Normal University</b><br/>Hangzhou, China +</td><td>('2613340', 'Yajie Zhao', 'yajie zhao')<br/>('47483055', 'Weikai Chen', 'weikai chen')<br/>('1780032', 'Jun Xing', 'jun xing')<br/>('21515518', 'Xiaoming Li', 'xiaoming li')<br/>('3408065', 'Zach Bessinger', 'zach bessinger')<br/>('1752129', 'Fuchang Liu', 'fuchang liu')<br/>('1724520', 'Wangmeng Zuo', 'wangmeng zuo')<br/>('38958903', 'Ruigang Yang', 'ruigang yang')</td><td>yajie.zhao@uky.edu +<br/>wechen@ict.usc.edu +<br/>junxnui@gmail.com +<br/>hit.xmshr@gmail.com +<br/>zach.bessinger@gmail.com +<br/>20140022@hznu.edu.cn +<br/>cswmzuo@gmail.com +<br/>ryang@cs.uky.edu </td></tr><tr><td>b7cf7bb574b2369f4d7ebc3866b461634147041a</td><td>Neural Comput & Applic (2012) 21:1575–1583 <br/>DOI 10.1007/s00521-011-0728-x <br/>O R I G I N A L A R T I C L E @@ -27724,12 +34741,36 @@ <br/>Received: 2 August 2010 / Accepted: 3 August 2011 / Published online: 19 August 2011 <br/>Ó Springer-Verlag London Limited 2011 </td><td>('1692984', 'Jun Yin', 'jun yin')</td><td></td></tr><tr><td>b750b3d8c34d4e57ecdafcd5ae8a15d7fa50bc24</td><td>Unified Solution to Nonnegative Data Factorization Problems -<br/><b>Huazhong University of Science and Technology, Wuhan, China</b><br/><b>National University of Singapore, Singapore</b></td><td>('1817910', 'Xiaobai Liu', 'xiaobai liu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('2156156', 'Hai Jin', 'hai jin')</td><td></td></tr><tr><td>b7eead8586ffe069edd190956bd338d82c69f880</td><td>A VIDEO DATABASE FOR FACIAL +<br/><b>Huazhong University of Science and Technology, Wuhan, China</b><br/><b>National University of Singapore, Singapore</b></td><td>('1817910', 'Xiaobai Liu', 'xiaobai liu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('2156156', 'Hai Jin', 'hai jin')</td><td></td></tr><tr><td>b7894c1f805ffd90ab4ab06002c70de68d6982ab</td><td>Biomedical Research 2017; Special Issue: S610-S618 +<br/>ISSN 0970-938X +<br/>www.biomedres.info +<br/>A comprehensive age estimation on face images using hybrid filter based +<br/>feature extraction. +<br/>Karthikeyan D1*, Balakrishnan G2 +<br/><b>Srinivasan Engineering College, Perambalur, India</b><br/><b>Indra Ganesan College of Engineering, Trichy, India</b></td><td></td><td></td></tr><tr><td>b7eead8586ffe069edd190956bd338d82c69f880</td><td>A VIDEO DATABASE FOR FACIAL <br/>BEHAVIOR UNDERSTANDING <br/>D. Freire-Obreg´on and M. Castrill´on-Santana. <br/>SIANI, Universidad de Las Palmas de Gran Canaria, Spain </td><td></td><td>dfreire@iusiani.ulpgc.es, mcastrillon@iusiani.ulpgc.es -</td></tr><tr><td>b75cee96293c11fe77ab733fc1147950abbe16f9</td><td></td><td></td><td></td></tr><tr><td>b7f05d0771da64192f73bdb2535925b0e238d233</td><td> MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan +</td></tr><tr><td>b75cee96293c11fe77ab733fc1147950abbe16f9</td><td></td><td></td><td></td></tr><tr><td>b7774c096dc18bb0be2acef07ff5887a22c2a848</td><td>Distance metric learning for image and webpage +<br/>comparison +<br/>To cite this version: +<br/>versité Pierre et Marie Curie - Paris VI, 2015. English. <NNT : 2015PA066019>. <tel-01135698v2> +<br/>HAL Id: tel-01135698 +<br/>https://tel.archives-ouvertes.fr/tel-01135698v2 +<br/>Submitted on 18 Mar 2015 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('32868306', 'Marc Teva Law', 'marc teva law')<br/>('32868306', 'Marc Teva Law', 'marc teva law')</td><td></td></tr><tr><td>b7f05d0771da64192f73bdb2535925b0e238d233</td><td> MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan <br/>4-3 <br/>Robust Active Shape Model using AdaBoosted Histogram Classifiers <br/>W ataru Ito @@ -27744,6 +34785,9 @@ <br/>aDept. of Brain and Cognitive Eng. Korea Univ., Seoul, Korea <br/>bDept. of Comp. Sci. & Eng. Michigan State Univ., E. Lansing, MI, USA 48824 </td><td>('2429013', 'Hyunju Maeng', 'hyunju maeng')<br/>('2131755', 'Hyun-Cheol Choi', 'hyun-cheol choi')<br/>('2222919', 'Unsang Park', 'unsang park')<br/>('1703007', 'Seong-Whan Lee', 'seong-whan lee')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td>{hjmaeng, hcchoi}@korea.ac.kr, parkunsa@cse.msu.edu, swlee@image.korea.ac.kr , jain@cse.msu.edu +</td></tr><tr><td>b7820f3d0f43c2ce613ebb6c3d16eb893c84cf89</td><td>Visual Data Synthesis via GAN for Zero-Shot Video Classification +<br/><b>Institute of Computer Science and Technology, Peking University</b><br/>Beijing 100871, China +</td><td>('2439211', 'Chenrui Zhang', 'chenrui zhang')<br/>('1704081', 'Yuxin Peng', 'yuxin peng')</td><td>pengyuxin@pku.edu.cn </td></tr><tr><td>b7b461f82c911f2596b310e2b18dd0da1d5d4491</td><td>2961 <br/>2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) <br/>978-1-4799-2893-4/14/$31.00 ©2014 IEEE @@ -27756,7 +34800,8 @@ <br/>(cid:2) <br/>(cid:3) <br/>(cid:4) -</td><td>('3149531', 'Arthur Szlam', 'arthur szlam')</td><td></td></tr><tr><td>b73fdae232270404f96754329a1a18768974d3f6</td><td></td><td></td><td></td></tr><tr><td>b7c5f885114186284c51e863b58292583047a8b4</td><td>GAdaBoost: Accelerating Adaboost Feature Selection with Genetic +</td><td>('3149531', 'Arthur Szlam', 'arthur szlam')</td><td></td></tr><tr><td>b73fdae232270404f96754329a1a18768974d3f6</td><td></td><td></td><td></td></tr><tr><td>b76af8fcf9a3ebc421b075b689defb6dc4282670</td><td>Face Mask Extraction in Video Sequence +</td><td>('2563750', 'Yujiang Wang', 'yujiang wang')</td><td></td></tr><tr><td>b7c5f885114186284c51e863b58292583047a8b4</td><td>GAdaBoost: Accelerating Adaboost Feature Selection with Genetic <br/>Algorithms <br/><b>The American University In Cairo, Road 90, New Cairo, Cairo, Egypt</b><br/>Keywords: <br/>Object Detection, Genetic Algorithms, Haar Features, Adaboost, Face Detection. @@ -27782,7 +34827,11 @@ <br/>Handling missing weak classifiers in boosted <br/>cascade: application to multiview and <br/>occluded face detection -</td><td>('3212236', 'Pierre Bouges', 'pierre bouges')<br/>('1865978', 'Thierry Chateau', 'thierry chateau')<br/>('32323470', 'Christophe Blanc', 'christophe blanc')<br/>('1685767', 'Gaëlle Loosli', 'gaëlle loosli')</td><td></td></tr><tr><td>db1f48a7e11174d4a724a4edb3a0f1571d649670</td><td>Joint Constrained Clustering and Feature +</td><td>('3212236', 'Pierre Bouges', 'pierre bouges')<br/>('1865978', 'Thierry Chateau', 'thierry chateau')<br/>('32323470', 'Christophe Blanc', 'christophe blanc')<br/>('1685767', 'Gaëlle Loosli', 'gaëlle loosli')</td><td></td></tr><tr><td>db848c3c32464d12da33b2f4c3a29fe293fc35d1</td><td>Pose Guided Human Video Generation +<br/>1 CUHK-SenseTime Joint Lab, CUHK, Hong Kong S.A.R. +<br/>2 SenseTime Research, Beijing, China +<br/><b>Carnegie Mellon University</b></td><td>('49984891', 'Ceyuan Yang', 'ceyuan yang')<br/>('1915826', 'Zhe Wang', 'zhe wang')<br/>('22689408', 'Xinge Zhu', 'xinge zhu')<br/>('2000034', 'Chen Huang', 'chen huang')<br/>('1788070', 'Jianping Shi', 'jianping shi')<br/>('1807606', 'Dahua Lin', 'dahua lin')</td><td>yangceyuan@sensetime.com +</td></tr><tr><td>db1f48a7e11174d4a724a4edb3a0f1571d649670</td><td>Joint Constrained Clustering and Feature <br/>Learning based on Deep Neural Networks <br/>by <br/><b>B.Sc., University of Science and Technology of China</b><br/>Thesis Submitted in Partial Fulfillment of the @@ -27803,13 +34852,48 @@ <br/>Volume 4, Issue 6 (June 2015), PP.169-169-174 <br/>Characteristic Based Image Search using Re-Ranking method <br/>1Chitti Babu, 2Yasmeen Jaweed, 3G.Vijay Kumar -<br/><b></b></td><td></td><td></td></tr><tr><td>dbaf89ca98dda2c99157c46abd136ace5bdc33b3</td><td>Nonlinear Cross-View Sample Enrichment for +<br/><b></b></td><td></td><td></td></tr><tr><td>dbb16032dd8f19bdfd045a1fc0fc51f29c70f70a</td><td>PARKHI et al.: DEEP FACE RECOGNITION +<br/>Deep Face Recognition +<br/>Visual Geometry Group +<br/>Department of Engineering Science +<br/><b>University of Oxford</b></td><td>('3188342', 'Omkar M. Parkhi', 'omkar m. parkhi')<br/>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>omkar@robots.ox.ac.uk +<br/>vedaldi@robots.ox.ac.uk +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>dbaf89ca98dda2c99157c46abd136ace5bdc33b3</td><td>Nonlinear Cross-View Sample Enrichment for <br/>Action Recognition <br/>Institut Mines-T´el´ecom; T´el´ecom ParisTech; CNRS LTCI -</td><td>('1695223', 'Ling Wang', 'ling wang')<br/>('1692389', 'Hichem Sahbi', 'hichem sahbi')</td><td></td></tr><tr><td>dbab6ac1a9516c360cdbfd5f3239a351a64adde7</td><td></td><td></td><td></td></tr><tr><td>dbb0a527612c828d43bcb9a9c41f1bf7110b1dc8</td><td>Chapter 7 +</td><td>('1695223', 'Ling Wang', 'ling wang')<br/>('1692389', 'Hichem Sahbi', 'hichem sahbi')</td><td></td></tr><tr><td>dbab6ac1a9516c360cdbfd5f3239a351a64adde7</td><td></td><td></td><td></td></tr><tr><td>dbe255d3d2a5d960daaaba71cb0da292e0af36a7</td><td>Evolutionary Cost-sensitive Extreme Learning +<br/>Machine +<br/>1 +</td><td>('36904370', 'Lei Zhang', 'lei zhang')</td><td></td></tr><tr><td>dbb0a527612c828d43bcb9a9c41f1bf7110b1dc8</td><td>Chapter 7 <br/>Machine Learning Techniques <br/>for Face Analysis -</td><td>('9301018', 'Roberto Valenti', 'roberto valenti')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')<br/>('1774778', 'Ira Cohen', 'ira cohen')</td><td></td></tr><tr><td>dba493caf6647214c8c58967a8251641c2bda4c2</td><td>Automatic 3D Facial Expression Editing in Videos +</td><td>('9301018', 'Roberto Valenti', 'roberto valenti')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')<br/>('1774778', 'Ira Cohen', 'ira cohen')</td><td></td></tr><tr><td>db5a00984fa54b9d2a1caad0067a9ff0d0489517</td><td>Multi-Task Adversarial Network for Disentangled Feature Learning +<br/>Ian Wassell1 +<br/><b>University of Cambridge</b><br/>2Adobe Research +</td><td>('49421489', 'Yang Liu', 'yang liu')<br/>('48707577', 'Zhaowen Wang', 'zhaowen wang')</td><td>1{yl504,ijw24}@cam.ac.uk +<br/>2{zhawang,hljin}@adobe.com +</td></tr><tr><td>dbd958ffedc3eae8032be67599ec281310c05630</td><td>Automated Restyling of Human Portrait Based on Facial Expression Recognition +<br/>and 3D Reconstruction +<br/><b>Stanford University</b><br/>350 Serra Mall, Stanford, CA 94305, USA +</td><td>('46740443', 'Cheng-Han Wu', 'cheng-han wu')</td><td>1chw0208@stanford.edu +<br/>2hsinc@stanford.edu +</td></tr><tr><td>dbed26cc6d818b3679e46677abc9fa8e04e8c6a6</td><td>A Hierarchical Generative Model for Eye Image Synthesis and Eye Gaze +<br/>Estimation +<br/><b>ECSE, Rensselaer Polytechnic Institute, Troy, NY, USA</b></td><td>('1771700', 'Kang Wang', 'kang wang')<br/>('49832825', 'Rui Zhao', 'rui zhao')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>{wangk10, zhaor, jiq}@rpi.edu +</td></tr><tr><td>db3545a983ffd24c97c18bf7f068783102548ad7</td><td>Enriching the Student Model in an +<br/>Intelligent Tutoring System +<br/>Submitted in partial fulfillment of the requirements for the degree +<br/>of Doctor of Philosophy +<br/>of the +<br/><b>Indian Institute of Technology, Bombay, India</b><br/>and +<br/><b>Monash University, Australia</b><br/>by +<br/>Supervisors: +<br/>The course of study for this award was developed jointly by +<br/><b>the Indian Institute of Technology, Bombay and Monash University, Australia</b><br/>and given academic recognition by each of them. +<br/>The programme was administered by The IITB-Monash Research Academy. +<br/>2014 +</td><td>('2844237', 'Ramkumar Rajendran', 'ramkumar rajendran')<br/>('1946438', 'Sridhar Iyer', 'sridhar iyer')<br/>('1791910', 'Sahana Murthy', 'sahana murthy')<br/>('38751653', 'Campbell Wilson', 'campbell wilson')<br/>('1727078', 'Judithe Sheard', 'judithe sheard')</td><td></td></tr><tr><td>dba493caf6647214c8c58967a8251641c2bda4c2</td><td>Automatic 3D Facial Expression Editing in Videos <br/><b>University of California, Santa Barbara</b><br/>2IMPA – Instituto de Matematica Pura e Aplicada </td><td>('13303219', 'Ya Chang', 'ya chang')<br/>('2428542', 'Marcelo Vieira', 'marcelo vieira')<br/>('1752714', 'Matthew Turk', 'matthew turk')<br/>('1705620', 'Luiz Velho', 'luiz velho')</td><td></td></tr><tr><td>dbb7f37fb9b41d1aa862aaf2d2e721a470fd2c57</td><td>Face Image Analysis With <br/>Convolutional Neural Networks @@ -27842,16 +34926,24 @@ <br/><b>UniversityofMaryland</b><br/>Princeton,NJ <br/><b>CollegePark, MD</b></td><td></td><td>Email:wzhao@sarno(cid:11).com <br/>Email:rama@cfar.umd.edu -</td></tr><tr><td>db82f9101f64d396a86fc2bd05b352e433d88d02</td><td>A Spatio-Temporal Probabilistic Framework for +</td></tr><tr><td>db67edbaeb78e1dd734784cfaaa720ba86ceb6d2</td><td>SPECFACE - A Dataset of Human Faces Wearing Spectacles +<br/><b>Indian Institute of Technology Kharagpur</b><br/>India +</td><td>('30654921', 'Anirban Dasgupta', 'anirban dasgupta')<br/>('30572870', 'Shubhobrata Bhattacharya', 'shubhobrata bhattacharya')<br/>('2680543', 'Aurobinda Routray', 'aurobinda routray')</td><td></td></tr><tr><td>db82f9101f64d396a86fc2bd05b352e433d88d02</td><td>A Spatio-Temporal Probabilistic Framework for <br/>Dividing and Predicting Facial Action Units <br/><b>Electrical and Computer Engineering, The University of Memphis</b></td><td>('2497319', 'Md. Iftekhar Tanveer', 'md. iftekhar tanveer')<br/>('1828610', 'Mohammed Yeasin', 'mohammed yeasin')</td><td></td></tr><tr><td>db428d03e3dfd98624c23e0462817ad17ef14493</td><td>Oxford TRECVID 2006 – Notebook paper <br/>Department of Engineering Science <br/><b>University of Oxford</b><br/>United Kingdom </td><td>('2276542', 'James Philbin', 'james philbin')<br/>('8873555', 'Anna Bosch', 'anna bosch')<br/>('1720149', 'Jan-Mark Geusebroek', 'jan-mark geusebroek')<br/>('1782755', 'Josef Sivic', 'josef sivic')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td></td></tr><tr><td>a83fc450c124b7e640adc762e95e3bb6b423b310</td><td>Deep Face Feature for Face Alignment -</td><td>('15679675', 'Boyi Jiang', 'boyi jiang')<br/>('2938279', 'Juyong Zhang', 'juyong zhang')<br/>('2964129', 'Bailin Deng', 'bailin deng')<br/>('8280113', 'Yudong Guo', 'yudong guo')<br/>('1724542', 'Ligang Liu', 'ligang liu')</td><td></td></tr><tr><td>a8117a4733cce9148c35fb6888962f665ae65b1e</td><td>IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. XX, XX 201X +</td><td>('15679675', 'Boyi Jiang', 'boyi jiang')<br/>('2938279', 'Juyong Zhang', 'juyong zhang')<br/>('2964129', 'Bailin Deng', 'bailin deng')<br/>('8280113', 'Yudong Guo', 'yudong guo')<br/>('1724542', 'Ligang Liu', 'ligang liu')</td><td></td></tr><tr><td>a85e9e11db5665c89b057a124547377d3e1c27ef</td><td>Dynamics of Driver’s Gaze: Explorations in +<br/>Behavior Modeling & Maneuver Prediction +</td><td>('1841835', 'Sujitha Martin', 'sujitha martin')<br/>('22254044', 'Sourabh Vora', 'sourabh vora')<br/>('2812409', 'Kevan Yuen', 'kevan yuen')</td><td></td></tr><tr><td>a8117a4733cce9148c35fb6888962f665ae65b1e</td><td>IEEE TRANSACTIONS ON XXXX, VOL. XX, NO. XX, XX 201X <br/>A Good Practice Towards Top Performance of Face <br/>Recognition: Transferred Deep Feature Fusion -</td><td>('33419682', 'Lin Xiong', 'lin xiong')<br/>('1785111', 'Jayashree Karlekar', 'jayashree karlekar')<br/>('2052311', 'Jian Zhao', 'jian zhao')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('2668358', 'Sugiri Pranata', 'sugiri pranata')<br/>('3493398', 'Shengmei Shen', 'shengmei shen')</td><td></td></tr><tr><td>a820941eaf03077d68536732a4d5f28d94b5864a</td><td>Leveraging Datasets with Varying Annotations for Face Alignment +</td><td>('33419682', 'Lin Xiong', 'lin xiong')<br/>('1785111', 'Jayashree Karlekar', 'jayashree karlekar')<br/>('2052311', 'Jian Zhao', 'jian zhao')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('2668358', 'Sugiri Pranata', 'sugiri pranata')<br/>('3493398', 'Shengmei Shen', 'shengmei shen')</td><td></td></tr><tr><td>a87ab836771164adb95d6744027e62e05f47fd96</td><td>Understanding human-human interactions: a survey +<br/><b>Utrecht University, Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands</b><br/><b>Utrecht University, Buys Ballotgebouw, Princetonplein 5, Utrecht, 3584CC, Netherlands</b></td><td>('26936326', 'Alexandros Stergiou', 'alexandros stergiou')<br/>('1754666', 'Ronald Poppe', 'ronald poppe')</td><td></td></tr><tr><td>a896ddeb0d253739c9aaef7fc1f170a2ba8407d3</td><td>SSH: Single Stage Headless Face Detector +<br/><b>University of Maryland</b></td><td>('40465379', 'Mahyar Najibi', 'mahyar najibi')<br/>('3383048', 'Pouya Samangouei', 'pouya samangouei')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td>{pouya,rama,lsd}@umiacs.umd.edu +<br/>najibi@cs.umd.edu +</td></tr><tr><td>a820941eaf03077d68536732a4d5f28d94b5864a</td><td>Leveraging Datasets with Varying Annotations for Face Alignment <br/>via Deep Regression Network <br/>1Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), <br/><b>Institute of Computing Technology, CAS, Beijing 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b><br/>3CAS Center for Excellence in Brain Science and Intelligence Technology @@ -27909,7 +35001,31 @@ <br/>Simultaneously Learning Neighborship and <br/>Projection Matrix for Supervised <br/>Dimensionality Reduction -</td><td>('34116743', 'Yanwei Pang', 'yanwei pang')<br/>('2521321', 'Bo Zhou', 'bo zhou')<br/>('1688370', 'Feiping Nie', 'feiping nie')</td><td></td></tr><tr><td>a8638a07465fe388ae5da0e8a68e62a4ee322d68</td><td>How to predict the global instantaneous feeling induced +</td><td>('34116743', 'Yanwei Pang', 'yanwei pang')<br/>('2521321', 'Bo Zhou', 'bo zhou')<br/>('1688370', 'Feiping Nie', 'feiping nie')</td><td></td></tr><tr><td>a803453edd2b4a85b29da74dcc551b3c53ff17f9</td><td>Pose Invariant Face Recognition Under Arbitrary +<br/>Illumination Based on 3D Face Reconstruction +<br/><b>School of Computer Science and Technology, Harbin Institute of Technology</b><br/>150001 Harbin, China +<br/>2 ICT-ISVISION Joint R&D Lab for Face Recognition, ICT, CAS, 100080 Beijing, China +</td><td>('1695600', 'Xiujuan Chai', 'xiujuan chai')<br/>('2343895', 'Laiyun Qing', 'laiyun qing')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')<br/>('1698902', 'Wen Gao', 'wen gao')</td><td>{xjchai,xlchen,wgao}@jdl.ac.cn +<br/>{lyqing,sgshan}@jdl.ac.cn +</td></tr><tr><td>a8a30a8c50d9c4bb8e6d2dd84bc5b8b7f2c84dd8</td><td>This is a repository copy of Modelling of Orthogonal Craniofacial Profiles. +<br/>White Rose Research Online URL for this paper: +<br/>http://eprints.whiterose.ac.uk/131767/ +<br/>Version: Published Version +<br/>Article: +<br/>Dai, Hang, Pears, Nicholas Edwin orcid.org/0000-0001-9513-5634 and Duncan, Christian +<br/>(2017) Modelling of Orthogonal Craniofacial Profiles. Journal of Imaging. ISSN 2313-433X +<br/>https://doi.org/10.3390/jimaging3040055 +<br/>Reuse +<br/>This article is distributed under the terms of the Creative Commons Attribution (CC BY) licence. This licence +<br/>allows you to distribute, remix, tweak, and build upon the work, even commercially, as long as you credit the +<br/>authors for the original work. More information and the full terms of the licence here: +<br/>https://creativecommons.org/licenses/ +<br/>Takedown +<br/>If you consider content in White Rose Research Online to be in breach of UK law, please notify us by +<br/>https://eprints.whiterose.ac.uk/ +</td><td></td><td>emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. +<br/>eprints@whiterose.ac.uk +</td></tr><tr><td>a8638a07465fe388ae5da0e8a68e62a4ee322d68</td><td>How to predict the global instantaneous feeling induced <br/>by a facial picture? <br/>To cite this version: <br/>feeling induced by a facial picture?. Signal Processing: Image Communication, Elsevier, 2015, @@ -27930,7 +35046,9 @@ <br/>publics ou priv´es. </td><td>('25030249', 'Arnaud Lienhard', 'arnaud lienhard')<br/>('2216412', 'Patricia Ladret', 'patricia ladret')<br/>('1788869', 'Alice Caplier', 'alice caplier')<br/>('25030249', 'Arnaud Lienhard', 'arnaud lienhard')<br/>('2216412', 'Patricia Ladret', 'patricia ladret')<br/>('1788869', 'Alice Caplier', 'alice caplier')</td><td></td></tr><tr><td>a8e75978a5335fd3deb04572bb6ca43dbfad4738</td><td>Sparse Graphical Representation based Discriminant <br/>Analysis for Heterogeneous Face Recognition -</td><td>('2299758', 'Chunlei Peng', 'chunlei peng')<br/>('10699750', 'Xinbo Gao', 'xinbo gao')<br/>('2870173', 'Nannan Wang', 'nannan wang')<br/>('38158055', 'Jie Li', 'jie li')</td><td></td></tr><tr><td>a8583e80a455507a0f146143abeb35e769d25e4e</td><td>A DISTANCE-ACCURACY HYBRID WEIGHTED VOTING SCHEME +</td><td>('2299758', 'Chunlei Peng', 'chunlei peng')<br/>('10699750', 'Xinbo Gao', 'xinbo gao')<br/>('2870173', 'Nannan Wang', 'nannan wang')<br/>('38158055', 'Jie Li', 'jie li')</td><td></td></tr><tr><td>a8d52265649c16f95af71d6f548c15afc85ac905</td><td>Situation Recognition with Graph Neural Networks +<br/><b>The Chinese University of Hong Kong, 2University of Toronto, 3Youtu Lab, Tencent</b><br/><b>Uber Advanced Technologies Group, 5Vector Institute</b></td><td>('8139953', 'Ruiyu Li', 'ruiyu li')<br/>('2103464', 'Makarand Tapaswi', 'makarand tapaswi')<br/>('2246396', 'Renjie Liao', 'renjie liao')<br/>('1729056', 'Jiaya Jia', 'jiaya jia')<br/>('2422559', 'Raquel Urtasun', 'raquel urtasun')<br/>('37895334', 'Sanja Fidler', 'sanja fidler')</td><td>ryli@cse.cuhk.edu.hk, {makarand,rjliao,urtasun,fidler}@cs.toronto.edu, leojia9@gmail.com +</td></tr><tr><td>a8583e80a455507a0f146143abeb35e769d25e4e</td><td>A DISTANCE-ACCURACY HYBRID WEIGHTED VOTING SCHEME <br/>FOR PARTIAL FACE RECOGNITION <br/>1Dept. of Information Engineering and Computer Science, <br/><b>Feng Chia University, Taichung, Taiwan</b><br/>2Department of Photonics, @@ -27960,6 +35078,34 @@ <br/>heesung.kwon.civ@mail.mil <br/>nasser.nasrabadi@mail.wvu.edu <br/>rama@umiacs.umd.edu +</td></tr><tr><td>a8a61badec9b8bc01f002a06e1426a623456d121</td><td>JOINT SPATIO-TEMPORAL ACTION LOCALIZATION +<br/>IN UNTRIMMED VIDEOS WITH PER-FRAME SEGMENTATION +<br/><b>Xi an Jiaotong University</b><br/>2HERE Technologies +<br/>3Alibaba Group +<br/>4Microsoft Research +</td><td>('46809347', 'Xuhuan Duan', 'xuhuan duan')<br/>('40367806', 'Le Wang', 'le wang')<br/>('51262903', 'Changbo Zhai', 'changbo zhai')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('1786361', 'Zhenxing Niu', 'zhenxing niu')<br/>('1715389', 'Nanning Zheng', 'nanning zheng')<br/>('1745420', 'Gang Hua', 'gang hua')</td><td></td></tr><tr><td>a8154d043f187c6640cb6aedeaa8385a323e46cf</td><td>MURRUGARRA, KOVASHKA: IMAGE RETRIEVAL WITH MIXED INITIATIVE +<br/>Image Retrieval with Mixed Initiative and +<br/>Multimodal Feedback +<br/>Department of Computer Science +<br/><b>University of Pittsburgh</b><br/>Pittsburgh, PA, USA +</td><td>('1916866', 'Nils Murrugarra-Llerena', 'nils murrugarra-llerena')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td>nineil@cs.pitt.edu +<br/>kovashka@cs.pitt.edu +</td></tr><tr><td>a812368fe1d4a186322bf72a6d07e1cf60067234</td><td><b>Imperial College London</b><br/>Department of Computing +<br/>Gaussian Processes +<br/>for Modeling of Facial Expressions +<br/>September, 2016 +<br/>Supervised by Prof. Maja Pantic +<br/>Submitted in part fulfilment of the requirements for the degree of PhD in Computing and +<br/><b>the Diploma of Imperial College London. This thesis is entirely my own work, and, except</b><br/>where otherwise indicated, describes my own research. +</td><td>('2308430', 'Stefanos Eleftheriadis', 'stefanos eleftheriadis')</td><td></td></tr><tr><td>de7f5e4ccc2f38e0c8f3f72a930ae1c43e0fdcf0</td><td>Merge or Not? Learning to Group Faces via Imitation Learning +<br/>SenseTime +<br/>SenseTime +<br/>SenseTime +<br/>Chen Chang Loy +<br/><b>The Chinese University of Hong Kong</b></td><td>('49990550', 'Yue He', 'yue he')<br/>('9963152', 'Kaidi Cao', 'kaidi cao')<br/>('46651787', 'Cheng Li', 'cheng li')</td><td>heyue@sensetime.com +<br/>caokaidi@sensetime.com +<br/>chengli@sensetime.com +<br/>ccloy@ie.cuhk.edu.hk </td></tr><tr><td>de8381903c579a4fed609dff3e52a1dc51154951</td><td><b>Graz University of Technology</b><br/><b>Institute for Computer Graphics and Vision</b><br/>Dissertation <br/>Shape and Appearance Based Analysis <br/>of Facial Images for Assessing ICAO @@ -27968,7 +35114,22 @@ <br/>Thesis supervisors <br/>Prof. Dr. Horst Bischof <br/>Prof. Dr. Fernando De la Torre -</td><td>('3464430', 'Markus Storer', 'markus storer')</td><td></td></tr><tr><td>de15af84b1257211a11889b6c2adf0a2bcf59b42</td><td>Anomaly Detection in Non-Stationary and +</td><td>('3464430', 'Markus Storer', 'markus storer')</td><td></td></tr><tr><td>ded968b97bd59465d5ccda4f1e441f24bac7ede5</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Large scale 3D Morphable Models +<br/>Zafeiriou +<br/>Received: date / Accepted: date +</td><td>('47456731', 'James Booth', 'james booth')</td><td></td></tr><tr><td>de0eb358b890d92e8f67592c6e23f0e3b2ba3f66</td><td>ACCEPTED BY IEEE TRANS. PATTERN ANAL. AND MACH. INTELL. +<br/>Inference-Based Similarity Search in +<br/>Randomized Montgomery Domains for +<br/>Privacy-Preserving Biometric Identification +</td><td>('46393453', 'Yi Wang', 'yi wang')<br/>('2087574', 'Jianwu Wan', 'jianwu wan')<br/>('39954962', 'Jun Guo', 'jun guo')<br/>('32840387', 'Yiu-ming Cheung', 'yiu-ming cheung')</td><td></td></tr><tr><td>def569db592ed1715ae509644444c3feda06a536</td><td>Discovery and usage of joint attention in images +<br/><b>Weizmann Institute of Science, Rehovot, Israel</b><br/><b>The Center for Brains, Minds and Machines, Massachusetts Institute of Technology, Cambridge, MA USA</b><br/><b>Massachusetts Institute of Technology, Cambridge, MA USA</b><br/><b>Weizmann Institute of Science, Rehovot, Israel</b></td><td></td><td>Daniel Harari (hararid@weizmann.ac.il) +<br/>Joshua B. Tenenbaum (jbt@mit.edu) +<br/>Shimon Ullman (shimon.ullman@weizmann.ac.il) +</td></tr><tr><td>dee406a7aaa0f4c9d64b7550e633d81bc66ff451</td><td>Content-Adaptive Sketch Portrait Generation by +<br/>Decompositional Representation Learning +</td><td>('8335563', 'Dongyu Zhang', 'dongyu zhang')<br/>('1737218', 'Liang Lin', 'liang lin')<br/>('1765674', 'Tianshui Chen', 'tianshui chen')<br/>('1738906', 'Xian Wu', 'xian wu')<br/>('1989769', 'Wenwei Tan', 'wenwei tan')<br/>('1732655', 'Ebroul Izquierdo', 'ebroul izquierdo')</td><td></td></tr><tr><td>de15af84b1257211a11889b6c2adf0a2bcf59b42</td><td>Anomaly Detection in Non-Stationary and <br/>Distributed Environments <br/>Colin O’Reilly <br/>Submitted for the Degree of @@ -27978,18 +35139,112 @@ <br/><b>University of Surrey</b><br/>Guildford, Surrey GU2 7XH, U.K. <br/>November 2014 <br/>© Colin O’Reilly 2014 -</td><td></td><td></td></tr><tr><td>dedabf9afe2ae4a1ace1279150e5f1d495e565da</td><td>3294 +</td><td></td><td></td></tr><tr><td>de3285da34df0262a4548574c2383c51387a24bf</td><td>Two-Stream Convolutional Networks for Dynamic Texture Synthesis +<br/>Department of Electrical Engineering and Computer Science +<br/><b>York University, Toronto</b></td><td>('19251410', 'Matthew Tesfaldet', 'matthew tesfaldet')</td><td>{mtesfald,mab}@eecs.yorku.ca +</td></tr><tr><td>dedabf9afe2ae4a1ace1279150e5f1d495e565da</td><td>3294 <br/>Robust Face Recognition With Structurally <br/>Incoherent Low-Rank Matrix Decomposition -</td><td>('2017922', 'Chia-Po Wei', 'chia-po wei')<br/>('2624492', 'Chih-Fan Chen', 'chih-fan chen')<br/>('2733735', 'Yu-Chiang Frank Wang', 'yu-chiang frank wang')</td><td></td></tr><tr><td>de398bd8b7b57a3362c0c677ba8bf9f1d8ade583</td><td>Hierarchical Bayesian Theme Models for +</td><td>('2017922', 'Chia-Po Wei', 'chia-po wei')<br/>('2624492', 'Chih-Fan Chen', 'chih-fan chen')<br/>('2733735', 'Yu-Chiang Frank Wang', 'yu-chiang frank wang')</td><td></td></tr><tr><td>dec0c26855da90876c405e9fd42830c3051c2f5f</td><td>Supplementary Material: Learning Compositional Visual Concepts with Mutual +<br/>Consistency +<br/><b>School of Electrical and Computer Engineering, Cornell University, Ithaca NY</b><br/>3Siemens Corporate Technology, Princeton NJ +<br/>Contents +<br/>1. Objective functions +<br/>1.1. Adversarial loss +<br/>1.2. Extended cycle-consistency loss . +<br/>1.3. Commutative loss +<br/>. . . +<br/>. . . +<br/>. . . +<br/>2. Additional implementation details +<br/>3. Additional results +<br/>4. Discussion +<br/>5. Generalizing ConceptGAN +<br/>5.1. Assumption: Concepts have distinct states . . +<br/>5.2. Assumption: Concepts are mutually compatible +<br/>5.3. Generalization . +<br/>. . . +<br/>1. Objective functions +<br/>In this section, we provide complete mathematical +<br/>expressions for each of the three terms in our loss func- +<br/>tion, following the notation defined in Section 3 of the main +<br/>paper and the assumption that no training data is available +<br/>in subdomain Σ11. +<br/>1.1. Adversarial loss +<br/>For generator G1 and discriminator D10, for example, +<br/>the adversarial loss is expressed as: +<br/>Ladv(G1, D10, Σ00, Σ10) = Eσ10∼P10 [log D10(σ10)] +<br/>+Eσ00∼P00[log(1 − D10(G1(σ00)))] +<br/>(1) +<br/>where the generator G1 and discriminator D10 are +<br/>learned to optimize a minimax objective such that +<br/>G∗ +<br/>1 = arg min +<br/>G1 +<br/>max +<br/>D10 +<br/>Ladv(G1, D10, Σ00, Σ10) +<br/>(2) +<br/>For generator G2 and discriminator D01, the adversarial +<br/>loss is expressed as: +<br/>Ladv(G2, D01, Σ00, Σ01) = Eσ01∼P01 [log D01(σ01)] +<br/>+Eσ00∼P00[log(1 − D01(G2(σ00)))] +<br/>For generator F1 and discriminator D00, the adversarial +<br/>loss is expressed as: +<br/>Ladv(F1, D00, Σ10, Σ00) = Eσ00∼P00 [log D00(σ00)] +<br/>+Eσ10∼P10 [log(1 − D00(F1(σ10)))] +<br/>For generator F2 and discriminator D00, the adversarial +<br/>loss is expressed as: +<br/>Ladv(F2, D00, Σ01, Σ00) = Eσ00∼P00 [log D00(σ00)] +<br/>+Eσ01∼P01 [log(1 − D00(F2(σ01)))] +<br/>(5) +<br/>The overall adversarial loss LADV is the sum of these four +<br/>terms. +<br/>(3) +<br/>(4) +<br/>(6) +<br/>LADV =Ladv(G1, D10, Σ00, Σ10) +<br/>+ Ladv(G2, D01, Σ00, Σ01) +<br/>+ Ladv(F1, D00, Σ10, Σ00) +<br/>+ Ladv(F2, D00, Σ01, Σ00) +<br/>1.2. Extended cycle-consistency loss +<br/>Following our discussion in Section 3.2 of the main +<br/>paper, for any data sample σ00 in subdomain Σ00, a +<br/>distance-4 cycle consistency constraint is defined in the +<br/>clockwise direction (F2 ◦ F1 ◦ G2 ◦ G1)(σ00) ≈ σ00 and in +<br/>the counterclockwise direction (F1 ◦ F2 ◦ G1 ◦ G2)(σ00) ≈ +<br/>σ00. Such constraints are implemented by the penalty func- +<br/>tion: +<br/>Lcyc4(G, F, Σ00) +<br/>= Eσ00∼P00[(cid:107)(F2 ◦ F1 ◦ G2 ◦ G1)(σ00) − σ00(cid:107)1] +<br/>+ Eσ00∼P00[(cid:107)(F1 ◦ F2 ◦ G1 ◦ G2)(σ00) − σ00(cid:107)1]. +<br/>(7) +</td><td>('3303727', 'Yunye Gong', 'yunye gong')<br/>('1976152', 'Srikrishna Karanam', 'srikrishna karanam')<br/>('3311781', 'Ziyan Wu', 'ziyan wu')<br/>('2692770', 'Kuan-Chuan Peng', 'kuan-chuan peng')<br/>('39497207', 'Jan Ernst', 'jan ernst')<br/>('1767099', 'Peter C. Doerschuk', 'peter c. doerschuk')</td><td>{yg326,pd83}@cornell.edu,{first.last}@siemens.com +</td></tr><tr><td>de398bd8b7b57a3362c0c677ba8bf9f1d8ade583</td><td>Hierarchical Bayesian Theme Models for <br/>Multi-pose Facial Expression Recognition </td><td>('3069077', 'Qirong Mao', 'qirong mao')<br/>('1851510', 'Qiyu Rao', 'qiyu rao')<br/>('1770550', 'Yongbin Yu', 'yongbin yu')<br/>('1710341', 'Ming Dong', 'ming dong')</td><td></td></tr><tr><td>ded41c9b027c8a7f4800e61b7cfb793edaeb2817</td><td></td><td></td><td></td></tr><tr><td>defa8774d3c6ad46d4db4959d8510b44751361d8</td><td>FEBEI - Face Expression Based Emoticon Identification <br/>CS - B657 Computer Vision <br/>Robert J Henderson - rojahend -</td><td>('1854614', 'Nethra Chandrasekaran', 'nethra chandrasekaran')<br/>('1830695', 'Prashanth Kumar Murali', 'prashanth kumar murali')</td><td></td></tr><tr><td>b03b4d8b4190361ed2de66fcbb6fda0c9a0a7d89</td><td>Deep Alternative Neural Network: Exploring +</td><td>('1854614', 'Nethra Chandrasekaran', 'nethra chandrasekaran')<br/>('1830695', 'Prashanth Kumar Murali', 'prashanth kumar murali')</td><td></td></tr><tr><td>b0c512fcfb7bd6c500429cbda963e28850f2e948</td><td></td><td></td><td></td></tr><tr><td>b08203fca1af7b95fda8aa3d29dcacd182375385</td><td>OBJECT AND TEXT-GUIDED SEMANTICS FOR CNN-BASED ACTIVITY RECOGNITION +<br/><b>U.S. Army Research Laboratory, Adelphi, MD, USA</b><br/>§Booz Allen Hamilton Inc., McLean, VA, USA +</td><td>('3090299', 'Sungmin Eum', 'sungmin eum')<br/>('39412489', 'Christopher Reale', 'christopher reale')<br/>('1688527', 'Heesung Kwon', 'heesung kwon')<br/>('3202888', 'Claire Bonial', 'claire bonial')</td><td></td></tr><tr><td>b03b4d8b4190361ed2de66fcbb6fda0c9a0a7d89</td><td>Deep Alternative Neural Network: Exploring <br/>Contexts as Early as Possible for Action Recognition <br/><b>School of Electronics Engineering and Computer Science, Peking University</b><br/><b>School of Electronics and Computer Engineering, Peking University</b></td><td>('3258842', 'Jinzhuo Wang', 'jinzhuo wang')<br/>('1788029', 'Wenmin Wang', 'wenmin wang')<br/>('8082703', 'Xiongtao Chen', 'xiongtao chen')<br/>('1702330', 'Ronggang Wang', 'ronggang wang')<br/>('1698902', 'Wen Gao', 'wen gao')</td><td>jzwang@pku.edu.cn, wangwm@ece.pku.edu.cn <br/>cxt@pku.edu.cn, rgwang@ece.pku.edu.cn, wgao@pku.edu.cn +</td></tr><tr><td>b09b693708f412823053508578df289b8403100a</td><td>WANG et al.: TWO-STREAM SR-CNNS FOR ACTION RECOGNITION IN VIDEOS +<br/>Two-Stream SR-CNNs for Action +<br/>Recognition in Videos +<br/>1 Advanced Interactive Technologies Lab +<br/>ETH Zurich +<br/>Zurich, Switzerland +<br/>2 Computer Vision Lab +<br/>ETH Zurich +<br/>Zurich, Switzerland +</td><td>('46394691', 'Yifan Wang', 'yifan wang')<br/>('40403685', 'Jie Song', 'jie song')<br/>('33345248', 'Limin Wang', 'limin wang')<br/>('1681236', 'Luc Van Gool', 'luc van gool')<br/>('2531379', 'Otmar Hilliges', 'otmar hilliges')</td><td>yifan.wang@student.ethz.ch +<br/>jsong@inf.ethz.ch +<br/>07wanglimin@gmail.com +<br/>vangool@vision.ee.ethz.ch +<br/>otmar.hilliges@inf.ethz.ch </td></tr><tr><td>b013cce42dd769db754a57351d49b7410b8e82ad</td><td>Automatic Point-based Facial Trait Judgments Evaluation <br/>1Computer Vision Center, Edifici O, Campus UAB, Spain <br/>2Universitat Oberta de Catalunya, Rambla del Poblenou 156, 08018, Barcelona, Spain @@ -28003,7 +35258,14 @@ <br/>Combination of Local and Global Kernels <br/><b>The University of Electro-Communications</b><br/>1-5-1 Chofugaoka, Chofu-shi, Tokyo 182-8585, JAPAN </td><td>('2510362', 'Kazuhiro HOTTA', 'kazuhiro hotta')</td><td>hotta@ice.uec.ac.jp, -</td></tr><tr><td>b03d6e268cde7380e090ddaea889c75f64560891</td><td></td><td></td><td></td></tr><tr><td>b03446a2de01126e6a06eb5d526df277fa36099f</td><td>A Torch Library for Action Recognition and Detection Using CNNs and LSTMs +</td></tr><tr><td>b03d6e268cde7380e090ddaea889c75f64560891</td><td></td><td></td><td></td></tr><tr><td>b084683e5bab9b2bc327788e7b9a8e049d5fff8f</td><td>Using LIP to Gloss Over Faces in Single-Stage Face Detection +<br/>Networks +<br/><b>The University of Queensland, School of ITEE, QLD 4072, Australia</b></td><td>('1973322', 'Siqi Yang', 'siqi yang')<br/>('2331880', 'Arnold Wiliem', 'arnold wiliem')<br/>('3104113', 'Shaokang Chen', 'shaokang chen')<br/>('2270092', 'Brian C. Lovell', 'brian c. lovell')</td><td>{siqi.yang, a.wiliem, s.chen2}@uq.edu.au, lovell@itee.uq.edu.au +</td></tr><tr><td>b0c1615ebcad516b5a26d45be58068673e2ff217</td><td>How Image Degradations Affect Deep CNN-based Face +<br/>Recognition? +<br/>S¸amil Karahan1 Merve Kılınc¸ Yıldırım1 Kadir Kırtac¸1 Ferhat S¸ ¨ukr¨u Rende1 +<br/>G¨ultekin B¨ut¨un1Hazım Kemal Ekenel2 +</td><td></td><td></td></tr><tr><td>b03446a2de01126e6a06eb5d526df277fa36099f</td><td>A Torch Library for Action Recognition and Detection Using CNNs and LSTMs <br/><b>Stanford University</b></td><td>('4910251', 'Helen Jiang', 'helen jiang')</td><td>{gthung, helennn}@stanford.edu </td></tr><tr><td>b0de0892d2092c8c70aa22500fed31aa7eb4dd3f</td><td>(will be inserted by the editor) <br/>A robust and efficient video representation for action recognition @@ -28064,7 +35326,11 @@ <br/><b>Computational Biomedicine Lab, University of Houston, TX, USA</b></td><td>('39634395', 'Pengfei Dou', 'pengfei dou')<br/>('2461369', 'Yuhang Wu', 'yuhang wu')<br/>('2700399', 'Shishir K. Shah', 'shishir k. shah')<br/>('1706204', 'Ioannis A. Kakadiaris', 'ioannis a. kakadiaris')</td><td>{pengfei,yuhang}@cbl.uh.edu, {sshah,IKakadia}@central.uh.edu </td></tr><tr><td>a608c5f8fd42af6e9bd332ab516c8c2af7063c61</td><td>2408 <br/>Age Estimation via Grouping and Decision Fusion -</td><td>('3006921', 'Kuan-Hsien Liu', 'kuan-hsien liu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('9363144', 'C.-C. Jay Kuo', 'c.-c. jay kuo')</td><td></td></tr><tr><td>a6ffe238eaf8632b4a8a6f718c8917e7f3261546</td><td> Australasian Medical Journal [AMJ 2011, 4, 10, 555-562] +</td><td>('3006921', 'Kuan-Hsien Liu', 'kuan-hsien liu')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')<br/>('9363144', 'C.-C. Jay Kuo', 'c.-c. jay kuo')</td><td></td></tr><tr><td>a6e8a8bb99e30a9e80dbf80c46495cf798066105</td><td>Ranking Generative Adversarial Networks: +<br/>Subjective Control over Semantic Image Attributes +<br/><b>University of Bath</b></td><td>('41020280', 'Yassir Saquil', 'yassir saquil')<br/>('1808255', 'Kwang In Kim', 'kwang in kim')</td><td></td></tr><tr><td>a6eb6ad9142130406fb4ffd4d60e8348c2442c29</td><td>Video Description: A Survey of Methods, +<br/>Datasets and Evaluation Metrics +</td><td>('50978260', 'Nayyer Aafaq', 'nayyer aafaq')<br/>('1746166', 'Syed Zulqarnain Gilani', 'syed zulqarnain gilani')<br/>('46641573', 'Wei Liu', 'wei liu')<br/>('46332747', 'Ajmal Mian', 'ajmal mian')</td><td></td></tr><tr><td>a6ffe238eaf8632b4a8a6f718c8917e7f3261546</td><td> Australasian Medical Journal [AMJ 2011, 4, 10, 555-562] <br/>Dynamic Facial Prosthetics for Sufferers of Facial Paralysis <br/><b>Nottingham Trent University, Nottingham, UK</b><br/><b>Nottingham University Hospital, Nottingham, UK</b><br/> RESEARCH <br/> @@ -28103,10 +35369,29 @@ <br/><b>The Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel</b></td><td>('3294355', 'Orit Kliper-Gross', 'orit kliper-gross')<br/>('1756099', 'Tal Hassner', 'tal hassner')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td>orit.kliper@weizmann.ac.il <br/>hassner@openu.ac.il <br/>wolf@cs.tau.ac.il -</td></tr><tr><td>a694180a683f7f4361042c61648aa97d222602db</td><td>Face Recognition using Scattering Wavelet under Illicit Drug Abuse Variations +</td></tr><tr><td>a6590c49e44aa4975b2b0152ee21ac8af3097d80</td><td>https://doi.org/10.1007/s11263-018-1074-6 +<br/>3D Interpreter Networks for Viewer-Centered Wireframe Modeling +<br/>Received: date / Accepted: date +</td><td>('3045089', 'Jiajun Wu', 'jiajun wu')<br/>('1763295', 'Joshua B. Tenenbaum', 'joshua b. tenenbaum')</td><td></td></tr><tr><td>a694180a683f7f4361042c61648aa97d222602db</td><td>Face Recognition using Scattering Wavelet under Illicit Drug Abuse Variations <br/>IIIT-Delhi India </td><td>('2503967', 'Prateekshit Pandey', 'prateekshit pandey')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td>fprateekshit12078, rsingh, mayankg@iiitd.ac.in -</td></tr><tr><td>a6db73f10084ce6a4186363ea9d7475a9a658a11</td><td></td><td></td><td></td></tr><tr><td>a6634ff2f9c480e94ed8c01d64c9eb70e0d98487</td><td></td><td></td><td></td></tr><tr><td>a6b1d79bc334c74cde199e26a7ef4c189e9acd46</td><td>bioRxiv preprint first posted online Aug. 17, 2017; +</td></tr><tr><td>a6db73f10084ce6a4186363ea9d7475a9a658a11</td><td></td><td></td><td></td></tr><tr><td>a6e25cab2251a8ded43c44b28a87f4c62e3a548a</td><td>Let’s Dance: Learning From Online Dance Videos +<br/><b>Georgia Institute of Technology</b><br/>Irfan Essa +</td><td>('40333356', 'Daniel Castro', 'daniel castro')<br/>('2935619', 'Steven Hickson', 'steven hickson')<br/>('3430745', 'Patsorn Sangkloy', 'patsorn sangkloy')<br/>('40506496', 'Bhavishya Mittal', 'bhavishya mittal')<br/>('35459529', 'Sean Dai', 'sean dai')<br/>('1945508', 'James Hays', 'james hays')</td><td>shickson@gatech.edu +<br/>patsorn sangkloy@gatech.edu +<br/>dcastro9@gatech.edu +<br/>bmittal6@gatech.edu +<br/>sdai@gatech.edu +<br/>hays@gatech.edu +<br/>irfan@gatech.edu +</td></tr><tr><td>a6634ff2f9c480e94ed8c01d64c9eb70e0d98487</td><td></td><td></td><td></td></tr><tr><td>a6270914cf5f60627a1332bcc3f5951c9eea3be0</td><td>Joint Attention in Driver-Pedestrian Interaction: from +<br/>Theory to Practice +<br/>Department of Electrical Engineering and Computer Science +<br/><b>York University, Toronto, ON, Canada</b><br/>March 28, 2018 +</td><td>('26902477', 'Amir Rasouli', 'amir rasouli')<br/>('1727853', 'John K. Tsotsos', 'john k. tsotsos')</td><td>{aras,tsotsos}@eecs.yorku.ca +</td></tr><tr><td>a6ce2f0795839d9c2543d64a08e043695887e0eb</td><td>Driver Gaze Region Estimation +<br/>Without Using Eye Movement +<br/><b>Massachusetts Institute of Technology (MIT</b></td><td>('49925254', 'Philipp Langhans', 'philipp langhans')<br/>('7137846', 'Joonbum Lee', 'joonbum lee')<br/>('1901227', 'Bryan Reimer', 'bryan reimer')</td><td></td></tr><tr><td>a6b1d79bc334c74cde199e26a7ef4c189e9acd46</td><td>bioRxiv preprint first posted online Aug. 17, 2017; <br/>doi: <br/>http://dx.doi.org/10.1101/177196 <br/>. @@ -28132,9 +35417,90 @@ </td><td>('13403748', 'Md. Abdul Mannan', 'md. abdul mannan')<br/>('34949901', 'Antony Lam', 'antony lam')<br/>('2367471', 'Yoshinori Kobayashi', 'yoshinori kobayashi')<br/>('1737913', 'Yoshinori Kuno', 'yoshinori kuno')</td><td></td></tr><tr><td>a6e21438695dbc3a184d33b6cf5064ddf655a9ba</td><td>PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human <br/>Action Understanding <br/><b>Institiude of Computer Science and Technology, Peking University</b></td><td>('2994549', 'Jiaying Liu', 'jiaying liu')<br/>('1708754', 'Chunhui Liu', 'chunhui liu')</td><td>{liuchunhui, huyy, lyttonhao, ssj940929, liujiaying}@pku.edu.cn -</td></tr><tr><td>b9cad920a00fc0e997fc24396872e03f13c0bb9c</td><td>FACE LIVENESS DETECTION UNDER BAD ILLUMINATION CONDITIONS +</td></tr><tr><td>b9081856963ceb78dcb44ac410c6fca0533676a3</td><td>UntrimmedNets for Weakly Supervised Action Recognition and Detection +<br/>1Computer Vision Laboratory, ETH Zurich, Switzerland +<br/><b>The Chinese University of Hong Kong, Hong Kong</b></td><td>('33345248', 'Limin Wang', 'limin wang')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('1807606', 'Dahua Lin', 'dahua lin')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td></td></tr><tr><td>b97f694c2a111b5b1724eefd63c8d64c8e19f6c9</td><td>Group Affect Prediction Using Multimodal Distributions +<br/>Aspiring Minds +<br/>Univeristy of Massachusetts, Amherst +<br/><b>Johns Hopkins University</b></td><td>('40997180', 'Saqib Nizam Shamsi', 'saqib nizam shamsi')<br/>('47679973', 'Bhanu Pratap Singh', 'bhanu pratap singh')<br/>('7341605', 'Manya Wadhwa', 'manya wadhwa')</td><td>shamsi.saqib@gmail.com +<br/>bhanupratap.mnit@gmail.com +<br/>mwadhwa1@jhu.edu +</td></tr><tr><td>b9d0774b0321a5cfc75471b62c8c5ef6c15527f5</td><td>Fishy Faces: Crafting Adversarial Images to Poison Face Authentication +<br/>imec-DistriNet, KU Leuven +<br/>imec-DistriNet, KU Leuven +<br/>imec-DistriNet, KU Leuven +<br/>imec-DistriNet, KU Leuven +<br/>imec-DistriNet, KU Leuven +</td><td>('4412412', 'Giuseppe Garofalo', 'giuseppe garofalo')<br/>('23974422', 'Vera Rimmer', 'vera rimmer')<br/>('19243432', 'Tim Van hamme', 'tim van hamme')<br/>('1722184', 'Davy Preuveneers', 'davy preuveneers')<br/>('1752104', 'Wouter Joosen', 'wouter joosen')</td><td></td></tr><tr><td>b9cad920a00fc0e997fc24396872e03f13c0bb9c</td><td>FACE LIVENESS DETECTION UNDER BAD ILLUMINATION CONDITIONS <br/><b>University of Campinas (Unicamp</b><br/>Campinas, SP, Brazil -</td><td>('2826093', 'Bruno Peixoto', 'bruno peixoto')<br/>('34629204', 'Carolina Michelassi', 'carolina michelassi')<br/>('2145405', 'Anderson Rocha', 'anderson rocha')</td><td></td></tr><tr><td>b9c9c7ef82f31614c4b9226e92ab45de4394c5f6</td><td>11 +</td><td>('2826093', 'Bruno Peixoto', 'bruno peixoto')<br/>('34629204', 'Carolina Michelassi', 'carolina michelassi')<br/>('2145405', 'Anderson Rocha', 'anderson rocha')</td><td></td></tr><tr><td>b908edadad58c604a1e4b431f69ac8ded350589a</td><td>Deep Face Feature for Face Alignment +</td><td>('15679675', 'Boyi Jiang', 'boyi jiang')<br/>('2938279', 'Juyong Zhang', 'juyong zhang')<br/>('2964129', 'Bailin Deng', 'bailin deng')<br/>('8280113', 'Yudong Guo', 'yudong guo')<br/>('47968194', 'Ligang Liu', 'ligang liu')</td><td></td></tr><tr><td>b93bf0a7e449cfd0db91a83284d9eba25a6094d8</td><td>Supplementary Material for: Active Pictorial Structures +<br/>Epameinondas Antonakos +<br/>Joan Alabort-i-Medina +<br/>Stefanos Zafeiriou +<br/><b>Imperial College London</b><br/>180 Queens Gate, SW7 2AZ, London, U.K. +<br/>In the following sections, we provide additional material for the paper “Active Pictorial Structures”. Section 1 explains in +<br/>more detail the differences between the proposed Active Pictorial Structures (APS) and Pictorial Structures (PS). Section 2 +<br/>presents the proofs about the structure of the precision matrices of the Gaussian Markov Random Filed (GMRF) (Eqs. 10 +<br/>and 12 of the main paper). Section 3 gives an analysis about the forward Gauss-Newton optimization of APS and shows that +<br/>the inverse technique with fixed Jacobian and Hessian, which is used in the main paper, is much faster. Finally, Sec. 4 shows +<br/>additional experimental results and conducts new experiments on different objects (human eyes and cars). An open-source +<br/>implementation of APS is available within the Menpo Project [1] in http://www.menpo.org/. +<br/>1. Differences between Active Pictorial Structures and Pictorial Structures +<br/>As explained in the main paper, the proposed model is partially motivated by PS [4, 8]. In the original formulation of PS, +<br/>the cost function to be optimized has the form +<br/>(cid:88) +<br/>n(cid:88) +<br/>n(cid:88) +<br/>i=1 +<br/>arg min +<br/>= arg min +<br/>i=1 +<br/>mi((cid:96)i) + +<br/>dij((cid:96)i, (cid:96)j) = +<br/>i,j:(vi,vj )∈E +<br/>[A((cid:96)i) − µa +<br/>i ]T (Σa +<br/>i )−1[A((cid:96)i) − µa +<br/>i ] + +<br/>(cid:88) +<br/>i,j:(vi,vj )∈E +<br/>[(cid:96)i − (cid:96)j − µd +<br/>ij]T (Σd +<br/>ij)−1[(cid:96)i − (cid:96)j − µd +<br/>ij] +<br/>(1) +<br/>1 , . . . , (cid:96)T +<br/>n ]T is the vector of landmark coordinates ((cid:96)i = [xi, yi]T , ∀i = 1, . . . , n), A((cid:96)i) is a feature vector +<br/>where s = [(cid:96)T +<br/>ij} denote the mean +<br/>extracted from the image location (cid:96)i and we have assumed a tree G = (V, E). {µa +<br/>and covariances of the appearance and deformation respectively. In Eq. 1, mi((cid:96)i) is a function measuring the degree of +<br/>mismatch when part vi is placed at location (cid:96)i in the image. Moreover, dij((cid:96)i, (cid:96)j) denotes a function measuring the degree +<br/>of deformation of the model when part vi is placed at location (cid:96)i and part vj is placed at location (cid:96)j. The authors show +<br/>an inference algorithm based on distance transform [3] that can find a global minimum of Eq. 1 without any initialization. +<br/>However, this algorithm imposes two important restrictions: (1) appearance of each part is independent of the rest of them +<br/>and (2) G must always be acyclic (a tree). Additionally, the computation of mi((cid:96)i) for all parts (i = 1, . . . , n) and all possible +<br/>image locations (response maps) has a high computational cost, which makes the algorithm very slow. Finally, in [8], the +<br/>authors only use a diagonal covariance for the relative locations (deformation) of each edge of the graph, which restricts the +<br/>flexibility of the model. +<br/>i } and {µd +<br/>ij, Σd +<br/>i , Σa +<br/>In the proposed APS, we aim to minimize the cost function (Eq. 19 of the main paper) +<br/>(cid:107)A(S(¯s, p)) − ¯a(cid:107)2 +<br/>[A(S(¯s, p)) − ¯a]T Qa[A(S(¯s, p)) − ¯a] + [S(¯s, p) − ¯s]T Qd[S(¯s, p) − ¯s] +<br/>Qa + (cid:107)S(¯s, p) − ¯s(cid:107)2 +<br/>Qd = +<br/>arg min +<br/>= arg min +<br/>(2) +<br/>There are two main differences between APS and PS: (1) we employ a statistical shape model and optimize with respect +<br/>to its parameters and (2) we use the efficient Gauss-Newton optimization technique. However, these differences introduce +<br/>some important advantages, as also mentioned in the main paper. The proposed formulation allows to define a graph (not +<br/>only tree) between the object’s parts. This means that we can assume dependencies between any pair of landmarks for both +</td><td></td><td>{e.antonakos, ja310, s.zafeiriou}@imperial.ac.uk +</td></tr><tr><td>b9c9c7ef82f31614c4b9226e92ab45de4394c5f6</td><td>11 <br/>Face Recognition under Varying Illumination <br/><b>Nanyang Technological University</b><br/>Singapore <br/>1. Introduction @@ -28179,7 +35545,17 @@ </td></tr><tr><td>b9cedd1960d5c025be55ade0a0aa81b75a6efa61</td><td>INEXACT KRYLOV SUBSPACE ALGORITHMS FOR LARGE <br/>MATRIX EXPONENTIAL EIGENPROBLEM FROM <br/>DIMENSIONALITY REDUCTION -</td><td>('1685951', 'Gang Wu', 'gang wu')<br/>('7139289', 'Ting-ting Feng', 'ting-ting feng')<br/>('9472022', 'Li-jia Zhang', 'li-jia zhang')<br/>('5828998', 'Meng Yang', 'meng yang')</td><td></td></tr><tr><td>a1dd806b8f4f418d01960e22fb950fe7a56c18f1</td><td>Interactively Building a Discriminative Vocabulary of Nameable Attributes +</td><td>('1685951', 'Gang Wu', 'gang wu')<br/>('7139289', 'Ting-ting Feng', 'ting-ting feng')<br/>('9472022', 'Li-jia Zhang', 'li-jia zhang')<br/>('5828998', 'Meng Yang', 'meng yang')</td><td></td></tr><tr><td>b971266b29fcecf1d5efe1c4dcdc2355cb188ab0</td><td>MAI et al.: ON THE RECONSTRUCTION OF FACE IMAGES FROM DEEP FACE TEMPLATES +<br/>On the Reconstruction of Face Images from +<br/>Deep Face Templates +</td><td>('3391550', 'Guangcan Mai', 'guangcan mai')<br/>('1684684', 'Kai Cao', 'kai cao')<br/>('1768574', 'Pong C. Yuen', 'pong c. yuen')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>a1af7ec84472afba0451b431dfdb59be323e35b7</td><td>LikeNet: A Siamese Motion Estimation +<br/>Network Trained in an Unsupervised Way +<br/>Multimedia and Vision Research Group +<br/><b>Queen Mary University of London</b><br/>London, UK +</td><td>('49505678', 'Aria Ahmadi', 'aria ahmadi')<br/>('2000297', 'Ioannis Marras', 'ioannis marras')<br/>('1744405', 'Ioannis Patras', 'ioannis patras')<br/>('49505678', 'Aria Ahmadi', 'aria ahmadi')<br/>('2000297', 'Ioannis Marras', 'ioannis marras')<br/>('1744405', 'Ioannis Patras', 'ioannis patras')</td><td>a.ahmadi@qmul.ac.uk +<br/>i.marras@qmul.ac.uk +<br/>i.patras@qmul.ac.uk +</td></tr><tr><td>a1dd806b8f4f418d01960e22fb950fe7a56c18f1</td><td>Interactively Building a Discriminative Vocabulary of Nameable Attributes <br/><b>Toyota Technological Institute, Chicago (TTIC</b><br/><b>University of Texas at Austin</b></td><td>('1713589', 'Devi Parikh', 'devi parikh')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>dparikh@ttic.edu <br/>grauman@cs.utexas.edu </td></tr><tr><td>a158c1e2993ac90a90326881dd5cb0996c20d4f3</td><td>OPEN ACCESS @@ -28245,7 +35621,52 @@ <br/>duplicate detection, data deduplication, con- <br/>densation, consolidation <br/>image clustering, -</td><td></td><td></td></tr><tr><td>a125bc55bdf4bec7484111eea9ae537be314ec62</td><td>Real-time Facial Expression Recognition in Image +</td><td></td><td></td></tr><tr><td>a1b7bb2a4970b7c479aff3324cc7773c1daf3fc1</td><td>Longitudinal Study of Child Face Recognition +<br/><b>Michigan State University</b><br/>East Lansing, MI, USA +<br/><b>Malaviya National Institute of Technology</b><br/>Jaipur, India +<br/><b>Michigan State University</b><br/>East Lansing, MI, USA +</td><td>('32623642', 'Debayan Deb', 'debayan deb')<br/>('2117075', 'Neeta Nain', 'neeta nain')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td>debdebay@msu.edu +<br/>nnain.cse@mnit.ac.in +<br/>jain@cse.msu.edu +</td></tr><tr><td>a14ed872503a2f03d2b59e049fd6b4d61ab4d6ca</td><td>Attentional Pooling for Action Recognition +<br/><b>The Robotics Institute, Carnegie Mellon University</b><br/>http://rohitgirdhar.github.io/AttentionalPoolingAction +</td><td>('3102850', 'Rohit Girdhar', 'rohit girdhar')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td></td></tr><tr><td>a1132e2638a8abd08bdf7fc4884804dd6654fa63</td><td>6 +<br/>Real-Time Video Face Recognition +<br/>for Embedded Devices +<br/>Tessera, Galway, +<br/>Ireland +<br/>1. Introduction +<br/>This chapter will address the challenges of real-time video face recognition systems +<br/>implemented in embedded devices. Topics to be covered include: the importance and +<br/>challenges of video face recognition in real life scenarios, describing a general architecture of +<br/>a generic video face recognition system and a working solution suitable for recognizing +<br/>faces in real-time using low complexity devices. Each component of the system will be +<br/>described together with the system’s performance on a database of video samples that +<br/>resembles real life conditions. +<br/>2. Video face recognition +<br/>Face recognition remains a very active topic in computer vision and receives attention from +<br/>a large community of researchers in that discipline. Many reasons feed this interest; the +<br/>main being the wide range of commercial, law enforcement and security applications that +<br/>require authentication. The progress made in recent years on the methods and algorithms +<br/>for data processing as well as the availability of new technologies makes it easier to study +<br/>these algorithms and turn them into commercially viable product. Biometric based security +<br/>systems are becoming more popular due to their non-invasive nature and their increasing +<br/>reliability. Surveillance applications based on face recognition are gaining increasing +<br/>attention after the United States’ 9/11 events and with the ongoing security threats. The +<br/>Face Recognition Vendor Test (FRVT) (Phillips et al., 2003) includes video face recognition +<br/>testing starting with the 2002 series of tests. +<br/>Recently, face recognition technology was deployed in consumer applications such as +<br/>organizing a collection of images using the faces present in the images (Picassa; Corcoran & +<br/>Costache, 2005), prioritizing family members for best capturing conditions when taking +<br/>pictures, or directly annotating the images as they are captured (Costache et al., 2006). +<br/>Video face recognition, compared with more traditional still face recognition, has the main +<br/>advantage of using multiple instances of the same individual in sequential frames for +<br/>recognition to occur. In still recognition case, the system has only one input image to make +<br/>the decision if the person is or is not in the database. If the image is not suitable for +<br/>recognition (due to face orientation, expression, quality or facial occlusions) the recognition +<br/>result will most likely be incorrect. In the video image there are multiple frames which can +<br/>www.intechopen.com +</td><td>('1706790', 'Petronel Bigioi', 'petronel bigioi')<br/>('1734172', 'Peter Corcoran', 'peter corcoran')</td><td></td></tr><tr><td>a125bc55bdf4bec7484111eea9ae537be314ec62</td><td>Real-time Facial Expression Recognition in Image <br/>Sequences Using an AdaBoost-based Multi-classifier <br/><b>National Taiwan University of Science and Technology, Taipei 10607, Taiwan</b><br/><b>National Taiwan University of Science and Technology, Taipei 10607, Taiwan</b><br/><b>National Taiwan University of Science and Technology, Taipei 10607, Taiwan</b><br/> To surmount the shortcomings as stated above, we <br/>attempt to develop an automatic facial expression recognition @@ -28297,7 +35718,10 @@ <br/>E-mail: D9515011@mail.ntust.edu.tw Tel: +886-02-2733-3141 ext.7425 </td></tr><tr><td>a14ae81609d09fed217aa12a4df9466553db4859</td><td>REVISED VERSION, JUNE 2011 <br/>Face Identification Using Large Feature Sets -</td><td>('1679142', 'William Robson Schwartz', 'william robson schwartz')<br/>('2723427', 'Huimin Guo', 'huimin guo')<br/>('3826759', 'Jonghyun Choi', 'jonghyun choi')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td></td></tr><tr><td>a1ee0176a9c71863d812fe012b5c6b9c15f9aa8a</td><td>Affective recommender systems: the role of emotions in +</td><td>('1679142', 'William Robson Schwartz', 'william robson schwartz')<br/>('2723427', 'Huimin Guo', 'huimin guo')<br/>('3826759', 'Jonghyun Choi', 'jonghyun choi')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td></td></tr><tr><td>a1f1120653bb1bd8bd4bc9616f85fdc97f8ce892</td><td>Latent Embeddings for Zero-shot Classification +<br/>1MPI for Informatics +<br/>2IIT Kanpur +<br/><b>Saarland University</b></td><td>('3370667', 'Yongqin Xian', 'yongqin xian')<br/>('2893664', 'Zeynep Akata', 'zeynep akata')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')<br/>('33460941', 'Matthias Hein', 'matthias hein')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td></td></tr><tr><td>a1ee0176a9c71863d812fe012b5c6b9c15f9aa8a</td><td>Affective recommender systems: the role of emotions in <br/>recommender systems <br/>Jurij Tasiˇc <br/><b>University of Ljubljana Faculty</b><br/><b>University of Ljubljana Faculty</b><br/><b>University of Ljubljana Faculty</b><br/>of electrical engineering @@ -28312,12 +35736,125 @@ </td><td>('1717186', 'Andrej Košir', 'andrej košir')</td><td>marko.tkalcic@fe.uni-lj.si <br/>andrej.kosir@fe.uni-lj.si <br/>jurij.tasic@fe.uni-lj.si +</td></tr><tr><td>a1dd9038b1e1e59c9d564e252d3e14705872fdec</td><td>Attributes as Operators: +<br/>Factorizing Unseen Attribute-Object Compositions +<br/><b>The University of Texas at Austin</b><br/>2 Facebook AI Research +</td><td>('38661780', 'Tushar Nagarajan', 'tushar nagarajan')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>tushar@cs.utexas.edu, grauman@fb.com∗ </td></tr><tr><td>a1e97c4043d5cc9896dc60ae7ca135782d89e5fc</td><td>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE <br/>Re-identification of Humans in Crowds using <br/>Personal, Social and Environmental Constraints -</td><td>('2963501', 'Shayan Modiri Assari', 'shayan modiri assari')<br/>('1803711', 'Haroon Idrees', 'haroon idrees')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td></td></tr><tr><td>efd308393b573e5410455960fe551160e1525f49</td><td>Tracking Persons-of-Interest via +</td><td>('2963501', 'Shayan Modiri Assari', 'shayan modiri assari')<br/>('1803711', 'Haroon Idrees', 'haroon idrees')<br/>('1745480', 'Mubarak Shah', 'mubarak shah')</td><td></td></tr><tr><td>a16fb74ea66025d1f346045fda00bd287c20af0e</td><td>A Coupled Evolutionary Network for Age Estimation +<br/>National Laboratory of Pattern Recognition, CASIA, Beijing, China 100190 +<br/>Center for Research on Intelligent Perception and Computing, CASIA, Beijing, China 100190 +<br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('2112221', 'Peipei Li', 'peipei li')<br/>('49995036', 'Yibo Hu', 'yibo hu')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>Email: {peipei.li, yibo.hu}@cripac.ia.ac.cn, {rhe, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>ef940b76e40e18f329c43a3f545dc41080f68748</td><td> +<br/> +<br/>Research Article Volume 7 Issue No.3 +<br/>ISSN XXXX XXXX © 2017 IJESC +<br/> +<br/>A Face Recognition and Spoofing Detection Adapted to Visually- +<br/>Impaired People +<br/><b>K.K Wagh Institute of Engineering and Education Research, Nashik, India</b><br/>Depart ment of Co mputer Engineering +<br/>Abstrac t: +<br/>According to estimates by the world Health organization, about 285 million people suffer fro m so me kind of v isual disabilit ies of +<br/>which 39 million are blind, resulting in 0.7 of the word population. As many v isual impaired peoples in the word they are unable +<br/>to recognize the people who is standing in front of them and some peoples who have problem to re me mbe r na me of the person. +<br/>They can easily recognize the person using this system. A co mputer vision technique and image ana lysis can help v isually +<br/>the home using face identification and spoofing detection system. This system also provide feature to add newly known people +<br/>and keep records of all peoples visiting their ho me. +<br/>Ke ywor ds: face-recognition, spoofing detection, visually-impaired, system architecture. +<br/>I. +<br/> INTRODUCTION +<br/>The facia l ana lysis can be used to e xtract very useful and +<br/>relevant information in order to help people with visual +<br/>impairment in several of its tasks daily providing them with a +<br/>greater degree of autonomy and security. Facia l recognition +<br/>has received many improve ments recent years and today is +<br/>approaching perfection. The advances in facia l recognition +<br/>have not been outside the People with disab ilities. For +<br/>e xa mple , recently it has an intelligent walking stick for the +<br/>blind that uses facial recognition [5]. The cane co mes +<br/>equipped with a fac ial recognition system, GPS and Bluetooth. +<br/>at the sight the face of any acquaintance or friend whose +<br/>picture is stored on the SD card stick, this will v ibrate and give +<br/>to Bluetooth headset through a necessary instructions to reach +<br/>this person. The system works with anyone who is at 10 +<br/>meters or less. And thanks to the GPS, the user will rece ive +<br/>instructions for reach wherever, as with any GPS navigator. +<br/>However, in addition to the task of recognition today have +<br/>biometric systems to deal with other problems, such as +<br/>spoofing. In network security terms, this term re fers to Using +<br/>techniques through which an attacker, usually with malic ious +<br/>use, it is passed by a other than through the falsification of +<br/>data entity in a co mmun ication. Motivation of the p roject is to +<br/>propose, build and validate an architecture based on face +<br/>recognition and anti-spoofing system that both can be +<br/>integrated in a video entry as a mobile app. In this way, we +<br/>want to give the blind and visually impaired an instrument or +<br/>tool to allo w an ult imate goal to improve the quality of life +<br/>and increase both safety and the feel of it in your ho me or +<br/>when you +<br/>interact with other people. The p roposed +<br/>architecture has been validated with rea l users and a real +<br/>environment simulating the same conditions as could give +<br/>both the images captured by a video portero as images taken +<br/>by a person visually impa ired through their mobile device. +<br/>Contributions are d iscussed below: First an algorith m is +<br/>proposed for the normalization face robust user as to rotations +<br/>and misalignments in the face detection algorith m. It is shown +<br/>that a robust norma lizat ion algorithm you can significantly +<br/>increase the rate of success in a face detection algorithm +<br/>The organizat ion of this document is as follo ws. In Section 2 +<br/>gives literature survey, Section 3 gives details of system +<br/>architecture. In Section 4 gives imp le mentation details. +<br/>Section 5 presents research findings and your analysis of those +<br/>findings. Section 6 concludes the paper. +<br/>II. LITERATURE S URVEY +<br/>A. Facial Rec ognition oriente d visual i mpair ment +<br/>The proble m of face recognition adapted to visually impaired +<br/>people has been investigated in their d ifferent ways. Belo w are +<br/>summarized the work impo rtant, indicating for each the most +<br/>important features that have been motivating development of +<br/>the architecture proposed here. In [6] fac ia l recognition system +<br/>is presented in mobile devices for the visually impaired, but +<br/>meet ings main ly focused on what aspects as visual fie ld +<br/>captured by the mobile focus much of the subject. In [7] +<br/>system developed facial recognition based on Local Binary +<br/>Pattern (LBP) [8]. They co mpared this with other a lternatives +<br/>descriptor (Local Te rnary Pattern [9] or Histogram of +<br/>Gradients [10]) and arrived It concluded that the performance +<br/>is slightly LBP superior, its computational cost is lower and +<br/>representation information is more co mpact. As has been +<br/>mentioned above, in [5] it has developed a system fac ial +<br/>recognition integrated into a cane. In none of these methods is +<br/>carried out detection spoofing, making the system has a +<br/>vulnerability high against such attacks. We believe it is a point +<br/>very important especially in people with visual d isabilities. +<br/>Moreover, none of the alternatives above mentioned is video +<br/>porters oriented. +<br/>B. De tection S poofing +<br/>As none of the above has been studied spoofing detection to +<br/>help people with visual impairment, we will discuss the +<br/>results more significant as +<br/>refers. There are many different methods +<br/>for detecting +<br/>spoofing. However, one o f the key factors in an application +<br/>that must run in rea l time and in a device Embedded is what +<br/>the method be co mputationally lightweight. Most algorith ms +<br/>or proposed are very comple x and are therefo re unfit for rea l, +<br/>far as detecting spoofing +<br/>International Journal of Engineering Science and Computing, March 2017 6051 http://ijesc.org/ +</td><td></td><td></td></tr><tr><td>efd308393b573e5410455960fe551160e1525f49</td><td>Tracking Persons-of-Interest via <br/>Unsupervised Representation Adaptation -</td><td>('2481388', 'Shun Zhang', 'shun zhang')<br/>('3068086', 'Jia-Bin Huang', 'jia-bin huang')<br/>('33047058', 'Jongwoo Lim', 'jongwoo lim')<br/>('1698965', 'Yihong Gong', 'yihong gong')<br/>('32014778', 'Jinjun Wang', 'jinjun wang')<br/>('1752333', 'Narendra Ahuja', 'narendra ahuja')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>efd28eabebb9815e34031316624e7f095c7dfcfe</td><td>A. Uhl and P. Wild. Combining Face with Face-Part Detectors under Gaussian Assumption. In A. Campilho and M. Kamel, +</td><td>('2481388', 'Shun Zhang', 'shun zhang')<br/>('3068086', 'Jia-Bin Huang', 'jia-bin huang')<br/>('33047058', 'Jongwoo Lim', 'jongwoo lim')<br/>('1698965', 'Yihong Gong', 'yihong gong')<br/>('32014778', 'Jinjun Wang', 'jinjun wang')<br/>('1752333', 'Narendra Ahuja', 'narendra ahuja')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>ef230e3df720abf2983ba6b347c9d46283e4b690</td><td>Page 1 of 20 +<br/>QUIS-CAMPI: An Annotated Multi-biometrics Data Feed From +<br/>Surveillance Scenarios +<br/><b>IT - Instituto de Telecomunica es, University of Beira Interior</b><br/><b>University of Beira Interior</b><br/><b>IT - Instituto de Telecomunica es, University of Beira Interior</b></td><td>('1712429', 'Hugo Proença', 'hugo proença')</td><td>*jcneves@ubi.pt +</td></tr><tr><td>ef4ecb76413a05c96eac4c743d2c2a3886f2ae07</td><td>Modeling the Importance of Faces in Natural Images +<br/>Jin B.a, Yildirim G.a, Lau C.a, Shaji A.a, Ortiz Segovia M.b and S¨usstrunk S.a +<br/>aEPFL, Lausanne, Switzerland; +<br/>bOc´e, Paris, France +</td><td></td><td></td></tr><tr><td>efd28eabebb9815e34031316624e7f095c7dfcfe</td><td>A. Uhl and P. Wild. Combining Face with Face-Part Detectors under Gaussian Assumption. In A. Campilho and M. Kamel, <br/>editors, Proceedings of the 9th International Conference on Image Analysis and Recognition (ICIAR’12), volume 7325 of <br/>LNCS, pages 80{89, Aveiro, Portugal, June 25{27, 2012. c⃝ Springer. doi: 10.1007/978-3-642-31298-4 10. The original <br/>publication is available at www.springerlink.com. @@ -28327,12 +35864,63 @@ <br/><b>University of Salzburg, Austria</b></td><td>('1689850', 'Andreas Uhl', 'andreas uhl')<br/>('2242291', 'Peter Wild', 'peter wild')</td><td>fuhl,pwildg@cosy.sbg.ac.at </td></tr><tr><td>eff87ecafed67cc6fc4f661cb077fed5440994bb</td><td>Evaluation of Expression Recognition <br/>Techniques -<br/><b>Beckman Institute, University of Illinois at Urbana-Champaign, USA</b><br/><b>Faculty of Science, University of Amsterdam, The Netherlands</b><br/><b>Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands</b></td><td>('1774778', 'Ira Cohen', 'ira cohen')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1840164', 'Yafei Sun', 'yafei sun')<br/>('1731570', 'Michael S. Lew', 'michael s. lew')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>ef2a5a26448636570986d5cda8376da83d96ef87</td><td>Recurrent Neural Networks and Transfer Learning for Action Recognition +<br/><b>Beckman Institute, University of Illinois at Urbana-Champaign, USA</b><br/><b>Faculty of Science, University of Amsterdam, The Netherlands</b><br/><b>Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands</b></td><td>('1774778', 'Ira Cohen', 'ira cohen')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1840164', 'Yafei Sun', 'yafei sun')<br/>('1731570', 'Michael S. Lew', 'michael s. lew')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td></td></tr><tr><td>ef458499c3856a6e9cd4738b3e97bef010786adb</td><td>Learning Type-Aware Embeddings for Fashion +<br/>Compatibility +<br/>Department of Computer Science, +<br/><b>University of Illinois at Urbana-Champaign</b></td><td>('47087718', 'Mariya I. Vasileva', 'mariya i. vasileva')<br/>('2856622', 'Bryan A. Plummer', 'bryan a. plummer')<br/>('40895028', 'Krishna Dusad', 'krishna dusad')<br/>('9560882', 'Shreya Rajpal', 'shreya rajpal')<br/>('40439276', 'Ranjitha Kumar', 'ranjitha kumar')</td><td>{mvasile2,bplumme2,dusad2,srajpal2,ranjitha,daf}@illnois.edu +</td></tr><tr><td>ef032afa4bdb18b328ffcc60e2dc5229cc1939bc</td><td>Fang and Yuan EURASIP Journal on Image and Video +<br/>Processing (2018) 2018:44 +<br/>https://doi.org/10.1186/s13640-018-0282-x +<br/>EURASIP Journal on Image +<br/>and Video Processing +<br/>RESEARCH +<br/>Open Access +<br/>Attribute-enhanced metric learning for +<br/>face retrieval +</td><td>('8589942', 'Yuchun Fang', 'yuchun fang')<br/>('30438417', 'Qiulong Yuan', 'qiulong yuan')</td><td></td></tr><tr><td>ef2a5a26448636570986d5cda8376da83d96ef87</td><td>Recurrent Neural Networks and Transfer Learning for Action Recognition <br/><b>Stanford University</b><br/><b>Stanford University</b></td><td>('11647121', 'Andrew Giel', 'andrew giel')<br/>('32426361', 'Ryan Diaz', 'ryan diaz')</td><td>agiel@stanford.edu <br/>ryandiaz@stanford.edu -</td></tr><tr><td>c32fb755856c21a238857b77d7548f18e05f482d</td><td>Multimodal Emotion Recognition for Human- +</td></tr><tr><td>ef5531711a69ed687637c48930261769465457f0</td><td>Studio2Shop: from studio photo shoots to fashion articles +<br/>Zalando Research, Muehlenstr. 25, 10243 Berlin, Germany +<br/>Keywords: +<br/>computer vision, deep learning, fashion, item recognition, street-to-shop +</td><td>('46928510', 'Julia Lasserre', 'julia lasserre')<br/>('1724791', 'Katharina Rasch', 'katharina rasch')<br/>('2742129', 'Roland Vollgraf', 'roland vollgraf')</td><td>julia.lasserre@zalando.de +</td></tr><tr><td>ef559d5f02e43534168fbec86707915a70cd73a0</td><td>DING, HUO, HU, LU: DEEPINSIGHT +<br/>DeepInsight: Multi-Task Multi-Scale Deep +<br/>Learning for Mental Disorder Diagnosis +<br/>1 School of Information +<br/><b>Renmin University of China</b><br/>Beijing, 100872, China +<br/>2 Beijing Key Laboratory +<br/>of Big Data Management +<br/>and Analysis Methods +<br/>Beijing, 100872, China +</td><td>('5535865', 'Mingyu Ding', 'mingyu ding')<br/>('4140493', 'Yuqi Huo', 'yuqi huo')<br/>('1745787', 'Jun Hu', 'jun hu')<br/>('1776220', 'Zhiwu Lu', 'zhiwu lu')</td><td>d130143597@163.com +<br/>bnhony@163.com +<br/>junhu@ruc.edu.cn +<br/>luzhiwu@ruc.edu.cn +</td></tr><tr><td>efa08283656714911acff2d5022f26904e451113</td><td>Active Object Localization in Visual Situations +</td><td>('3438473', 'Max H. Quinn', 'max h. quinn')<br/>('13739397', 'Anthony D. Rhodes', 'anthony d. rhodes')<br/>('4421478', 'Melanie Mitchell', 'melanie mitchell')</td><td></td></tr><tr><td>ef8de1bd92e9ee9d0d2dee73095d4d348dc54a98</td><td>Fine-grained Activity Recognition +<br/>with Holistic and Pose based Features +<br/><b>Max Planck Institute for Informatics, Germany</b><br/><b>Stanford University, USA</b></td><td>('2299109', 'Leonid Pishchulin', 'leonid pishchulin')<br/>('1906895', 'Mykhaylo Andriluka', 'mykhaylo andriluka')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')</td><td></td></tr><tr><td>ef999ab2f7b37f46445a3457bf6c0f5fd7b5689d</td><td>Calhoun: The NPS Institutional Archive +<br/>DSpace Repository +<br/>Theses and Dissertations +<br/>1. Thesis and Dissertation Collection, all items +<br/>2017-12 +<br/>Improving face verification in photo albums by +<br/>combining facial recognition and metadata +<br/>with cross-matching +<br/>Monterey, California: Naval Postgraduate School +<br/>http://hdl.handle.net/10945/56868 +<br/>Downloaded from NPS Archive: Calhoun +</td><td></td><td></td></tr><tr><td>c32fb755856c21a238857b77d7548f18e05f482d</td><td>Multimodal Emotion Recognition for Human- <br/>Computer Interaction: A Survey -<br/><b>School of Computer and Communication Engineering, University of Science and Technology Beijing, 100083 Beijing, China</b></td><td>('10692633', 'Michele Mukeshimana', 'michele mukeshimana')<br/>('1714904', 'Xiaojuan Ban', 'xiaojuan ban')<br/>('17056027', 'Nelson Karani', 'nelson karani')<br/>('7247643', 'Ruoyi Liu', 'ruoyi liu')</td><td></td></tr><tr><td>c3b3636080b9931ac802e2dd28b7b684d6cf4f8b</td><td>International Journal of Security and Its Applications +<br/><b>School of Computer and Communication Engineering, University of Science and Technology Beijing, 100083 Beijing, China</b></td><td>('10692633', 'Michele Mukeshimana', 'michele mukeshimana')<br/>('1714904', 'Xiaojuan Ban', 'xiaojuan ban')<br/>('17056027', 'Nelson Karani', 'nelson karani')<br/>('7247643', 'Ruoyi Liu', 'ruoyi liu')</td><td></td></tr><tr><td>c3beae515f38daf4bd8053a7d72f6d2ed3b05d88</td><td></td><td></td><td></td></tr><tr><td>c3dc4f414f5233df96a9661609557e341b71670d</td><td>Tao et al. EURASIP Journal on Advances in Signal Processing 2011, 2011:4 +<br/>http://asp.eurasipjournals.com/content/2011/1/4 +<br/>RESEARCH +<br/>Utterance independent bimodal emotion +<br/>recognition in spontaneous communication +<br/>Open Access +</td><td>('37670752', 'Jianhua Tao', 'jianhua tao')<br/>('48027528', 'Shifeng Pan', 'shifeng pan')<br/>('2740129', 'Minghao Yang', 'minghao yang')<br/>('3295988', 'Kaihui Mu', 'kaihui mu')<br/>('2253805', 'Jianfeng Che', 'jianfeng che')</td><td></td></tr><tr><td>c3b3636080b9931ac802e2dd28b7b684d6cf4f8b</td><td>International Journal of Security and Its Applications <br/>Vol. 7, No. 2, March, 2013 <br/>Face Recognition via Local Directional Pattern <br/><b>Division of IT Convergence, Daegu Gyeongbuk Institute of Science and Technology</b><br/>50-1, Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, Korea. @@ -28340,7 +35928,7 @@ </td></tr><tr><td>c398684270543e97e3194674d9cce20acaef3db3</td><td>Chapter 2 <br/>Comparative Face Soft Biometrics for <br/>Human Identification -</td><td>('19249411', 'Nawaf Yousef Almudhahka', 'nawaf yousef almudhahka')<br/>('1727698', 'Mark S. Nixon', 'mark s. nixon')<br/>('31534955', 'Jonathon S. Hare', 'jonathon s. hare')</td><td></td></tr><tr><td>c3418f866a86dfd947c2b548cbdeac8ca5783c15</td><td></td><td></td><td></td></tr><tr><td>c3bcc4ee9e81ce9c5c0845f34e9992872a8defc0</td><td>MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan +</td><td>('19249411', 'Nawaf Yousef Almudhahka', 'nawaf yousef almudhahka')<br/>('1727698', 'Mark S. Nixon', 'mark s. nixon')<br/>('31534955', 'Jonathon S. Hare', 'jonathon s. hare')</td><td></td></tr><tr><td>c3285a1d6ec6972156fea9e6dc9a8d88cd001617</td><td></td><td></td><td></td></tr><tr><td>c3418f866a86dfd947c2b548cbdeac8ca5783c15</td><td></td><td></td><td></td></tr><tr><td>c3bcc4ee9e81ce9c5c0845f34e9992872a8defc0</td><td>MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan <br/>8-10 <br/>A New Scheme for Image Recognition Using Higher-Order Local <br/>Autocorrelation and Factor Analysis @@ -28348,6 +35936,16 @@ <br/>yyyAIST <br/>Tukuba, Japan </td><td>('29737626', 'Naoyuki Nomoto', 'naoyuki nomoto')<br/>('2163494', 'Yusuke Shinohara', 'yusuke shinohara')<br/>('2981587', 'Takayoshi Shiraki', 'takayoshi shiraki')<br/>('1800592', 'Takumi Kobayashi', 'takumi kobayashi')<br/>('1809629', 'Nobuyuki Otsu', 'nobuyuki otsu')</td><td>f shiraki, takumi, otsug @isi.imi.i.u-tokyo.ac.jp +</td></tr><tr><td>c34532fe6bfbd1e6df477c9ffdbb043b77e7804d</td><td>A 3D Morphable Eye Region Model +<br/>for Gaze Estimation +<br/><b>University of Cambridge, Cambridge, UK</b><br/><b>Carnegie Mellon University, Pittsburgh, USA</b><br/><b>Max Planck Institute for Informatics, Saarbr ucken, Germany</b></td><td>('34399452', 'Erroll Wood', 'erroll wood')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')<br/>('39626495', 'Peter Robinson', 'peter robinson')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td>{eww23,pr10}@cl.cam.ac.uk +<br/>{tbaltrus,morency}@cs.cmu.edu +<br/>bulling@mpi-inf.mpg.de +</td></tr><tr><td>c394a5dfe5bea5fbab4c2b6b90d2d03e01fb29c0</td><td>Person Reidentification and Recognition in +<br/>Video +<br/>Computer Science and Engineering, +<br/><b>University of South Florida, Tampa, Florida, USA</b><br/>http://figment.csee.usf.edu/ +</td><td>('3110392', 'Rangachar Kasturi', 'rangachar kasturi')</td><td>R1K@cse.usf.edu,rajmadhan@mail.usf.edu </td></tr><tr><td>c32383330df27625592134edd72d69bb6b5cff5c</td><td>422 <br/>IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 42, NO. 2, APRIL 2012 <br/>Intrinsic Illumination Subspace for Lighting @@ -28362,6 +35960,9 @@ <br/>Using an Ensemble of Exemplars <br/><b>University City Blvd., Charlotte, NC</b><br/>Department of Computer Science <br/><b>University of North Carolina at Charlotte</b></td><td>('1715594', 'Scott Spurlock', 'scott spurlock')<br/>('2549750', 'Peter Malmgren', 'peter malmgren')<br/>('1873911', 'Hui Wu', 'hui wu')<br/>('1690110', 'Richard Souvenir', 'richard souvenir')</td><td>{sspurloc, ptmalmyr, hwu13, souvenir}@uncc.edu +</td></tr><tr><td>c39ffc56a41d436748b9b57bdabd8248b2d28a32</td><td>Residual Attention Network for Image Classification +<br/><b>SenseTime Group Limited, 2Tsinghua University</b><br/><b>The Chinese University of Hong Kong, 4Beijing University of Posts and Telecommunications</b></td><td>('1682816', 'Fei Wang', 'fei wang')<br/>('9563639', 'Mengqing Jiang', 'mengqing jiang')<br/>('40110742', 'Chen Qian', 'chen qian')<br/>('1692609', 'Shuo Yang', 'shuo yang')<br/>('49672774', 'Cheng Li', 'cheng li')<br/>('1720776', 'Honggang Zhang', 'honggang zhang')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>1{wangfei, qianchen, chengli}@sensetime.com, 2jmq14@mails.tsinghua.edu.cn +<br/>3{ys014, xtang}@ie.cuhk.edu.hk, xgwang@ee.cuhk.edu.hk, 4zhhg@bupt.edu.cn </td></tr><tr><td>c32cd207855e301e6d1d9ddd3633c949630c793a</td><td>On the Effect of Illumination and Face Recognition <br/>Jeffrey Ho <br/>Department of CISE @@ -28370,7 +35971,56 @@ <br/><b>University of California at San Diego</b><br/>La Jolla, CA 92093 </td><td>('38998440', 'David Kriegman', 'david kriegman')</td><td>Email: jho@cise.ufl.edu <br/>Email: kriegman@cs.ucsd.edu -</td></tr><tr><td>c37a971f7a57f7345fdc479fa329d9b425ee02be</td><td>A Novice Guide towards Human Motion Analysis and Understanding +</td></tr><tr><td>c317181fa1de2260e956f05cd655642607520a4f</td><td>Research Article +<br/>Research +<br/>Article for submission to journal +<br/>Subject Areas: +<br/>computer vision, pattern recognition, +<br/>feature descriptor +<br/>Keywords: +<br/>micro-facial expression, expression +<br/>recognition, action unit +<br/>Objective Classes for +<br/>Micro-Facial Expression +<br/>Recognition +<br/><b>Centre for Imaging Sciences, University of</b><br/>Manchester, Manchester, United Kingdom +<br/><b>Sudan University of Science and Technology</b><br/>Khartoum, Sudan +<br/>3School of Computing, Mathematics and Digital +<br/><b>Technology, Manchester Metropolitan University</b><br/>Manchester, United Kingdom +<br/>instead of predicted emotion, +<br/>Micro-expressions are brief spontaneous facial expressions +<br/>that appear on a face when a person conceals an emotion, +<br/>making them different +<br/>to normal facial expressions in +<br/>subtlety and duration. Currently, emotion classes within +<br/>the CASME II dataset are based on Action Units and +<br/>self-reports, creating conflicts during machine learning +<br/>training. We will show that classifying expressions using +<br/>Action Units, +<br/>removes +<br/>the potential bias of human reporting. The proposed +<br/>classes are tested using LBP-TOP, HOOF and HOG 3D +<br/>feature descriptors. The experiments are evaluated on +<br/>two benchmark FACS coded datasets: CASME II and +<br/>SAMM. The best result achieves 86.35% accuracy when +<br/>classifying the proposed 5 classes on CASME II using +<br/>HOG 3D, outperforming the result of the state-of-the- +<br/>art 5-class emotional-based classification in CASME II. +<br/>Results indicate that classification based on Action Units +<br/>provides an objective method to improve micro-expression +<br/>recognition. +<br/>1. Introduction +<br/>A micro-facial expression is revealed when someone attempts +<br/>to conceal their true emotion [1,2]. When they consciously +<br/>realise that a facial expression is occurring, the person may try +<br/>to suppress the facial expression because showing the emotion +<br/>may not be appropriate [3]. Once the suppression has occurred, +<br/>the person may mask over the original facial expression and +<br/>cause a micro-facial expression. In a high-stakes environment, +<br/>these expressions tend to become more likely as there is more +<br/>risk to showing the emotion. +</td><td>('3125772', 'Moi Hoon Yap', 'moi hoon yap')<br/>('36059631', 'Adrian K. Davison', 'adrian k. davison')<br/>('23986818', 'Walied Merghani', 'walied merghani')<br/>('3125772', 'Moi Hoon Yap', 'moi hoon yap')</td><td>e-mail: M.Yap@mmu.ac.uk +</td></tr><tr><td>c30e4e4994b76605dcb2071954eaaea471307d80</td><td></td><td></td><td></td></tr><tr><td>c37a971f7a57f7345fdc479fa329d9b425ee02be</td><td>A Novice Guide towards Human Motion Analysis and Understanding </td><td>('40360970', 'Ahmed Nabil Mohamed', 'ahmed nabil mohamed')</td><td>dr.ahmed.mohamed@ieee.org </td></tr><tr><td>c3638b026c7f80a2199b5ae89c8fcbedfc0bd8af</td><td></td><td></td><td></td></tr><tr><td>c32c8bfadda8f44d40c6cd9058a4016ab1c27499</td><td>Unconstrained Face Recognition From a Single <br/>Image @@ -28404,9 +36054,22 @@ <br/>2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) <br/>978-1-4799-2893-4/14/$31.00 ©2014 IEEE <br/>1. INTRODUCTION -</td><td></td><td></td></tr><tr><td>c418a3441f992fea523926f837f4bfb742548c16</td><td>A Computer Approach for Face Aging Problems +</td><td></td><td></td></tr><tr><td>c37de914c6e9b743d90e2566723d0062bedc9e6a</td><td>©2016 Society for Imaging Science and Technology +<br/>DOI: 10.2352/ISSN.2470-1173.2016.11.IMAWM-455 +<br/>Joint and Discriminative Dictionary Learning +<br/>Expression Recognition +<br/>for Facial +</td><td>('38611433', 'Sriram Kumar', 'sriram kumar')<br/>('3168309', 'Behnaz Ghoraani', 'behnaz ghoraani')<br/>('32219349', 'Andreas Savakis', 'andreas savakis')</td><td></td></tr><tr><td>c418a3441f992fea523926f837f4bfb742548c16</td><td>A Computer Approach for Face Aging Problems <br/>Centre for Pattern Recognition and Machine Intelligence, <br/><b>Concordia University, Canada</b></td><td>('1769788', 'Khoa Luu', 'khoa luu')</td><td>kh_lu@cenparmi.concordia.ca +</td></tr><tr><td>c4fb2de4a5dc28710d9880aece321acf68338fde</td><td>Interactive Generative Adversarial Networks for Facial Expression Generation +<br/>in Dyadic Interactions +<br/><b>University of Central Florida</b><br/>Educational Testing Service +<br/>Saad Khan +<br/>Educational Testing Service +</td><td>('2974242', 'Behnaz Nojavanasghari', 'behnaz nojavanasghari')<br/>('2224875', 'Yuchi Huang', 'yuchi huang')</td><td>behnaz@eecs.ucf.edu +<br/>yhuang001@ets.org +<br/>skhan002@ets.org </td></tr><tr><td>c44c84540db1c38ace232ef34b03bda1c81ba039</td><td>Cross-Age Reference Coding for Age-Invariant <br/>Face Recognition and Retrieval <br/><b>Institute of Information Science, Academia Sinica, Taipei, Taiwan</b><br/><b>National Taiwan University, Taipei, Taiwan</b></td><td>('33970300', 'Bor-Chun Chen', 'bor-chun chen')<br/>('1720473', 'Chu-Song Chen', 'chu-song chen')<br/>('1716836', 'Winston H. Hsu', 'winston h. hsu')</td><td></td></tr><tr><td>c4f1fcd0a5cdaad8b920ee8188a8557b6086c1a4</td><td>Int J Comput Vis (2014) 108:3–29 @@ -28418,7 +36081,8 @@ </td><td>('3251767', 'Steve Branson', 'steve branson')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td></td></tr><tr><td>c46a4db7247d26aceafed3e4f38ce52d54361817</td><td>A CNN Cascade for Landmark Guided Semantic <br/>Part Segmentation <br/><b>School of Computer Science, The University of Nottingham, Nottingham, UK</b></td><td>('34596685', 'Aaron S. Jackson', 'aaron s. jackson')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td>{aaron.jackson, michel.valstar, yorgos.tzimiropoulos}@nottingham.ac.uk -</td></tr><tr><td>c4dcf41506c23aa45c33a0a5e51b5b9f8990e8ad</td><td> Understanding Activity: Learning the Language of Action +</td></tr><tr><td>c43862db5eb7e43e3ef45b5eac4ab30e318f2002</td><td>Provable Self-Representation Based Outlier Detection in a Union of Subspaces +<br/><b>Johns Hopkins University, Baltimore, MD, 21218, USA</b></td><td>('1878841', 'Chong You', 'chong you')<br/>('1780452', 'Daniel P. Robinson', 'daniel p. robinson')</td><td></td></tr><tr><td>c4dcf41506c23aa45c33a0a5e51b5b9f8990e8ad</td><td> Understanding Activity: Learning the Language of Action <br/> Univ. of Rochester and Maryland <br/>1.1 Overview <br/>Understanding observed activity is an important @@ -28507,7 +36171,31 @@ <br/>Using A Single 3D Reference Model <br/><b>National Taiwan University of Science and Technology</b><br/>No. 43, Sec.4, Keelung Rd., Taipei, 106, Taiwan </td><td>('38801529', 'Gee-Sern Hsu', 'gee-sern hsu')<br/>('3329222', 'Hsiao-Chia Peng', 'hsiao-chia peng')</td><td>*jison@mail.ntust.edu.tw -</td></tr><tr><td>eacba5e8fbafb1302866c0860fc260a2bdfff232</td><td>VOS-GAN: Adversarial Learning of Visual-Temporal +</td></tr><tr><td>ea46951b070f37ad95ea4ed08c7c2a71be2daedc</td><td>Using phase instead of optical flow +<br/>for action recognition +<br/><b>Computer Vision Lab, Delft University of Technology, Netherlands</b><br/><b>Intelligent Sensory Interactive Systems, University of Amsterdam, Netherlands</b></td><td>('9179750', 'Omar Hommos', 'omar hommos')<br/>('37041694', 'Silvia L. Pintea', 'silvia l. pintea')<br/>('1738975', 'Jan C. van Gemert', 'jan c. van gemert')</td><td></td></tr><tr><td>eac6aee477446a67d491ef7c95abb21867cf71fc</td><td>JOURNAL +<br/>A survey of sparse representation: algorithms and +<br/>applications +</td><td>('38448016', 'Zheng Zhang', 'zheng zhang')<br/>('38649019', 'Yong Xu', 'yong xu')<br/>('37081450', 'Jian Yang', 'jian yang')<br/>('1720243', 'Xuelong Li', 'xuelong li')<br/>('1698371', 'David Zhang', 'david zhang')</td><td></td></tr><tr><td>ea079334121a0ba89452036e5d7f8e18f6851519</td><td>UNSUPERVISED INCREMENTAL LEARNING OF DEEP DESCRIPTORS +<br/>FROM VIDEO STREAMS +<br/><b>MICC University of Florence</b></td><td>('2619131', 'Federico Pernici', 'federico pernici')<br/>('8196487', 'Alberto Del Bimbo', 'alberto del bimbo')</td><td>federico.pernici@unifi.it, alberto.delbimbo@unifi.it +</td></tr><tr><td>eac1b644492c10546a50f3e125a1f790ec46365f</td><td>Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for +<br/>Action Classification and Detection +<br/><b>University of Freiburg</b><br/>Freiburg im Breisgau, Germany +</td><td>('2890820', 'Mohammadreza Zolfaghari', 'mohammadreza zolfaghari')<br/>('2371771', 'Gabriel L. Oliveira', 'gabriel l. oliveira')<br/>('31656404', 'Nima Sedaghat', 'nima sedaghat')<br/>('1710872', 'Thomas Brox', 'thomas brox')</td><td>{zolfagha,oliveira,nima,brox}@cs.uni-freiburg.de +</td></tr><tr><td>ea80a050d20c0e24e0625a92e5c03e5c8db3e786</td><td>Face Verification and Face Image Synthesis +<br/>under Illumination Changes +<br/>using Neural Networks +<br/>by +<br/>Under the supervision of +<br/>Prof. Daphna Weinshall +<br/>School of Computer Science and Engineering +<br/><b>The Hebrew University of Jerusalem</b><br/>Israel +<br/>Submitted in partial fulfillment of the +<br/>requirements of the degree of +<br/>Master of Science +<br/>December, 2017 +</td><td></td><td></td></tr><tr><td>eacba5e8fbafb1302866c0860fc260a2bdfff232</td><td>VOS-GAN: Adversarial Learning of Visual-Temporal <br/>Dynamics for Unsupervised Dense Prediction in Videos <br/>∗ Pattern Recognition and Computer Vision (PeRCeiVe) Lab <br/><b>University of Catania, Italy</b><br/>www.perceivelab.com @@ -28529,7 +36217,68 @@ <br/>Tunis, Tunisia, <br/>Tel: 9419010363; </td><td>('9304667', 'Hédi Trabelsi', 'hédi trabelsi')<br/>('2281259', 'Ines Malek', 'ines malek')<br/>('31649078', 'Imed Jabri', 'imed jabri')</td><td>E-mail: rabelg@live.fr -</td></tr><tr><td>ea85378a6549bb9eb9bcc13e31aa6a61b655a9af</td><td>Diplomarbeit +</td></tr><tr><td>eafda8a94e410f1ad53b3e193ec124e80d57d095</td><td>Jeffrey F. Cohn +<br/>13 +<br/>Observer-Based Measurement of Facial Expression +<br/>With the Facial Action Coding System +<br/>Facial expression has been a focus of emotion research for over +<br/>a hundred years (Darwin, 1872/1998). It is central to several +<br/>leading theories of emotion (Ekman, 1992; Izard, 1977; +<br/>Tomkins, 1962) and has been the focus of at times heated +<br/>debate about issues in emotion science (Ekman, 1973, 1993; +<br/>Fridlund, 1992; Russell, 1994). Facial expression figures +<br/>prominently in research on almost every aspect of emotion, +<br/>including psychophysiology (Levenson, Ekman, & Friesen, +<br/>1990), neural bases (Calder et al., 1996; Davidson, Ekman, +<br/>Saron, Senulis, & Friesen, 1990), development (Malatesta, +<br/>Culver, Tesman, & Shephard, 1989; Matias & Cohn, 1993), +<br/>perception (Ambadar, Schooler, & Cohn, 2005), social pro- +<br/>cesses (Hatfield, Cacioppo, & Rapson, 1992; Hess & Kirouac, +<br/>2000), and emotion disorder (Kaiser, 2002; Sloan, Straussa, +<br/>Quirka, & Sajatovic, 1997), to name a few. +<br/>Because of its importance to the study of emotion, a num- +<br/>ber of observer-based systems of facial expression measure- +<br/>ment have been developed (Ekman & Friesen, 1978, 1982; +<br/>Ekman, Friesen, & Tomkins, 1971; Izard, 1979, 1983; Izard +<br/>& Dougherty, 1981; Kring & Sloan, 1991; Tronick, Als, & +<br/>Brazelton, 1980). Of these various systems for describing +<br/>facial expression, the Facial Action Coding System (FACS; +<br/>Ekman & Friesen, 1978; Ekman, Friesen, & Hager, 2002) is +<br/>the most comprehensive, psychometrically rigorous, and +<br/>widely used (Cohn & Ekman, 2005; Ekman & Rosenberg, +<br/>2005). Using FACS and viewing video-recorded facial behav- +<br/>ior at frame rate and slow motion, coders can manually code +<br/>nearly all possible facial expressions, which are decomposed +<br/>into action units (AUs). Action units, with some qualifica- +<br/>tions, are the smallest visually discriminable facial move- +<br/>ments. By comparison, other systems are less thorough +<br/>(Malatesta et al., 1989), fail to differentiate between some +<br/>anatomically distinct movements (Oster, Hegley, & Nagel, +<br/>1992), consider movements that are not anatomically dis- +<br/>tinct as separable (Oster et al., 1992), and often assume a one- +<br/>to-one mapping between facial expression and emotion (for +<br/>a review of these systems, see Cohn & Ekman, in press). +<br/>Unlike systems that use emotion labels to describe ex- +<br/>pression, FACS explicitly distinguishes between facial actions +<br/>and inferences about what they mean. FACS itself is descrip- +<br/>tive and includes no emotion-specified descriptors. Hypoth- +<br/>eses and inferences about the emotional meaning of facial +<br/>actions are extrinsic to FACS. If one wishes to make emo- +<br/>tion-based inferences from FACS codes, a variety of related +<br/>resources exist. These include the FACS Investigators’ Guide +<br/>(Ekman et al., 2002), the FACS interpretive database (Ekman, +<br/>Rosenberg, & Hager, 1998), and a large body of empirical +<br/>research.(Ekman & Rosenberg, 2005). These resources sug- +<br/>gest combination rules for defining emotion-specified expres- +<br/>sions from FACS action units, but this inferential step remains +<br/>extrinsic to FACS. Because of its descriptive power, FACS +<br/>is regarded by many as the standard measure for facial be- +<br/>havior and is used widely in diverse fields. Beyond emo- +<br/>tion science, these include facial neuromuscular disorders +<br/>(Van Swearingen & Cohn, 2005), neuroscience (Bruce & +<br/>Young, 1998; Rinn, 1984, 1991), computer vision (Bartlett, +<br/>203 +<br/>UNPROOFED PAGES </td><td>('2059653', 'Zara Ambadar', 'zara ambadar')<br/>('21451088', 'Paul Ekman', 'paul ekman')</td><td></td></tr><tr><td>ea85378a6549bb9eb9bcc13e31aa6a61b655a9af</td><td>Diplomarbeit <br/>Template Protection for PCA-LDA-based 3D <br/>Face Recognition System <br/>von @@ -28544,13 +36293,130 @@ <br/>Edif. Central del Parque Cient´ıfico Tecnol´ogico <br/>Universidad de Las Palmas de Gran Canaria <br/>35017 - Spain -</td><td>('4643134', 'Javier Lorenzo-Navarro', 'javier lorenzo-navarro')</td><td></td></tr><tr><td>ea218cebea2228b360680cb85ca133e8c2972e56</td><td>Recover Canonical-View Faces in the 明Tild with Deep +</td><td>('4643134', 'Javier Lorenzo-Navarro', 'javier lorenzo-navarro')</td><td></td></tr><tr><td>ea890846912f16a0f3a860fce289596a7dac575f</td><td>ORIGINAL RESEARCH ARTICLE +<br/>published: 09 October 2014 +<br/>doi: 10.3389/fpsyg.2014.01154 +<br/>Benefits of social vs. non-social feedback on learning and +<br/>generosity. Results from theTipping Game +<br/><b>Tilburg Center for Logic, General Ethics, and Philosophy of Science, Tilburg University, Tilburg, Netherlands</b><br/><b>Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, UK</b><br/>Edited by: +<br/><b>Giulia Andrighetto, Institute of</b><br/>Cognitive Science and Technologies – +<br/>National Research Council, Italy +<br/>Reviewed by: +<br/><b>David R. Simmons, University of</b><br/>Glasgow, UK +<br/><b>Aron Szekely, University of Oxford, UK</b><br/>*Correspondence: +<br/>Logic, General Ethics, and Philosophy +<br/><b>of Science, Tilburg University</b><br/>P. O. Box 90153, 5000 LE +<br/>Tilburg, Netherlands +<br/>Stankevicius have contributed equally +<br/>to this work. +<br/>Although much work has recently been directed at understanding social decision-making, +<br/>relatively little is known about how different types of feedback impact adaptive changes +<br/>in social behavior. To address this issue quantitatively, we designed a novel associative +<br/>learning task called the “Tipping Game,” in which participants had to learn a social norm +<br/>of tipping in restaurants. Participants were found to make more generous decisions +<br/>from feedback in the form of facial expressions, +<br/>in comparison to feedback in the +<br/>form of symbols such as ticks and crosses. Furthermore, more participants displayed +<br/>learning in the condition where they received social feedback than participants in the non- +<br/>social condition. Modeling results showed that the pattern of performance displayed by +<br/>participants receiving social feedback could be explained by a lower sensitivity to economic +<br/>costs. +<br/>Keywords: social/non-social feedback, facial expressions, social norms, tipping behavior, associative learning +<br/>INTRODUCTION +<br/>Several behavioral, neurobiological and theoretical studies have +<br/>shown that social norm compliance, and more generally adap- +<br/>tive changes in social behavior, often require the effective use and +<br/><b>weighing of different types of information, including expected</b><br/>economic costs and benefits, the potential impact of our behavior +<br/>on the welfare of others and our own reputation, as well as feed- +<br/>back information (Bicchieri, 2006; Adolphs, 2009; Frith and Frith, +<br/>2012). Relatively little attention has been paid to how different +<br/>types of feedback (or reward) may impact the way social norms +<br/>are learned. The present study addresses this issue with behavioral +<br/>and modeling results from a novel associative learning task called +<br/>the “Tipping Game.” We take the example of tipping and ask: how +<br/>do social feedback in the form of facial expressions, as opposed +<br/>to non-social feedback in the form of such conventional signs as +<br/>ticks and crosses, affect the way participants learn a social norm +<br/>of tipping? +<br/>Recent findings indicate that people’s decision-making is often +<br/>biased by social stimuli. For example, images of a pair of eyes can +<br/>significantly increase pro-social behavior in laboratory conditions +<br/>as well as in real-world contexts (Haley and Fessler, 2005; Bateson +<br/>et al., 2006; Rigdon et al., 2009; Ernest-Jones et al., 2011). Fur- +<br/>thermore, decision-making can be systematically biased by facial +<br/>emotional expressions used as predictors of monetary reward +<br/>(Averbeck and Duchaine, 2009; Evans et al., 2011; Shore and +<br/>Heerey, 2011). Facial expressions of happiness elicit approach- +<br/>ing behavior, whereas angry faces elicit avoidance (Seidel et al., +<br/>2010; for a review seeBlair, 2003). Because they can function as +<br/>signals to others, eliciting specific behavioral responses, emotional +<br/>facial expressions play a major role in socialization practices that +<br/>help individuals to adapt to the norms and values of their culture +<br/>(Keltner and Haidt, 1999; Frith, 2009). +<br/>Despite this body of findings, the literature does not pro- +<br/>vide an unambiguous answer to the question of how learning +<br/>performance is affected by social stimuli in comparison to differ- +<br/>ent types of non-social stimuli used as feedback about previous +<br/>decisions in a learning task (Ruff and Fehr, 2014). Consistent +<br/>with the view that social reinforcement is a powerful facili- +<br/>tator of human learning (Zajonc, 1965; Bandura, 1977), one +<br/>recent study using a feedback-guided item-category association +<br/>task found that learning performance in control groups was +<br/>improved when social (smiling or angry faces) instead of non- +<br/>social (green or red lights) reinforcement was used (Hurlemann +<br/>et al., 2010). +<br/>However, the paradigm used in this study did not distin- +<br/>guish between two conditions in which social-facilitative effects +<br/>on learning performance have been observed: first, a condition +<br/>characterized by the mere presence of others (Allport, 1920); and +<br/>second, a condition where others provide reinforcing feedback +<br/>(Zajonc, 1965). In the task used by Hurlemann et al. (2010), faces +<br/>were present onscreen throughout each trial, changing from a +<br/>neutral to a happy expression for correct responses or angry for +<br/>incorrect responses. So, this study could not identify the specific +<br/>effect of social feedback on learning. +<br/>Consistent with the assumption oft made in economics and +<br/>psychology that optimal decisions and learning are based on an +<br/>assessment of the evidence that is unbiased by the social or non- +<br/>social nature of the evidence itself (Becker, 1976; Oaksford and +<br/>Chater, 2007), Lin et al. (2012a) found that, instead of boosting +<br/>learning performance, social reward (smiling or angry faces) made +<br/>www.frontiersin.org +<br/>October 2014 | Volume 5 | Article 1154 | 1 +</td><td>('37157064', 'Matteo Colombo', 'matteo colombo')<br/>('25749361', 'Aistis Stankevicius', 'aistis stankevicius')<br/>('2771872', 'Peggy Seriès', 'peggy seriès')<br/>('37157064', 'Matteo Colombo', 'matteo colombo')<br/>('37157064', 'Matteo Colombo', 'matteo colombo')</td><td>e-mail: m.colombo@uvt.nl +</td></tr><tr><td>eaaed082762337e7c3f8a1b1dfea9c0d3ca281bf</td><td><b>VICTORIA UNIVERSITY OF WELLINGTON</b><br/>Te Whare Wananga o te Upoko o te Ika a Maui +<br/>School of Mathematics, Statistics and Computer Science +<br/>Computer Science +<br/>Algebraic Simplification of Genetic +<br/>Programs during Evolution +<br/>Technical Report CS-TR-06/7 +<br/>February 2006 +<br/>School of Mathematics, Statistics and Computer Science +<br/><b>Victoria University</b><br/>PO Box 600, Wellington +<br/>New Zealand +<br/>Tel: +64 4 463 5341 +<br/>Fax: +64 4 463 5045 +<br/>http://www.mcs.vuw.ac.nz/research +</td><td>('1679067', 'Mengjie Zhang', 'mengjie zhang')</td><td>Email: Tech.Reports@mcs.vuw.ac.nz +</td></tr><tr><td>ea218cebea2228b360680cb85ca133e8c2972e56</td><td>Recover Canonical-View Faces in the 明Tild with Deep <br/>Neural Networks <br/><b>Departm nt of Information Engin ering Th Chines University of Hong Kong</b><br/><b>The Chinese University ofHong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b><br/>zz 012 日 ie . cuh k. edu . h k </td><td>('2042558', 'Zhenyao Zhu', 'zhenyao zhu')<br/>('1693209', 'Ping Luo', 'ping luo')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>xgwang@ee . cuhk . edu . hk <br/>p 1 uo .1 h 工 @gm a i l . com <br/>xtang@ i e . cuhk. edu . hk -</td></tr><tr><td>ea96bc017fb56593a59149e10d5f14011a3744a0</td><td></td><td></td><td></td></tr><tr><td>e10a257f1daf279e55f17f273a1b557141953ce2</td><td></td><td></td><td></td></tr><tr><td>e171fba00d88710e78e181c3e807c2fdffc6798a</td><td></td><td></td><td></td></tr><tr><td>e1c59e00458b4dee3f0e683ed265735f33187f77</td><td>Spectral Rotation versus K-Means in Spectral Clustering +</td></tr><tr><td>ea96bc017fb56593a59149e10d5f14011a3744a0</td><td></td><td></td><td></td></tr><tr><td>e1630014a5ae3d2fb7ff6618f1470a567f4d90f5</td><td>Look, Listen and Learn - A Multimodal LSTM for Speaker Identification +<br/>SenseTime Group Limited1 +<br/><b>The University of Hong Kong</b><br/>Project page: http://www.deeplearning.cc/mmlstm +</td><td>('46972608', 'Yongtao Hu', 'yongtao hu')</td><td>{rensijie, yuwing, xuli, sunwenxiu, yanqiong}@sensetime.com +<br/>{herohuyongtao, wangchuan2400}@gmail.com +</td></tr><tr><td>e19fb22b35c352f57f520f593d748096b41a4a7b</td><td>Modeling Context for Image +<br/>Understanding: +<br/>When, For What, and How? +<br/>Department of Electrical and Computer Engineering, +<br/><b>Carnegie Mellon University</b><br/>A thesis submitted for the degree of +<br/>Doctor of Philosophy +<br/>April 3, 2009 +</td><td>('1713589', 'Devi Parikh', 'devi parikh')</td><td></td></tr><tr><td>e10a257f1daf279e55f17f273a1b557141953ce2</td><td></td><td></td><td></td></tr><tr><td>e171fba00d88710e78e181c3e807c2fdffc6798a</td><td></td><td></td><td></td></tr><tr><td>e1c59e00458b4dee3f0e683ed265735f33187f77</td><td>Spectral Rotation versus K-Means in Spectral Clustering <br/>Computer Science and Engineering Department <br/><b>University of Texas at Arlington</b><br/>Arlington,TX,76019 </td><td>('39122448', 'Jin Huang', 'jin huang')<br/>('1688370', 'Feiping Nie', 'feiping nie')<br/>('1748032', 'Heng Huang', 'heng huang')</td><td>huangjinsuzhou@gmail.com, feipingnie@gmail.com, heng@uta.edu @@ -28575,7 +36441,9 @@ <br/>r.hofmann@campus.tu-berlin.de <br/>ahmmed@campus.tu-berlin.de <br/>kashefy@ni.tu-berlin.de -</td></tr><tr><td>e16efd2ae73a325b7571a456618bfa682b51aef8</td><td></td><td></td><td></td></tr><tr><td>e13360cda1ebd6fa5c3f3386c0862f292e4dbee4</td><td></td><td></td><td></td></tr><tr><td>e1f6e2651b7294951b5eab5d2322336af1f676dc</td><td>Appl. Math. Inf. Sci. 9, No. 2L, 461-469 (2015) +</td></tr><tr><td>e16efd2ae73a325b7571a456618bfa682b51aef8</td><td></td><td></td><td></td></tr><tr><td>e19ebad4739d59f999d192bac7d596b20b887f78</td><td>Learning Gating ConvNet for Two-Stream based Methods in Action +<br/>Recognition +</td><td>('1696573', 'Jiagang Zhu', 'jiagang zhu')<br/>('1726367', 'Wei Zou', 'wei zou')<br/>('48147901', 'Zheng Zhu', 'zheng zhu')</td><td></td></tr><tr><td>e13360cda1ebd6fa5c3f3386c0862f292e4dbee4</td><td></td><td></td><td></td></tr><tr><td>e1f6e2651b7294951b5eab5d2322336af1f676dc</td><td>Appl. Math. Inf. Sci. 9, No. 2L, 461-469 (2015) <br/>461 <br/>Applied Mathematics & Information Sciences <br/>An International Journal @@ -28584,7 +36452,19 @@ <br/>Animation based on Facial Expression Analysis <br/><b>Sejong University, 98 Gunja, Gwangjin, Seoul 143-747, Korea</b><br/>Received: 22 May 2014, Revised: 23 Jul. 2014, Accepted: 24 Jul. 2014 <br/>Published online: 1 Apr. 2015 -</td><td>('2137943', 'Taehoon Cho', 'taehoon cho')<br/>('4027010', 'Jin-Ho Choi', 'jin-ho choi')<br/>('2849238', 'Hyeon-Joong Kim', 'hyeon-joong kim')<br/>('7236280', 'Soo-Mi Choi', 'soo-mi choi')</td><td></td></tr><tr><td>e1e6e6792e92f7110e26e27e80e0c30ec36ac9c2</td><td>TSINGHUA SCIENCE AND TECHNOLOGY +</td><td>('2137943', 'Taehoon Cho', 'taehoon cho')<br/>('4027010', 'Jin-Ho Choi', 'jin-ho choi')<br/>('2849238', 'Hyeon-Joong Kim', 'hyeon-joong kim')<br/>('7236280', 'Soo-Mi Choi', 'soo-mi choi')</td><td></td></tr><tr><td>e1d726d812554f2b2b92cac3a4d2bec678969368</td><td>J Electr Eng Technol.2015; 10(?): 30-40 +<br/>http://dx.doi.org/10.5370/JEET.2015.10.2.030 +<br/>ISSN(Print) +<br/>1975-0102 +<br/>ISSN(Online) 2093-7423 +<br/>Human Action Recognition Bases on Local Action Attributes +<br/>and Mohan S Kankanhalli** +</td><td>('3132751', 'Weizhi Nie', 'weizhi nie')<br/>('3026404', 'Yongkang Wong', 'yongkang wong')</td><td></td></tr><tr><td>e1256ff535bf4c024dd62faeb2418d48674ddfa2</td><td>Towards Open-Set Identity Preserving Face Synthesis +<br/><b>University of Science and Technology of China</b><br/>2Microsoft Research +</td><td>('3093568', 'Jianmin Bao', 'jianmin bao')<br/>('39447786', 'Dong Chen', 'dong chen')<br/>('1716835', 'Fang Wen', 'fang wen')<br/>('7179232', 'Houqiang Li', 'houqiang li')<br/>('1745420', 'Gang Hua', 'gang hua')</td><td>{doch, fangwen, ganghua}@microsoft.com +<br/>lihq@ustc.edu.cn +<br/>jmbao@mail.ustc.edu.cn +</td></tr><tr><td>e1e6e6792e92f7110e26e27e80e0c30ec36ac9c2</td><td>TSINGHUA SCIENCE AND TECHNOLOGY <br/>ISSNll1007-0214 <br/>0?/?? pp???–??? <br/>DOI: 10.26599/TST.2018.9010000 @@ -28593,7 +36473,46 @@ </td><td>('39021559', 'Muge Li', 'muge li')<br/>('2897748', 'Liangyue Li', 'liangyue li')<br/>('1688370', 'Feiping Nie', 'feiping nie')</td><td></td></tr><tr><td>cd9666858f6c211e13aa80589d75373fd06f6246</td><td>A Novel Time Series Kernel for <br/>Sequences Generated by LTI Systems <br/>V.le delle Scienze Ed.6, DIID, Universit´a degli studi di Palermo, Italy -</td><td>('1711610', 'Liliana Lo Presti', 'liliana lo presti')<br/>('9127836', 'Marco La Cascia', 'marco la cascia')</td><td></td></tr><tr><td>cd4c047f4d4df7937aff8fc76f4bae7718004f40</td><td></td><td></td><td></td></tr><tr><td>cd596a2682d74bdfa7b7160dd070b598975e89d9</td><td>Mood Detection: Implementing a facial +</td><td>('1711610', 'Liliana Lo Presti', 'liliana lo presti')<br/>('9127836', 'Marco La Cascia', 'marco la cascia')</td><td></td></tr><tr><td>cdc7bd87a2c9983dab728dbc8aac74d8c9ed7e66</td><td>What Makes a Video a Video: Analyzing Temporal Information in Video +<br/>Understanding Models and Datasets +<br/><b>Stanford University, 2Facebook, 3Dartmouth College</b></td><td>('38485317', 'De-An Huang', 'de-an huang')<br/>('34066479', 'Vignesh Ramanathan', 'vignesh ramanathan')<br/>('49274550', 'Dhruv Mahajan', 'dhruv mahajan')<br/>('1732879', 'Lorenzo Torresani', 'lorenzo torresani')<br/>('2210374', 'Manohar Paluri', 'manohar paluri')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')</td><td></td></tr><tr><td>cd4941cbef1e27d7afdc41b48c1aff5338aacf06</td><td>MovieGraphs: Towards Understanding Human-Centric Situations from Videos +<br/><b>University of Toronto</b><br/><b>Vector Institute</b><br/>Lluís Castrejón3 +<br/><b>Montreal Institute for Learning Algorithms</b><br/>http://moviegraphs.cs.toronto.edu +<br/>Figure 1: An example from the MovieGraphs dataset. Each of the 7637 video clips is annotated with: 1) a graph that captures the characters +<br/>in the scene and their attributes, interactions (with topics and reasons), relationships, and time stamps; 2) a situation label that captures the +<br/>overarching theme of the interactions; 3) a scene label showing where the action takes place; and 4) a natural language description of the +<br/>clip. The graphs at the bottom show situations that occur before and after the one depicted in the main panel. +</td><td>('2039154', 'Paul Vicol', 'paul vicol')<br/>('2103464', 'Makarand Tapaswi', 'makarand tapaswi')<br/>('37895334', 'Sanja Fidler', 'sanja fidler')</td><td>{pvicol, makarand, fidler}@cs.toronto.edu, lluis.enric.castrejon.subira@umontreal.ca +</td></tr><tr><td>cd4c047f4d4df7937aff8fc76f4bae7718004f40</td><td></td><td></td><td></td></tr><tr><td>cdef0eaff4a3c168290d238999fc066ebc3a93e8</td><td>CONTRASTIVE-CENTER LOSS FOR DEEP NEURAL NETWORKS +<br/>1School of Information and Communication Engineering +<br/>2Beijing Key Laboratory of Network System and Network Culture +<br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>('49712251', 'Ce Qi', 'ce qi')<br/>('1684263', 'Fei Su', 'fei su')</td><td></td></tr><tr><td>cd444ee7f165032b97ee76b21b9ff58c10750570</td><td><b>UNIVERSITY OF CALIFORNIA</b><br/>IRVINE +<br/>Relational Models for Human-Object Interactions and Object Affordances +<br/>DISSERTATION +<br/>submitted in partial satisfaction of the requirements +<br/>for the degree of +<br/>DOCTOR OF PHILOSOPHY +<br/>in Computer Science +<br/>by +<br/>Dissertation Committee: +<br/>Professor Deva Ramanan, Chair +<br/>Professor Charless Fowlkes +<br/>Professor Padhraic Smyth +<br/>Professor Serge Belongie +<br/>2013 +</td><td>('40277674', 'Chaitanya Desai', 'chaitanya desai')</td><td></td></tr><tr><td>cd23dc3227ee2a3ab0f4de1817d03ca771267aeb</td><td>WU, KAMATA, BRECKON: FACE RECOGNITION VIA DSGNN +<br/>Face Recognition via Deep Sparse Graph +<br/>Neural Networks +<br/>Renjie WU1 +<br/>Toby Breckon2 +<br/>1 Graduate School of Information, +<br/>Production and Systems +<br/><b>Waseda University</b><br/>Kitakyushu-shi, Japan +<br/>2 Engineering and Computing Sciences +<br/><b>Durham University, Durham, UK</b></td><td>('35222422', 'Sei-ichiro Kamata', 'sei-ichiro kamata')</td><td>wurj-sjtu-waseda@ruri.waseda.jp +<br/>kam@waseda.jp +<br/>toby.breckon@durham.ac.uk +</td></tr><tr><td>cd596a2682d74bdfa7b7160dd070b598975e89d9</td><td>Mood Detection: Implementing a facial <br/>expression recognition system <br/>1. Introduction <br/>Facial expressions play a significant role in human dialogue. As a result, there has been @@ -28640,6 +36559,29 @@ <br/>Privileged Information for Visual Recognition <br/>Lane Department of Computer Science and Electrical Engineering <br/><b>West Virginia University</b></td><td>('2897426', 'Saeid Motiian', 'saeid motiian')<br/>('1736352', 'Gianfranco Doretto', 'gianfranco doretto')</td><td>{samotiian,gidoretto}@mix.wvu.edu +</td></tr><tr><td>cd2c54705c455a4379f45eefdf32d8d10087e521</td><td>A Hybrid Model for Identity Obfuscation by +<br/>Face Replacement +<br/><b>Max Planck Institute for Informatics, Saarland Informatics Campus</b></td><td>('32222907', 'Qianru Sun', 'qianru sun')<br/>('1739548', 'Mario Fritz', 'mario fritz')</td><td>{qsun, atewari, wxu, mfritz, theobalt, schiele}@mpi-inf.mpg.de +</td></tr><tr><td>cd7a7be3804fd217e9f10682e0c0bfd9583a08db</td><td>Women also Snowboard: +<br/>Overcoming Bias in Captioning Models +</td><td>('40895688', 'Kaylee Burns', 'kaylee burns')</td><td></td></tr><tr><td>cd023d2d067365c83d8e27431e83e7e66082f718</td><td>Real-Time Rotation-Invariant Face Detection with +<br/>Progressive Calibration Networks +<br/>1 Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), +<br/><b>Institute of Computing Technology, CAS, Beijing 100190, China</b><br/><b>University of Chinese Academy of Sciences, Beijing 100049, China</b><br/>3 CAS Center for Excellence in Brain Science and Intelligence Technology +</td><td>('41017549', 'Xuepeng Shi', 'xuepeng shi')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1693589', 'Meina Kan', 'meina kan')<br/>('3126238', 'Shuzhe Wu', 'shuzhe wu')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td>{xuepeng.shi, shiguang.shan, meina.kan, shuzhe.wu, xilin.chen}@vipl.ict.ac.cn +</td></tr><tr><td>cca9ae621e8228cfa787ec7954bb375536160e0d</td><td>Learning to Collaborate for User-Controlled Privacy +<br/>Martin Bertran 1† +<br/>Natalia Martinez 1†* +<br/>Afroditi Papadaki 2 +<br/>Miguel Rodrigues 2 +<br/><b>Duke University, Durham, NC, USA</b><br/><b>University College London, London, UK</b><br/>†These authors contributed equally to this work. +<br/>Privacy is a human right. Tim Cook, Apple CEO. +</td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('1699339', 'Guillermo Sapiro', 'guillermo sapiro')</td><td>martin.bertran@duke.edu +<br/>natalia.martinez@duke.edu +<br/>a.papadaki.17@ucl.ac.uk +<br/>qiuqiang@gmail.com +<br/>m.rodrigues@ucl.ac.uk +<br/>guillermo.sapiro@duke.edu </td></tr><tr><td>cc589c499dcf323fe4a143bbef0074c3e31f9b60</td><td>A 3D Facial Expression Database For Facial Behavior Research <br/><b>State University of New York at Binghamton</b></td><td>('8072251', 'Lijun Yin', 'lijun yin')</td><td></td></tr><tr><td>ccfcbf0eda6df876f0170bdb4d7b4ab4e7676f18</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 6, NO. 1, JUNE 2011 <br/>A Dynamic Appearance Descriptor Approach to @@ -28710,13 +36652,29 @@ <br/>Cinema and other aspects of film and video creation. <br/>PROJECT DATE 2014 <br/>URL http://misharabinovich.com/soyummy.html -</td><td>('40462877', 'MISHA RABINOVICH', 'misha rabinovich')<br/>('1679896', 'Yogesh Girdhar', 'yogesh girdhar')</td><td></td></tr><tr><td>ccf43c62e4bf76b6a48ff588ef7ed51e87ddf50b</td><td>American Journal of Food Science and Health +</td><td>('40462877', 'MISHA RABINOVICH', 'misha rabinovich')<br/>('1679896', 'Yogesh Girdhar', 'yogesh girdhar')</td><td></td></tr><tr><td>cc8e378fd05152a81c2810f682a78c5057c8a735</td><td>International Journal of Computer Sciences and Engineering Open Access +<br/> Research Paper Volume-5, Issue-12 E-ISSN: 2347-2693 +<br/>Expression Invariant Face Recognition System based on Topographic +<br/>Independent Component Analysis and Inner Product Classifier +<br/> +<br/>Department of Electrical Engineering, IIT Delhi, New Delhi, India +<br/>Available online at: www.ijcseonline.org +<br/>Received: 07/Nov/2017, Revised: 22/Nov/2017, Accepted: 14/Dec/2017, Published: 31/Dec/2017 +</td><td>('40258123', 'Aruna Bhat', 'aruna bhat')</td><td>*Corresponding Author: abigit06@yahoo.com +</td></tr><tr><td>ccf43c62e4bf76b6a48ff588ef7ed51e87ddf50b</td><td>American Journal of Food Science and Health <br/>Vol. 2, No. 2, 2016, pp. 7-17 <br/>http://www.aiscience.org/journal/ajfsh <br/>ISSN: 2381-7216 (Print); ISSN: 2381-7224 (Online) <br/>Nutraceuticals and Cosmeceuticals for Human <br/>Beings–An Overview -<br/><b>Narayana Pharmacy College, Nellore, India</b></td><td>('40179150', 'R. Ramasubramania Raja', 'r. ramasubramania raja')</td><td></td></tr><tr><td>cc8bf03b3f5800ac23e1a833447c421440d92197</td><td></td><td></td><td></td></tr><tr><td>cc91001f9d299ad70deb6453d55b2c0b967f8c0d</td><td>OPEN ACCESS +<br/><b>Narayana Pharmacy College, Nellore, India</b></td><td>('40179150', 'R. Ramasubramania Raja', 'r. ramasubramania raja')</td><td></td></tr><tr><td>cc31db984282bb70946f6881bab741aa841d3a7c</td><td>ALBANIE, VEDALDI: LEARNING GRIMACES BY WATCHING TV +<br/>Learning Grimaces by Watching TV +<br/>http://www.robots.ox.ac.uk/~albanie +<br/>http://www.robots.ox.ac.uk/~vedaldi +<br/>Engineering Science Department +<br/>Univeristy of Oxford +<br/>Oxford, UK +</td><td>('7641268', 'Samuel Albanie', 'samuel albanie')<br/>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')</td><td></td></tr><tr><td>cc8bf03b3f5800ac23e1a833447c421440d92197</td><td></td><td></td><td></td></tr><tr><td>cc91001f9d299ad70deb6453d55b2c0b967f8c0d</td><td>OPEN ACCESS <br/>ISSN 2073-8994 <br/>Article <br/>Performance Enhancement of Face Recognition in Smart TV @@ -28741,6 +36699,9 @@ </td></tr><tr><td>cc9057d2762e077c53e381f90884595677eceafa</td><td>On the Exploration of Joint Attribute Learning <br/>for Person Re-identification <br/><b>Michigan State University</b></td><td>('38993748', 'Joseph Roth', 'joseph roth')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>{rothjos1,liuxm}@cse.msu.edu +</td></tr><tr><td>ccf16bcf458e4d7a37643b8364594656287f5bfc</td><td>A CNN Cascade for Landmark Guided Semantic +<br/>Part Segmentation +<br/><b>School of Computer Science, The University of Nottingham, Nottingham, UK</b></td><td>('34596685', 'Aaron S. Jackson', 'aaron s. jackson')<br/>('46637307', 'Michel Valstar', 'michel valstar')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td>{aaron.jackson, michel.valstar, yorgos.tzimiropoulos}@nottingham.ac.uk </td></tr><tr><td>e64b683e32525643a9ddb6b6af8b0472ef5b6a37</td><td>Face Recognition and Retrieval in Video </td><td>('10795229', 'Caifeng Shan', 'caifeng shan')</td><td></td></tr><tr><td>e69ac130e3c7267cce5e1e3d9508ff76eb0e0eef</td><td>Research Article <br/>Addressing the illumination challenge in two- @@ -28754,6 +36715,11 @@ <br/><b>Computational Biomedicine Laboratory, University of Houston, Houston, Texas 77204, USA</b><br/>2Department of Computer Science, Cybersecurity Laboratory, Instituto Tecnológico y de Estudios Superiores de Monterrey, Monterrey, <br/>NL 64840, Mexico </td><td>('2899018', 'Miguel A. Ochoa-Villegas', 'miguel a. ochoa-villegas')<br/>('1905427', 'Olivia Barron-Cano', 'olivia barron-cano')<br/>('1706204', 'Ioannis A. Kakadiaris', 'ioannis a. kakadiaris')</td><td>✉ E-mail: ioannisk@uh.edu +</td></tr><tr><td>e6b45d5a86092bbfdcd6c3c54cda3d6c3ac6b227</td><td>Pairwise Relational Networks for Face +<br/>Recognition +<br/>1 Department of Creative IT Engineering, POSTECH, Korea +<br/>2 Department of Computer Science and Engineering, POSTECH, Korea +</td><td>('2794366', 'Bong-Nam Kang', 'bong-nam kang')<br/>('50682377', 'Yonghyun Kim', 'yonghyun kim')<br/>('1695669', 'Daijin Kim', 'daijin kim')</td><td>{bnkang,gkyh0805,dkim}@postech.ac.kr </td></tr><tr><td>e6865b000cf4d4e84c3fe895b7ddfc65a9c4aaec</td><td>Chapter 15. The critical role of the <br/>cold-start problem and incentive systems <br/>in emotional Web 2.0 services @@ -28771,7 +36737,19 @@ </td><td>('1688370', 'Feiping Nie', 'feiping nie')<br/>('1714390', 'Dong Xu', 'dong xu')<br/>('1700883', 'Changshui Zhang', 'changshui zhang')</td><td></td></tr><tr><td>e6f20e7431172c68f7fce0d4595100445a06c117</td><td>Searching Action Proposals via Spatial <br/>Actionness Estimation and Temporal Path <br/>Inference and Tracking -<br/><b>cid:93)Peking University Shenzhen Graduate School, Shenzhen, P.R.China</b><br/><b>DISI, University of Trento, Trento, Italy</b></td><td>('40147776', 'Dan Xu', 'dan xu')<br/>('3238696', 'Zhihao Li', 'zhihao li')<br/>('1684933', 'Ge Li', 'ge li')</td><td></td></tr><tr><td>e6540d70e5ffeed9f447602ea3455c7f0b38113e</td><td></td><td></td><td></td></tr><tr><td>e6ee36444038de5885473693fb206f49c1369138</td><td></td><td></td><td></td></tr><tr><td>e6178de1ef15a6a973aad2791ce5fbabc2cb8ae5</td><td>Improving Facial Landmark Detection via a +<br/><b>cid:93)Peking University Shenzhen Graduate School, Shenzhen, P.R.China</b><br/><b>DISI, University of Trento, Trento, Italy</b></td><td>('40147776', 'Dan Xu', 'dan xu')<br/>('3238696', 'Zhihao Li', 'zhihao li')<br/>('1684933', 'Ge Li', 'ge li')</td><td></td></tr><tr><td>e6e5a6090016810fb902b51d5baa2469ae28b8a1</td><td>Title +<br/>Energy-Efficient Deep In-memory Architecture for NAND +<br/>Flash Memories +<br/>Archived version +<br/>Accepted manuscript: the content is same as the published +<br/>paper but without the final typesetting by the publisher +<br/>Published version +<br/>DOI +<br/>Published paper +<br/>URL +<br/>Authors (contact) +<br/>10.1109/ISCAS.2018.8351458 +</td><td></td><td></td></tr><tr><td>e6540d70e5ffeed9f447602ea3455c7f0b38113e</td><td></td><td></td><td></td></tr><tr><td>e6ee36444038de5885473693fb206f49c1369138</td><td></td><td></td><td></td></tr><tr><td>e6178de1ef15a6a973aad2791ce5fbabc2cb8ae5</td><td>Improving Facial Landmark Detection via a <br/>Super-Resolution Inception Network <br/><b>Institute for Human-Machine Communication</b><br/><b>Technical University of Munich, Germany</b></td><td>('38746426', 'Martin Knoche', 'martin knoche')<br/>('3044182', 'Daniel Merget', 'daniel merget')<br/>('1705843', 'Gerhard Rigoll', 'gerhard rigoll')</td><td></td></tr><tr><td>f913bb65b62b0a6391ffa8f59b1d5527b7eba948</td><td></td><td></td><td></td></tr><tr><td>f9784db8ff805439f0a6b6e15aeaf892dba47ca0</td><td>Comparing the performance of Emotion-Recognition Implementations <br/>in OpenCV, Cognitive Services, and Google Vision APIs @@ -28877,7 +36855,10 @@ <br/>for the degree of <br/>Computer Science– Doctor of Philosophy <br/>2013 -</td><td>('31508481', 'Alessandra Aparecida Paulino', 'alessandra aparecida paulino')</td><td></td></tr><tr><td>f96bdd1e2a940030fb0a89abbe6c69b8d7f6f0c1</td><td></td><td></td><td></td></tr><tr><td>f93606d362fcbe62550d0bf1b3edeb7be684b000</td><td>The Computer Journal Advance Access published February 1, 2012 +</td><td>('31508481', 'Alessandra Aparecida Paulino', 'alessandra aparecida paulino')</td><td></td></tr><tr><td>f92ade569cbe54344ffd3bb25efd366dcd8ad659</td><td>EFFECT OF SUPER RESOLUTION ON HIGH DIMENSIONAL FEATURES FOR +<br/>UNSUPERVISED FACE RECOGNITION IN THE WILD +<br/><b>University of Bridgeport, Bridgeport, CT 06604, USA</b></td><td>('40373065', 'Ahmed ElSayed', 'ahmed elsayed')<br/>('37374395', 'Ausif Mahmood', 'ausif mahmood')</td><td>Emails: aelsayed@my.bridgeport.edu, {mahmood,sobh}@bridgeport.edu +</td></tr><tr><td>f96bdd1e2a940030fb0a89abbe6c69b8d7f6f0c1</td><td></td><td></td><td></td></tr><tr><td>f93606d362fcbe62550d0bf1b3edeb7be684b000</td><td>The Computer Journal Advance Access published February 1, 2012 <br/><b>The Author 2012. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved</b><br/>doi:10.1093/comjnl/bxs001 <br/>Nearest Neighbor Classifier Based <br/>on Nearest Feature Decisions @@ -28942,6 +36923,19 @@ <br/>The Computer Journal, 2012 </td><td>('1744784', 'Alex Pappachen James', 'alex pappachen james')<br/>('1697594', 'Sima Dimitrijev', 'sima dimitrijev')</td><td>For Permissions, please email: journals.permissions@oup.com <br/>Corresponding author: apj@ieee.org +</td></tr><tr><td>f94f366ce14555cf0d5d34248f9467c18241c3ee</td><td>Deep Convolutional Neural Network in +<br/>Deformable Part Models for Face Detection +<br/><b>University of Science, Vietnam National University, HCMC</b><br/><b>School of Information Science, Japan Advanced Institute of Science and Technology</b></td><td>('2187730', 'Dinh-Luan Nguyen', 'dinh-luan nguyen')<br/>('34453615', 'Vinh-Tiep Nguyen', 'vinh-tiep nguyen')<br/>('1780348', 'Minh-Triet Tran', 'minh-triet tran')<br/>('2854896', 'Atsuo Yoshitaka', 'atsuo yoshitaka')</td><td>1212223@student.hcmus.edu.vn +<br/>{nvtiep,tmtriet}@fit.hcmus.edu.vn +<br/>ayoshi@jaist.ac.jp +</td></tr><tr><td>f997a71f1e54d044184240b38d9dc680b3bbbbc0</td><td>Deep Cross Modal Learning for Caricature Verification and +<br/>Identification(CaVINet) +<br/>https://lsaiml.github.io/CaVINet/ +<br/><b>Indian Institute of Technology Ropar</b><br/><b>Indian Institute of Technology Ropar</b><br/><b>Indian Institute of Technology Ropar</b><br/>Narayanan C Krishnan +<br/><b>Indian Institute of Technology Ropar</b></td><td>('6220011', 'Jatin Garg', 'jatin garg')<br/>('51152207', 'Himanshu Tolani', 'himanshu tolani')<br/>('41021778', 'Skand Vishwanath Peri', 'skand vishwanath peri')</td><td>2014csb1017@iitrpr.ac.in +<br/>2014csb1015@iitrpr.ac.in +<br/>pvskand@gmail.com +<br/>ckn@iitrpr.ac.in </td></tr><tr><td>f909d04c809013b930bafca12c0f9a8192df9d92</td><td>Single Image Subspace for Face Recognition <br/><b>Nanjing University of Aeronautics and Astronautics, China</b><br/>1 Department of Computer Science and Engineering, <br/>2 National Key Laboratory for Novel Software Technology, @@ -28954,8 +36948,21 @@ <br/>information using depth sensors <br/><b>Kingston University London, University of Westminster London</b><br/><b>Imperial College London</b></td><td>('1686887', 'Juan Manuel Fernandez Montenegro', 'juan manuel fernandez montenegro')<br/>('2866802', 'Barbara Villarini', 'barbara villarini')<br/>('2140622', 'Athanasios Gkelias', 'athanasios gkelias')<br/>('1689047', 'Vasileios Argyriou', 'vasileios argyriou')</td><td>Juan.Fernandez@kingston.ac.uk,B.Villarini@westminster.ac.uk,A.Gkelias@ <br/>imperial.ac.uk,Vasileios.Argyriou@kingston.ac.uk +</td></tr><tr><td>f08e425c2fce277aedb51d93757839900d591008</td><td>Neural Motifs: Scene Graph Parsing with Global Context +<br/><b>Paul G. Allen School of Computer Science and Engineering, University of Washington</b><br/><b>Allen Institute for Arti cial Intelligence</b><br/><b>School of Computer Science, Carnegie Mellon University</b><br/>https://rowanzellers.com/neuralmotifs +</td><td>('2545335', 'Rowan Zellers', 'rowan zellers')<br/>('38094552', 'Sam Thomson', 'sam thomson')</td><td>{rowanz, my89, yejin}@cs.washington.edu, sthomson@cs.cmu.edu </td></tr><tr><td>f02f0f6fcd56a9b1407045de6634df15c60a85cd</td><td>Learning Low-shot facial representations via 2D warping <br/><b>RWTH Aachen University</b></td><td>('35362682', 'Shen Yan', 'shen yan')</td><td>shen.yan@rwth-aachen.de +</td></tr><tr><td>f0cee87e9ecedeb927664b8da44b8649050e1c86</td><td></td><td></td><td></td></tr><tr><td>f0f4f16d5b5f9efe304369120651fa688a03d495</td><td>Temporal Generative Adversarial Nets +<br/>Preferred Networks inc., Japan +</td><td>('49160719', 'Masaki Saito', 'masaki saito')<br/>('8252749', 'Eiichi Matsumoto', 'eiichi matsumoto')</td><td>{msaito, matsumoto}@preferred.jp +</td></tr><tr><td>f0ca31fd5cad07e84b47d50dc07db9fc53482a46</td><td>Advances in Pure Mathematics, 2012, 2, 226-242 +<br/>http://dx.doi.org/10.4236/apm.2012.24033 Published Online July 2012 (http://www.SciRP.org/journal/apm) +<br/>Feature Patch Illumination Spaces and Karcher +<br/>Compression for Face Recognition via +<br/>Grassmannians +<br/><b>California State University, Long Beach, USA</b><br/><b>Colorado State University, Fort Collins, USA</b><br/>Received January 7, 2012; revised February 20, 2012; accepted February 27, 2012 +</td><td>('2640182', 'Jen-Mei Chang', 'jen-mei chang')<br/>('30383278', 'Chris Peterson', 'chris peterson')<br/>('41211081', 'Michael Kirby', 'michael kirby')</td><td>Email: jen-mei.chang@csulb.edu, {peterson, Kirby}@math.colostate.edu </td></tr><tr><td>f0ae807627f81acb63eb5837c75a1e895a92c376</td><td>International Journal of Emerging Engineering Research and Technology <br/>Volume 3, Issue 12, December 2015, PP 128-133 <br/>ISSN 2349-4395 (Print) & ISSN 2349-4409 (Online) @@ -28972,6 +36979,10 @@ </td><td>('1710408', 'Xin Fan', 'xin fan')<br/>('7864960', 'Zhongxuan Luo', 'zhongxuan luo')<br/>('1732068', 'Jielin Zhang', 'jielin zhang')<br/>('2758604', 'Xinchen Zhou', 'xinchen zhou')<br/>('2235253', 'Qi Jia', 'qi jia')<br/>('3136305', 'Daiyun Luo', 'daiyun luo')</td><td>E-Mails: xin.fan@ieee.org (X.F.); jiaqi7166@gmail.com (Q.J.) <br/>China; E-Mails: jielinzh@dlut.edu.cn (J.Z.); dasazxc@gmail.com (X.Z.); 419524597@qq.com (D.L.) <br/>* Author to whom correspondence should be addressed; E-Mail: zxluo@dlut.edu.cn; +</td></tr><tr><td>f0a4a3fb6997334511d7b8fc090f9ce894679faf</td><td>Generative Face Completion +<br/><b>University of California, Merced</b><br/>2Adobe Research +</td><td>('1754382', 'Yijun Li', 'yijun li')<br/>('2391885', 'Sifei Liu', 'sifei liu')<br/>('1768964', 'Jimei Yang', 'jimei yang')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td>{yli62,sliu32,mhyang}@ucmerced.edu +<br/>jimyang@adobe.com </td></tr><tr><td>f0681fc08f4d7198dcde803d69ca62f09f3db6c5</td><td>Spatiotemporal Features for Effective Facial <br/>Expression Recognition <br/>Hatice C¸ ınar Akakın and B¨ulent Sankur @@ -29000,18 +37011,56 @@ <br/><b>UNIVERSITY OF OULU GRADUATE SCHOOL</b><br/><b>UNIVERSITY OF OULU</b><br/>FACULTY OF INFORMATION TECHNOLOGY AND ELECTRICAL ENGINEERING, <br/>DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING; <br/>INFOTECH OULU -</td><td>('6433503', 'Santeri Palviainen', 'santeri palviainen')<br/>('3797304', 'Sanna Taskila', 'sanna taskila')<br/>('5451992', 'Olli Vuolteenaho', 'olli vuolteenaho')<br/>('6238085', 'Sinikka Eskelinen', 'sinikka eskelinen')<br/>('2165962', 'Jari Juga', 'jari juga')<br/>('5451992', 'Olli Vuolteenaho', 'olli vuolteenaho')<br/>('35709493', 'Jukka Komulainen', 'jukka komulainen')</td><td></td></tr><tr><td>f06b015bb19bd3c39ac5b1e4320566f8d83a0c84</td><td></td><td></td><td></td></tr><tr><td>f0a3f12469fa55ad0d40c21212d18c02be0d1264</td><td>Sparsity Sharing Embedding for Face +</td><td>('6433503', 'Santeri Palviainen', 'santeri palviainen')<br/>('3797304', 'Sanna Taskila', 'sanna taskila')<br/>('5451992', 'Olli Vuolteenaho', 'olli vuolteenaho')<br/>('6238085', 'Sinikka Eskelinen', 'sinikka eskelinen')<br/>('2165962', 'Jari Juga', 'jari juga')<br/>('5451992', 'Olli Vuolteenaho', 'olli vuolteenaho')<br/>('35709493', 'Jukka Komulainen', 'jukka komulainen')</td><td></td></tr><tr><td>f0398ee5291b153b716411c146a17d4af9cb0edc</td><td>LEARNING OPTICAL FLOW VIA DILATED NETWORKS AND OCCLUSION REASONING +<br/><b>University of California, Merced</b><br/>5200 N Lake Rd, Merced, CA, US +</td><td>('1749901', 'Yi Zhu', 'yi zhu')</td><td>{yzhu25, snewsam}@ucmerced.edu +</td></tr><tr><td>f0f0e94d333b4923ae42ee195df17c0df62ea0b1</td><td>Scaling Manifold Ranking Based Image Retrieval +<br/>†NTT Software Innovation Center, 3-9-11 Midori-cho Musashino-shi, Tokyo, Japan +<br/>‡NTT Service Evolution Laboratories, 1-1 Hikarinooka Yokosuka-shi, Kanagawa, Japan +<br/><b>California Institute of Technology, 1200 East California Boulevard Pasadena, California, USA</b><br/><b>Osaka University, 1-5 Yamadaoka, Suita-shi, Osaka, Japan</b></td><td>('32130106', 'Yasuhiro Fujiwara', 'yasuhiro fujiwara')<br/>('32285163', 'Go Irie', 'go irie')<br/>('46593534', 'Shari Kuroyama', 'shari kuroyama')<br/>('48075831', 'Makoto Onizuka', 'makoto onizuka')</td><td>{fujiwara.yasuhiro, irie.go}@lab.ntt.co.jp, kuroyama@caltech.edu, oni@acm.org +</td></tr><tr><td>f06b015bb19bd3c39ac5b1e4320566f8d83a0c84</td><td></td><td></td><td></td></tr><tr><td>f0a3f12469fa55ad0d40c21212d18c02be0d1264</td><td>Sparsity Sharing Embedding for Face <br/>Verification <br/>Department of Electrical Engineering, KAIST, Daejeon, Korea </td><td>('2350325', 'Donghoon Lee', 'donghoon lee')<br/>('2857402', 'Hyunsin Park', 'hyunsin park')<br/>('8270717', 'Junyoung Chung', 'junyoung chung')<br/>('2126465', 'Youngook Song', 'youngook song')</td><td></td></tr><tr><td>f05ad40246656a977cf321c8299158435e3f3b61</td><td>Face Recognition Using Face Patch Networks <br/><b>The Chinese University of Hong Kong</b></td><td>('2312486', 'Chaochao Lu', 'chaochao lu')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')<br/>('1678783', 'Deli Zhao', 'deli zhao')</td><td>{cclu,dlzhao,xtang}@ie.cuhk.edu.hk -</td></tr><tr><td>f781e50caa43be13c5ceb13f4ccc2abc7d1507c5</td><td>MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan +</td></tr><tr><td>f02a6bccdaee14ab55ad94263539f4f33f1b15bb</td><td>Article +<br/>Segment-Tube: Spatio-Temporal Action Localization +<br/>in Untrimmed Videos with Per-Frame Segmentation +<br/><b>Institute of Arti cial Intelligence and Robotics, Xi an Jiaotong University, Xi an, Shannxi 710049, China</b><br/>Received: 23 April 2018; Accepted: 16 May 2018; Published: 22 May 2018 +</td><td>('40367806', 'Le Wang', 'le wang')<br/>('46809347', 'Xuhuan Duan', 'xuhuan duan')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('1786361', 'Zhenxing Niu', 'zhenxing niu')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('1715389', 'Nanning Zheng', 'nanning zheng')</td><td>duanxuhuan0123@stu.xjtu.edu.cn (X.D.); nnzheng@xjtu.edu.cn (N.Z.) +<br/>2 HERE Technologies, Chicago, IL 60606, USA; qilin.zhang@here.com +<br/>3 Alibaba Group, Hangzhou 311121, China; zhenxing.nzx@alibaba-inc.com +<br/>4 Microsoft Research, Redmond, WA 98052, USA; ganghua@microsoft.com +<br/>* Correspondence: lewang@xjtu.edu.cn; Tel.: +86-29-8266-8672 +</td></tr><tr><td>f7dea4454c2de0b96ab5cf95008ce7144292e52a</td><td></td><td></td><td></td></tr><tr><td>f781e50caa43be13c5ceb13f4ccc2abc7d1507c5</td><td>MVA2005 IAPR Conference on Machine VIsion Applications, May 16-18, 2005 Tsukuba Science City, Japan <br/>12-1 <br/>Towards Flexible and Intelligent Vision Systems <br/>– From Thresholding to CHLAC – <br/><b>University of Tokyo</b><br/>AISTy <br/><b>y National Institute of Advanced Industrial Science and Technology</b><br/>Umezono 1-1-1, Tsukuba-shi, Ibaraki-ken, 305-8568 Japan </td><td>('1809629', 'Nobuyuki Otsu', 'nobuyuki otsu')</td><td>Email: otsu.n@aist.go.jp +</td></tr><tr><td>f7b4bc4ef14349a6e66829a0101d5b21129dcf55</td><td>LONG ET AL.: TOWARDS LIGHT-WEIGHT ANNOTATIONS: FIR FOR ZSL +<br/>Towards Light-weight Annotations: Fuzzy +<br/>Interpolative Reasoning for Zero-shot Image +<br/>Classification +<br/>1 Open Lab, School of Computing +<br/><b>Newcastle University, UK</b><br/>2 Department of Computer Science and +<br/>Digital Technologies, Northumbria Uni- +<br/>versity, UK +<br/><b>Inception Institute of Arti cial</b><br/>gence, UAE +<br/>Intelli- +</td><td>('50363618', 'Yang Long', 'yang long')<br/>('48272923', 'Yao Tan', 'yao tan')<br/>('34975328', 'Daniel Organisciak', 'daniel organisciak')<br/>('1706028', 'Longzhi Yang', 'longzhi yang')<br/>('40799321', 'Ling Shao', 'ling shao')</td><td>yang.long@ieee.org +<br/>yao.tan@northumbria.ac.uk +<br/>d.organisciak@gmail.com +<br/>longzhi.yang@northumbria.ac.uk +<br/>ling.shao@ieee.org +</td></tr><tr><td>f7b422df567ce9813926461251517761e3e6cda0</td><td>FACE AGING WITH CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS +<br/>(cid:63) Orange Labs, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France +<br/>† Eurecom, 450 route des Chappes, 06410 Biot, France +</td><td>('3116433', 'Grigory Antipov', 'grigory antipov')<br/>('2341854', 'Moez Baccouche', 'moez baccouche')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td></td></tr><tr><td>f7824758800a7b1a386db5bd35f84c81454d017a</td><td>KEPLER: Keypoint and Pose Estimation of Unconstrained Faces by +<br/>Learning Efficient H-CNN Regressors +<br/>Department of Electrical and Computer Engineering, CFAR and UMIACS +<br/><b>University of Maryland-College Park, USA</b></td><td>('50333013', 'Amit Kumar', 'amit kumar')<br/>('2943431', 'Azadeh Alavi', 'azadeh alavi')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{akumar14,azadeh,rama}@umiacs.umd.edu </td></tr><tr><td>f74917fc0e55f4f5682909dcf6929abd19d33e2e</td><td>Workshop track - ICLR 2018 <br/>GAN QUALITY INDEX (GQI) BY GAN-INDUCED <br/>CLASSIFIER @@ -29027,11 +37076,140 @@ <br/><b>Kong Polytechnic University, Kowloon, Hong Kong</b><br/><b>b Computer Science, School of Electrical and Data Engineering, University of Technology, Sydney</b><br/>Australia </td><td>('13671251', 'Cigdem Turan', 'cigdem turan')<br/>('1703078', 'Kin-Man Lam', 'kin-man lam')<br/>('1706670', 'Xiangjian He', 'xiangjian he')</td><td>E-mail addresses: cigdem.turan@connect.polyu.hk (C. Turan), enkmlam@polyu.edu.hk (K.-M. Lam), <br/>xiangjian.he@uts.edu.au (X. He) -</td></tr><tr><td>f7452a12f9bd927398e036ea6ede02da79097e6e</td><td></td><td></td><td></td></tr><tr><td>f7093b138fd31956e30d411a7043741dcb8ca4aa</td><td>Hierarchical Clustering in Face Similarity Score +</td></tr><tr><td>f78fe101b21be36e98cd3da010051bb9b9829a1e</td><td>Hindawi +<br/>Computational Intelligence and Neuroscience +<br/>Volume 2018, Article ID 7208794, 10 pages +<br/>https://doi.org/10.1155/2018/7208794 +<br/>Research Article +<br/>Unsupervised Domain Adaptation for Facial Expression +<br/>Recognition Using Generative Adversarial Networks +<br/>1,2 +<br/><b>State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, 300072, China</b><br/><b>Key Laboratory of MOEMS of the Ministry of Education, Tianjin University, 300072, China</b><br/>Received 14 April 2018; Accepted 19 June 2018; Published 9 July 2018 +<br/>Academic Editor: Ant´onio D. P. Correia +<br/>which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. +<br/>In the facial expression recognition task, a good-performing convolutional neural network (CNN) model trained on one dataset +<br/>(source dataset) usually performs poorly on another dataset (target dataset). This is because the feature distribution of the same +<br/>emotion varies in different datasets. To improve the cross-dataset accuracy of the CNN model, we introduce an unsupervised +<br/>domain adaptation method, which is especially suitable for unlabelled small target dataset. In order to solve the problem of lack of +<br/>samples from the target dataset, we train a generative adversarial network (GAN) on the target dataset and use the GAN generated +<br/>samples to fine-tune the model pretrained on the source dataset. In the process of fine-tuning, we give the unlabelled GAN generated +<br/>samples distributed pseudolabels dynamically according to the current prediction probabilities. Our method can be easily applied +<br/>to any existing convolutional neural networks (CNN). We demonstrate the effectiveness of our method on four facial expression +<br/>recognition datasets with two CNN structures and obtain inspiring results. +<br/>1. Introduction +<br/>Facial expressions recognition (FER) has a wide spectrum of +<br/>application potentials in human-computer interaction, cog- +<br/>nitive psychology, computational neuroscience, and medical +<br/>healthcare. In recent years, convolutional neural networks +<br/>(CNN) have achieved many exciting results in artificial +<br/>intelligent and pattern recognition and have been successfully +<br/>used in facial expression recognition [1]. Jaiswal et al. [2] +<br/>present a novel approach to facial action unit detection +<br/>using a combination of Convolutional and Bidirectional +<br/>Long Short-Term Memory Neural Networks (CNN-BLSTM), +<br/>which jointly learns shape, appearance, and dynamics in a +<br/>deep learning manner. You et al. [3] introduce a new data +<br/>set, which contains more than 3 million weakly labelled +<br/>images of different emotions. Esser et al. [4] develop a model +<br/>for efficient neuromorphic computing using the Deep CNN +<br/>technique. H-W.Ng et al. [5] develop a cascading fine-tuning +<br/>approach for emotion recognition. Neagoe et al. [6] propose +<br/>a model for subject independent emotion recognition from +<br/>facial expressions using combined CNN and DBN. However, +<br/>these CNN models are often trained and tested on the +<br/>same dataset, whereas the cross-dataset performance is less +<br/>concerned. Although the basic emotions defined by Ekman +<br/>and Friesen [7], anger, disgust, fear, happy, sadness, and +<br/>surprise, are believed to be universal, the way of expressing +<br/>these emotions can be quite diverse across different cultures, +<br/>ages, and genders [8]. As a result, a well-trained CNN model, +<br/>having high recognition accuracy on the training dataset, +<br/>usually performs poorly on other datasets. In order to make +<br/>the facial expression recognition system more practical, it +<br/>is necessary to improve the generalization ability of the +<br/>recognition model. +<br/>In this paper, we aim at improving the cross-dataset +<br/>accuracy of a CNN model on facial expression recognition. +<br/>One way to solve this problem is to rebuild models from +<br/>scratch using large-scale newly collected samples. Large +<br/>amounts of training samples, such as the dataset ImageNet [9] +<br/>containing over 15 million images, can reduce the overfitting +<br/>problem and help to train a reliable model. However, for +<br/>facial expression recognition, +<br/>it is expensive and some- +<br/>times even impossible to get enough labelled training data. +<br/>Therefore, we proposed an unsupervised domain adaptation +<br/>method, which is especially suitable for unlabelled small +</td><td>('47119020', 'Xiaoqing Wang', 'xiaoqing wang')<br/>('36142058', 'Xiangjun Wang', 'xiangjun wang')<br/>('3332231', 'Yubo Ni', 'yubo ni')<br/>('47119020', 'Xiaoqing Wang', 'xiaoqing wang')</td><td>Correspondence should be addressed to Xiangjun Wang; tjuxjw@126.com +</td></tr><tr><td>f79c97e7c3f9a98cf6f4a5d2431f149ffacae48f</td><td>Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published +<br/>version when available. +<br/>Title +<br/>On color texture normalization for active appearance models +<br/>Author(s) +<br/>Ionita, Mircea C.; Corcoran, Peter M.; Buzuloiu, Vasile +<br/>Publication +<br/>Date +<br/>2009-05-12 +<br/>Publication +<br/>Information +<br/>Ionita, M. C., Corcoran, P., & Buzuloiu, V. (2009). On Color +<br/>Texture Normalization for Active Appearance Models. Image +<br/>Processing, IEEE Transactions on, 18(6), 1372-1378. +<br/>Publisher +<br/>IEEE +<br/>Link to +<br/>publisher's +<br/>version +<br/>http://dx.doi.org/10.1109/TIP.2009.2017163 +<br/>Item record +<br/>http://hdl.handle.net/10379/1350 +<br/>Some rights reserved. For more information, please see the item record link above. +<br/>Downloaded 2017-06-17T22:38:27Z +</td><td></td><td></td></tr><tr><td>f7452a12f9bd927398e036ea6ede02da79097e6e</td><td></td><td></td><td></td></tr><tr><td>f7a271acccf9ec66c9b114d36eec284fbb89c7ef</td><td>Open Access +<br/>Research +<br/>Does attractiveness influence condom +<br/>use intentions in heterosexual men? +<br/>An experimental study +<br/>To cite: Eleftheriou A, +<br/>Bullock S, Graham CA, et al. +<br/>Does attractiveness influence +<br/>condom use intentions in +<br/>heterosexual men? +<br/>An experimental study. BMJ +<br/>Open 2016;6:e010883. +<br/>doi:10.1136/bmjopen-2015- +<br/>010883 +<br/>▸ Prepublication history for +<br/>this paper is available online. +<br/>To view these files please +<br/>visit the journal online +<br/>(http://dx.doi.org/10.1136/ +<br/>bmjopen-2015-010883). +<br/>Received 17 December 2015 +<br/>Revised 1 March 2016 +<br/>Accepted 7 April 2016 +<br/>1Department of Electronics +<br/>and Computer Science, +<br/><b>University of Southampton</b><br/>Southampton, UK +<br/><b>Institute for Complex</b><br/>Systems Simulation, +<br/><b>University of Southampton</b><br/>Southampton, UK +<br/>3Department of Computer +<br/><b>Science, University of Bristol</b><br/>Bristol, UK +<br/>4Centre for Sexual Health +<br/>Research, Department of +<br/><b>Psychology, University of</b><br/>Southampton, Southampton, +<br/>UK +<br/>Correspondence to +</td><td>('6093065', 'Anastasia Eleftheriou', 'anastasia eleftheriou')<br/>('1733871', 'Seth Bullock', 'seth bullock')<br/>('4712904', 'Cynthia A Graham', 'cynthia a graham')<br/>('48479171', 'Nicole Stone', 'nicole stone')<br/>('50227141', 'Roger Ingham', 'roger ingham')<br/>('6093065', 'Anastasia Eleftheriou', 'anastasia eleftheriou')</td><td>ae2n12@soton.ac.uk +</td></tr><tr><td>f7093b138fd31956e30d411a7043741dcb8ca4aa</td><td>Hierarchical Clustering in Face Similarity Score <br/>Space <br/>Jason Grant and Patrick Flynn <br/>Department of Computer Science and Engineering <br/><b>University of Notre Dame</b><br/>Notre Dame, IN 46556 +</td><td></td><td></td></tr><tr><td>f7dcadc5288653ec6764600c7c1e2b49c305dfaa</td><td>Copyright +<br/>by +<br/>Adriana Ivanova Kovashka +<br/>2014 </td><td></td><td></td></tr><tr><td>f7de943aa75406fe5568fdbb08133ce0f9a765d4</td><td>Project 1.5: Human Identification at a Distance - Hornak, Adjeroh, Cukic, Gautum, & Ross <br/>Project 1.5 <br/>Biometric Identification and Surveillance1 @@ -29095,7 +37273,11 @@ <br/><b>School of EEE, Nanyang Technological University, Singapore</b><br/>2Advanced Digital Sciences Center, Singapore </td><td>('34651153', 'Junlin Hu', 'junlin hu')<br/>('1697700', 'Jiwen Lu', 'jiwen lu')<br/>('34316743', 'Junsong Yuan', 'junsong yuan')<br/>('1689805', 'Yap-Peng Tan', 'yap-peng tan')</td><td></td></tr><tr><td>f78863f4e7c4c57744715abe524ae4256be884a9</td><td></td><td></td><td></td></tr><tr><td>f77c9bf5beec7c975584e8087aae8d679664a1eb</td><td>Local Deep Neural Networks for Age and Gender Classification <br/>March 27, 2017 -</td><td>('9949538', 'Zukang Liao', 'zukang liao')<br/>('2403354', 'Stavros Petridis', 'stavros petridis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>e8686663aec64f4414eba6a0f821ab9eb9f93e38</td><td>IMPROVING SHAPE-BASED FACE RECOGNITION BY MEANS OF A SUPERVISED +</td><td>('9949538', 'Zukang Liao', 'zukang liao')<br/>('2403354', 'Stavros Petridis', 'stavros petridis')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>f7ba77d23a0eea5a3034a1833b2d2552cb42fb7a</td><td>This is a pre-print of the original paper accepted at the International Joint Conference on Biometrics (IJCB) 2017. +<br/>LOTS about Attacking Deep Features +<br/>Vision and Security Technology (VAST) Lab +<br/><b>University of Colorado, Colorado Springs, USA</b></td><td>('2974221', 'Andras Rozsa', 'andras rozsa')<br/>('1760117', 'Terrance E. Boult', 'terrance e. boult')</td><td>{arozsa,mgunther,tboult}@vast.uccs.edu +</td></tr><tr><td>e8686663aec64f4414eba6a0f821ab9eb9f93e38</td><td>IMPROVING SHAPE-BASED FACE RECOGNITION BY MEANS OF A SUPERVISED <br/>DISCRIMINANT HAUSDORFF DISTANCE <br/>J.L. Alba <br/>, A. Pujol @@ -29118,13 +37300,49 @@ <br/>Supervisor: <br/>Instructor: <br/>Professor Erkki Oja -</td><td>('1700492', 'Jing Wu', 'jing wu')<br/>('1758971', 'Markus Koskela', 'markus koskela')</td><td></td></tr><tr><td>e8410c4cd1689829c15bd1f34995eb3bd4321069</td><td></td><td></td><td></td></tr><tr><td>e8f0f9b74db6794830baa2cab48d99d8724e8cb6</td><td>Active Image Labeling and Its Application to +</td><td>('1700492', 'Jing Wu', 'jing wu')<br/>('1758971', 'Markus Koskela', 'markus koskela')</td><td></td></tr><tr><td>e8410c4cd1689829c15bd1f34995eb3bd4321069</td><td></td><td></td><td></td></tr><tr><td>e8fdacbd708feb60fd6e7843b048bf3c4387c6db</td><td>Deep Learning +<br/>Hinnerup Net A/S +<br/>www.hinnerup.net +<br/>July 4, 2014 +<br/>Introduction +<br/>Deep learning is a topic in the field of artificial intelligence (AI) and is a relatively +<br/>new research area although based on the popular artificial neural networks (supposedly +<br/>mirroring brain function). With the development of the perceptron in the 1950s and +<br/>1960s by Frank RosenBlatt, research began on artificial neural networks. To further +<br/>mimic the architectural depth of the brain, researchers wanted to train a deep multi- +<br/>layer neural network – this, however, did not happen until Geoffrey Hinton in 2006 +<br/>introduced Deep Belief Networks [1]. +<br/>Recently, the topic of deep learning has gained public interest. Large web companies such +<br/>as Google and Facebook have a focused research on AI and an ever increasing amount +<br/>of compute power, which has led to researchers finally being able to produce results +<br/>that are of interest to the general public. In July 2012 Google trained a deep learning +<br/>network on YouTube videos with the remarkable result that the network learned to +<br/>recognize humans as well as cats [6], and in January this year Google successfully used +<br/>deep learning on Street View images to automatically recognize house numbers with +<br/>an accuracy comparable to that of a human operator [5]. In March this year Facebook +<br/>announced their DeepFace algorithm that is able to match faces in photos with Facebook +<br/>users almost as accurately as a human can do [9]. +<br/>Deep learning and other AI are here to stay and will become more and more present in +<br/>our daily lives, so we had better make ourselves acquainted with the technology. Let’s +<br/>dive into the deep water and try not to drown! +<br/>Data Representations +<br/>Before presenting data to an AI algorithm, we would normally prepare the data to make +<br/>it feasible to work with. For instance, if the data consists of images, we would take each +</td><td></td><td></td></tr><tr><td>e8f0f9b74db6794830baa2cab48d99d8724e8cb6</td><td>Active Image Labeling and Its Application to <br/>Facial Action Labeling <br/><b>Electrical, Computer, Rensselaer Polytechnic Institute</b><br/><b>Visualization and Computer Vision Lab, GE Global Research Center</b></td><td>('40396543', 'Lei Zhang', 'lei zhang')<br/>('1686235', 'Yan Tong', 'yan tong')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>zhangl2@rpi.edu,tongyan@research.ge.com,qji@ecse.rpi.edu </td></tr><tr><td>e8b2a98f87b7b2593b4a046464c1ec63bfd13b51</td><td>CMS-RCNN: Contextual Multi-Scale <br/>Region-based CNN for Unconstrained Face <br/>Detection -</td><td>('3117715', 'Chenchen Zhu', 'chenchen zhu')<br/>('3049981', 'Yutong Zheng', 'yutong zheng')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td></td></tr><tr><td>e8c9dcbf56714db53063b9c367e3e44300141ff6</td><td>Automated FACS face analysis benefits from the addition of velocity +</td><td>('3117715', 'Chenchen Zhu', 'chenchen zhu')<br/>('3049981', 'Yutong Zheng', 'yutong zheng')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td></td></tr><tr><td>e87d6c284cdd6828dfe7c092087fbd9ff5091ee4</td><td>Unsupervised Creation of Parameterized Avatars +<br/>1Facebook AI Research +<br/><b>School of Computer Science, Tel Aviv University</b></td><td>('1776343', 'Lior Wolf', 'lior wolf')<br/>('2188620', 'Yaniv Taigman', 'yaniv taigman')<br/>('33964593', 'Adam Polyak', 'adam polyak')</td><td></td></tr><tr><td>e8523c4ac9d7aa21f3eb4062e09f2a3bc1eedcf7</td><td>Towards End-to-End Face Recognition through Alignment Learning +<br/><b>Tsinghua University</b><br/>Beijing, China, 100084 +</td><td>('8802368', 'Yuanyi Zhong', 'yuanyi zhong')<br/>('1752427', 'Jiansheng Chen', 'jiansheng chen')<br/>('39071060', 'Bo Huang', 'bo huang')</td><td>zhongyy13@mails.tsinghua.edu.cn, jschenthu@mail.tsinghua.edu.cn, huangb14@mails.tsinghua.edu.cn +</td></tr><tr><td>e85a255a970ee4c1eecc3e3d110e157f3e0a4629</td><td>Fusing Hierarchical Convolutional Features for Human Body Segmentation and +<br/>Clothing Fashion Classification +<br/><b>School of Computer Science, Wuhan University, P.R. China</b></td><td>('47294008', 'Zheng Zhang', 'zheng zhang')<br/>('3127916', 'Chengfang Song', 'chengfang song')<br/>('4793870', 'Qin Zou', 'qin zou')</td><td>E-mails: {zhangzheng, songchf, qzou}@whu.edu.cn +</td></tr><tr><td>e8c9dcbf56714db53063b9c367e3e44300141ff6</td><td>Automated FACS face analysis benefits from the addition of velocity <br/>Get The FACS Fast: <br/>Timothy R. Brick <br/><b>University of Virginia</b><br/>Charlottesville, VA 22904 @@ -29135,6 +37353,43 @@ </td><td></td><td>tbrick@virginia.edu <br/>mhunter@virginia.edu <br/>jeffcohn@cs.cmu.edu +</td></tr><tr><td>e8d1b134d48eb0928bc999923a4e092537e106f6</td><td>WEIGHTED MULTI-REGION CONVOLUTIONAL NEURAL NETWORK FOR ACTION +<br/>RECOGNITION WITH LOW-LATENCY ONLINE PREDICTION +<br/><b>cid:63)University of Science and Technology of China, Hefei, Anhui, China</b><br/>†HERE Technologies, Chicago, Illinois, USA +</td><td>('49417387', 'Yunfeng Wang', 'yunfeng wang')<br/>('38272296', 'Wengang Zhou', 'wengang zhou')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('49897466', 'Xiaotian Zhu', 'xiaotian zhu')<br/>('7179232', 'Houqiang Li', 'houqiang li')</td><td></td></tr><tr><td>e8c6c3fc9b52dffb15fe115702c6f159d955d308</td><td>13 +<br/>Linear Subspace Learning for +<br/>Facial Expression Analysis +<br/>Philips Research +<br/>The Netherlands +<br/>1. Introduction +<br/>Facial expression, resulting from movements of the facial muscles, is one of the most +<br/>powerful, natural, and immediate means for human beings to communicate their emotions +<br/>and intentions. Some examples of facial expressions are shown in Fig. 1. Darwin (1872) was +<br/>the first to describe in detail the specific facial expressions associated with emotions in +<br/>animals and humans; he argued that all mammals show emotions reliably in their faces. +<br/>Psychological studies (Mehrabian, 1968; Ambady & Rosenthal, 1992) indicate that facial +<br/>expressions, with other non-verbal cues, play a major and fundamental role in face-to-face +<br/>communication. +<br/>Fig. 1. Facial expressions of George W. Bush. +<br/>Machine analysis of facial expressions, enabling computers to analyze and interpret facial +<br/>expressions as humans do, has many important applications including intelligent human- +<br/>computer interaction, computer animation, surveillance and security, medical diagnosis, +<br/>law enforcement, and awareness system (Shan, 2007). Driven by its potential applications +<br/>and theoretical interests of cognitive and psychological scientists, automatic facial +<br/>expression analysis has attracted much attention in last two decades (Pantic & Rothkrantz, +<br/>2000a; Fasel & Luettin, 2003; Tian et al, 2005; Pantic & Bartlett, 2007). It has been studied in +<br/>multiple disciplines such as psychology, cognitive science, computer vision, pattern +<br/>Source: Machine Learning, Book edited by: Abdelhamid Mellouk and Abdennacer Chebira, +<br/> ISBN 978-3-902613-56-1, pp. 450, February 2009, I-Tech, Vienna, Austria +<br/>www.intechopen.com +</td><td>('10795229', 'Caifeng Shan', 'caifeng shan')</td><td></td></tr><tr><td>e8b3a257a0a44d2859862cdec91c8841dc69144d</td><td>Liquid Pouring Monitoring via +<br/>Rich Sensory Inputs +<br/><b>National Tsing Hua University, Taiwan</b><br/><b>Stanford University, USA</b></td><td>('27555915', 'Tz-Ying Wu', 'tz-ying wu')<br/>('9618379', 'Juan-Ting Lin', 'juan-ting lin')<br/>('27538483', 'Chan-Wei Hu', 'chan-wei hu')<br/>('9200530', 'Juan Carlos Niebles', 'juan carlos niebles')<br/>('46611107', 'Min Sun', 'min sun')</td><td>{gina9726, brade31919, johnsonwang0810, huchanwei1204}@gmail.com, +<br/>sunmin@ee.nthu.edu.tw +<br/>jniebles@cs.stanford.edu +</td></tr><tr><td>fa90b825346a51562d42f6b59a343b98ea2e501a</td><td>Modeling Naive Psychology of Characters in Simple Commonsense Stories +<br/><b>Paul G. Allen School of Computer Science and Engineering, University of Washington</b><br/><b>Allen Institute for Arti cial Intelligence</b><br/><b>Information Sciences Institute and Computer Science, University of Southern California</b></td><td>('2516777', 'Hannah Rashkin', 'hannah rashkin')<br/>('2691021', 'Antoine Bosselut', 'antoine bosselut')<br/>('2729164', 'Maarten Sap', 'maarten sap')<br/>('1710034', 'Kevin Knight', 'kevin knight')<br/>('1699545', 'Yejin Choi', 'yejin choi')</td><td>{hrashkin,msap,antoineb,yejin}@cs.washington.edu +<br/>knight@isi.edu </td></tr><tr><td>fab83bf8d7cab8fe069796b33d2a6bd70c8cefc6</td><td>Draft: Evaluation Guidelines for Gender <br/>Classification and Age Estimation <br/>July 1, 2011 @@ -29229,6 +37484,9 @@ <br/>Frontiers in Robotics and AI | www.frontiersin.org <br/>November 2017 | Volume 4 | Article 61 </td><td>('7149684', 'Martin Cooney', 'martin cooney')<br/>('5058247', 'Josef Bigun', 'josef bigun')<br/>('7149684', 'Martin Cooney', 'martin cooney')</td><td>martin.daniel.cooney@gmail.com +</td></tr><tr><td>fa4f59397f964a23e3c10335c67d9a24ef532d5c</td><td>DAP3D-Net: Where, What and How Actions Occur in Videos? +<br/>Department of Computer Science and Digital Technologies +<br/><b>Northumbria University, Newcastle upon Tyne, NE1 8ST, UK</b></td><td>('40241836', 'Li Liu', 'li liu')<br/>('47942896', 'Yi Zhou', 'yi zhou')<br/>('40799321', 'Ling Shao', 'ling shao')</td><td>li2.liu@northumbria.ac.uk, m.y.yu@ieee.org, ling.shao@ieee.org </td></tr><tr><td>fa08a4da5f2fa39632d90ce3a2e1688d147ece61</td><td>Supplementary material for <br/>“Unsupervised Creation of Parameterized Avatars” <br/>1 Summary of Notations @@ -29282,6 +37540,33 @@ </td><td>('2742026', 'Kostiantyn Antoniuk', 'kostiantyn antoniuk')</td><td>antonkos@cmp.felk.cvut.cz <br/>xfrancv@cmp.felk.cvut.cz <br/>hlavac@fel.cvut.cz +</td></tr><tr><td>fac8cff9052fc5fab7d5ef114d1342daba5e4b82</td><td>(CV last updated Oct. 5th, 2009.) +<br/>www.stat.cmu.edu/~abrock +<br/>1-412-478-3609 +<br/>Citizenship: U.S., Australia (dual) +<br/>Education +<br/>1994-1998 +<br/>: Ph.D., Department of Statistics and Department of of Electrical Engineering at +<br/><b>Melbourne University, Advisors: K. Borovkov, R. Evans</b><br/>1993 +<br/>: Honours Science Degree (in the Department of Statistics) completed at Melbourne +<br/><b>University (H</b><br/>1988-92 +<br/>: Bachelor of Science and Bachelor of Engineering with Honours completed at Mel- +<br/><b>bourne University</b><br/>Employment +<br/>2007+ +<br/><b>Carnegie Mellon University</b><br/>2007-2009 +<br/>: Senior Analyst, Horton Point LLC (Hedge Fund Management Company) +<br/>2006-2007 +<br/>: Associate Professor, Department of Statistics, Carnegie Mellon Uniuversity +<br/>2005-2007 +<br/>: Affiliated faculty member, Machine Learning Department (formerly known as the +<br/><b>Center for Automated Learning and Discovery), Carnegie Mellon University</b><br/>2003-2007 +<br/><b>Faculty member, Parallel Data Lab (PDL), Carnegie Mellon University</b><br/>2002-2005 +<br/><b>Carnegie Mellon University</b><br/>1999-2002 +<br/><b>Carnegie Mellon University</b><br/>1998-1999 +<br/>: Research Fellow, Department of Electrical and Electronic Engineering, The Univer- +<br/>sity of Melbourne +<br/>1993-1995 +<br/><b>Sessional Tutor, The University of Melbourne</b></td><td>('1680307', 'Anthony Brockwell', 'anthony brockwell')</td><td>anthony.brockwell@gmail.com </td></tr><tr><td>faa29975169ba3bbb954e518bc9814a5819876f6</td><td>Evolution-Preserving Dense Trajectory Descriptors <br/><b>Stony Brook University, Stony Brook, NY 11794, USA</b></td><td>('2295608', 'Yang Wang', 'yang wang')<br/>('3482497', 'Vinh Tran', 'vinh tran')<br/>('2356016', 'Minh Hoai', 'minh hoai')</td><td>{wang33, tquangvinh, minhhoai}@cs.stonybrook.edu </td></tr><tr><td>fafe69a00565895c7d57ad09ef44ce9ddd5a6caa</td><td>Applied Mathematics, 2012, 3, 2071-2079 @@ -29290,13 +37575,30 @@ <br/>under Illumination Variations <br/><b>Mihaylo College of Business and Economics</b><br/><b>California State University, Fullerton, USA</b><br/>Received August 18, 2012; revised September 18, 2012; accepted September 25, 2012 </td><td>('2046854', 'Sinjini Mitra', 'sinjini mitra')</td><td>Email: smitra@fullerton.edu -</td></tr><tr><td>faca1c97ac2df9d972c0766a296efcf101aaf969</td><td>Sympathy for the Details: Dense Trajectories and Hybrid +</td></tr><tr><td>faf5583063682e70dedc4466ac0f74eeb63169e7</td><td></td><td></td><td>HolisticPersonProcessing:FacesWithBodiesTelltheWholeStoryHillelAviezerPrincetonUniversityandNewYorkUniversityYaacovTropeNewYorkUniversityAlexanderTodorovPrincetonUniversityFacesandbodiesaretypicallyencounteredsimultaneously,yetlittleresearchhasexploredthevisualprocessingofthefullperson.Specifically,itisunknownwhetherthefaceandbodyareperceivedasdistinctcomponentsorasanintegrated,gestalt-likeunit.Toexaminethisquestion,weinvestigatedwhetheremotionalface–bodycompositesareprocessedinaholistic-likemannerbyusingavariantofthecompositefacetask,ameasureofholisticprocessing.Participantsjudgedfacialexpressionscombinedwithemotionallycongruentorincongruentbodiesthathavebeenshowntoinfluencetherecognitionofemotionfromtheface.Critically,thefaceswereeitheralignedwiththebodyinanaturalpositionormisalignedinamannerthatbreakstheecologicalpersonform.Convergingdatafrom3experimentsconfirmthatbreakingthepersonformreducesthefacilitatinginfluenceofcongruentbodycontextaswellastheimpedinginfluenceofincongruentbodycontextontherecognitionofemotionfromtheface.Theseresultsshowthatfacesandbodiesareprocessedasasingleunitandsupportthenotionofacompositepersoneffectanalogoustotheclassiceffectdescribedforfaces.Keywords:emotionperception,contexteffects,facialandbodyexpressions,holisticperception,com-positeeffectAglanceisusuallysufficientforextractingagreatdealofsocialinformationfromotherpeople(Adolphs,2002).Perceptualcuestocharacteristicssuchasgender,sexualorientation,emotionalex-pression,attractiveness,andpersonalitytraitscanbefoundinboththefaceandthebody(e.g.,facecues,Adolphs,2003;Calder&Young,2005;Ekman,1993;Elfenbein&Ambady,2002;Haxby,Hoffman,&Gobbini,2000;Rule,Ambady,&Hallett,2009;Thornhill&Gangestad,1999;Todorov&Duchaine,2008;Todo-rov,Pakrashi,&Oosterhof,2009;Willis&Todorov,2006;Ze-browitz,Hall,Murphy,&Rhodes,2002;Zebrowitz&Montepare,2008;bodycues,deGelderetal.,2006;Johnson,Gill,Reichman,&Tassinary,2007;Peelen&Downing,2005;Stevenage,Nixon,&Vince,1999;Wallbott,1998).Todate,mostresearchershaveinvestigatedthefaceandthebodyasdiscreteperceptualunits,focusingontheprocessingofeachsourceinisolation.Althoughthisapproachhasprovedex-tremelyfruitfulforcharacterizingtheuniqueperceptualcontribu-tionsofthefaceandbody,surprisinglylittleisknownabouttheprocessingofbothsourcescombined.Theaimofthecurrentstudywastoshedlightontheperceptualprocessingofthefullpersonbyexaminingwhetherthefaceandbodyinconjunctionareprocessedasaholistic“personunit.”Onthebasisofpreviousaccounts,onemaypredictthatfacesandbodiesareprocessedastwovisualcomponentsofsocialinformation(Wallbott,1998).Theseviewsarguethatfacesandbodiesmaydifferinvalue,intensity,andclarity,andconsequentlytheinformationfromeachmustbeweightedandcombinedbythecognitivesysteminordertoreachaconclusionaboutthetarget(Ekman,Friesen,&Ellsworth,1982;Ellison&Massaro,1997;Trope,1986;Wallbott,1998).Accordingtothisapproach,thefaceandbodymayinfluenceeachother.However,theinfluenceisnotsynergistic,andtheperceptionofthefaceandbodyisequaltotheweightedsumoftheirparts(Wallbott,1998).Bycontrast,thehypothesisofferedhereisthatthefaceandbodyaresubcomponentsofalargerperceptualpersonunit.Fromanecologicalperspectivethisseemslikelybecauseundernaturalconditions,thevisualsystemrarelyencountersisolatedfacesandbodies(McArthur&Baron,1983;Russell,1997).Accordingtothisview,thefaceandbodyformaunitaryperceptthatmayencompassdifferentpropertiesthanthetwosourcesofinformationseparately.Inotherwords,theinformationreadoutfromthefullpersonmaybemorethanthesumofthefaceandbodyalone.HolisticProcessingandtheCompositeEffectPastresearchonsocialperceptionexaminingunitizedgestaltprocessinghasfocusedprimarilyontheface.Indeed,ahallmarkoffaceperceptionisholisticprocessingbywhichindividualfacialcomponentsbecomeintegratedintoawhole-faceunit(Farah,Wilson,Drain,&Tanaka,1995;Tanaka&Farah,1993).Althoughisolatedfacialcomponentsdobearspecificinformation(Smith,Cottrell,Gosselin,&Schyns,2005;Whalenetal.,2004),theirarrangementinthenaturalfaceconfigurationresultsinaninte-ThisarticlewaspublishedOnlineFirstFebruary20,2012.HillelAviezer,DepartmentofPsychology,PrincetonUniversity,andDepartmentofPsychology,NewYorkUniversity;YaacovTrope,Depart-mentofPsychology,NewYorkUniversity;AlexanderTodorov,Depart-mentofPsychology,PrincetonUniversity.CorrespondenceconcerningthisarticleshouldbeaddressedtoHillelAviezer,DepartmentofPsychology,PrincetonUniversity,Princeton,NJ08540-1010.E-mail:haviezer@princeton.eduJournalofPersonalityandSocialPsychology©2012AmericanPsychologicalAssociation2012,Vol.103,No.1,20–370022-3514/12/$12.00DOI:10.1037/a002741120 </td></tr><tr><td>faca1c97ac2df9d972c0766a296efcf101aaf969</td><td>Sympathy for the Details: Dense Trajectories and Hybrid <br/>Classification Architectures for Action Recognition <br/><b>Computer Vision Group, Xerox Research Center Europe, Meylan, France</b><br/>2Centre de Visi´o per Computador, Universitat Aut`onoma de Barcelona, Bellaterra, Spain <br/>3German Aerospace Center, Wessling, Germany </td><td>('1799820', 'Adrien Gaidon', 'adrien gaidon')<br/>('2286630', 'Eleonora Vig', 'eleonora vig')</td><td>{cesar.desouza, adrien.gaidon}@xrce.xerox.com, <br/>eleonora.vig@dlr.de, antonio@cvc.uab.es -</td></tr><tr><td>fae83b145e5eeda8327de9f19df286edfaf5e60c</td><td>Readings in Technology and Education: Proceedings of ICICTE 2010 +</td></tr><tr><td>fab60b3db164327be8588bce6ce5e45d5b882db6</td><td>Maximum A Posteriori Estimation of Distances +<br/>Between Deep Features in Still-to-Video Face +<br/>Recognition +<br/><b>National Research University Higher School of Economics</b><br/>Laboratory of Algorithms and Technologies for Network Analysis, +<br/>36 Rodionova St., Nizhny Novgorod, Russia +<br/><b>National Research University Higher School of Economics</b><br/>20 Myasnitskaya St., Moscow, Russia +<br/>September 2, 2018 +</td><td>('35153729', 'Andrey V. Savchenko', 'andrey v. savchenko')<br/>('2080292', 'Natalya S. Belova', 'natalya s. belova')</td><td>avsavchenko@hse.ru +<br/>nbelova@hse.ru +</td></tr><tr><td>fad895771260048f58d12158a4d4d6d0623f4158</td><td>Audio-Visual Emotion +<br/>Recognition For Natural +<br/>Human-Robot Interaction +<br/>Dissertation zur Erlangung des akademischen Grades +<br/>Doktor der Ingenieurwissenschaften (Dr.-Ing.) +<br/>vorgelegt von +<br/>an der Technischen Fakultät der Universität Bielefeld +<br/>15. März 2010 +</td><td>('32382494', 'Ahmad Rabie', 'ahmad rabie')</td><td></td></tr><tr><td>fae83b145e5eeda8327de9f19df286edfaf5e60c</td><td>Readings in Technology and Education: Proceedings of ICICTE 2010 <br/>367 <br/>TOWARDS AN INTERACTIVE E-LEARNING SYSTEM BASED ON <br/>EMOTIONS AND AFFECTIVE COGNITION @@ -29306,7 +37608,11 @@ <br/>Konstantinos Ch. Drossos <br/>Department of Audiovisual Arts <br/><b>Ionian University</b><br/>Greece -</td><td>('25189167', 'Panagiotis Vlamos', 'panagiotis vlamos')<br/>('2284118', 'Andreas Floros', 'andreas floros')<br/>('1761403', 'Michail N. Giannakos', 'michail n. giannakos')</td><td></td></tr><tr><td>ff8315c1a0587563510195356c9153729b533c5b</td><td>432 +</td><td>('25189167', 'Panagiotis Vlamos', 'panagiotis vlamos')<br/>('2284118', 'Andreas Floros', 'andreas floros')<br/>('1761403', 'Michail N. Giannakos', 'michail n. giannakos')</td><td></td></tr><tr><td>ffea8775fc9c32f573d1251e177cd283b4fe09c9</td><td>Accepted to be Published in Proceedings of the IEEE International Conference on Multimedia and Expo (ICME) 2018, San Diego, USA +<br/>TRANSFORMATION ON COMPUTER–GENERATED FACIAL IMAGE TO AVOID DETECTION +<br/>BY SPOOFING DETECTOR +<br/><b>Graduate University for Advanced Studies, Kanagawa, Japan</b><br/><b>National Institute of Informatics, Tokyo, Japan</b><br/><b>The University of Edinburgh, Edinburgh, UK</b></td><td>('47321045', 'Huy H. Nguyen', 'huy h. nguyen')<br/>('9328269', 'Ngoc-Dung T. Tieu', 'ngoc-dung t. tieu')<br/>('2912817', 'Hoang-Quoc Nguyen-Son', 'hoang-quoc nguyen-son')<br/>('1716857', 'Junichi Yamagishi', 'junichi yamagishi')<br/>('1678602', 'Isao Echizen', 'isao echizen')</td><td>{nhhuy, dungtieu, nshquoc, jyamagishi, iechizen}@nii.ac.jp +</td></tr><tr><td>ff8315c1a0587563510195356c9153729b533c5b</td><td>432 <br/>Zapping Index:Using Smile to Measure <br/>Advertisement Zapping Likelihood </td><td>('1803478', 'Songfan Yang', 'songfan yang')<br/>('1784929', 'Mehran Kafai', 'mehran kafai')<br/>('39776603', 'Le An', 'le an')<br/>('1707159', 'Bir Bhanu', 'bir bhanu')</td><td></td></tr><tr><td>ff44d8938c52cfdca48c80f8e1618bbcbf91cb2a</td><td>Towards Video Captioning with Naming: a @@ -29314,7 +37620,9 @@ <br/>Dipartimento di Ingegneria “Enzo Ferrari” <br/>Universit`a degli Studi di Modena e Reggio Emilia </td><td>('2035969', 'Stefano Pini', 'stefano pini')<br/>('3468983', 'Marcella Cornia', 'marcella cornia')<br/>('1843795', 'Lorenzo Baraldi', 'lorenzo baraldi')<br/>('1741922', 'Rita Cucchiara', 'rita cucchiara')</td><td>{name.surname}@unimore.it -</td></tr><tr><td>ff398e7b6584d9a692e70c2170b4eecaddd78357</td><td></td><td></td><td></td></tr><tr><td>ffc5a9610df0341369aa75c0331ef021de0a02a9</td><td>Transferred Dimensionality Reduction +</td></tr><tr><td>fffefc1fb840da63e17428fd5de6e79feb726894</td><td>Fine-Grained Age Estimation in the wild with +<br/>Attention LSTM Networks +</td><td>('47969038', 'Ke Zhang', 'ke zhang')<br/>('49229283', 'Na Liu', 'na liu')<br/>('3451660', 'Xingfang Yuan', 'xingfang yuan')<br/>('46910049', 'Xinyao Guo', 'xinyao guo')<br/>('35038034', 'Ce Gao', 'ce gao')<br/>('2626320', 'Zhenbing Zhao', 'zhenbing zhao')</td><td></td></tr><tr><td>ff398e7b6584d9a692e70c2170b4eecaddd78357</td><td></td><td></td><td></td></tr><tr><td>ffc5a9610df0341369aa75c0331ef021de0a02a9</td><td>Transferred Dimensionality Reduction <br/>State Key Laboratory on Intelligent Technology and Systems <br/>Tsinghua National Laboratory for Information Science and Technology (TNList) <br/><b>Tsinghua University, Beijing 100084, China</b></td><td>('39747687', 'Zheng Wang', 'zheng wang')<br/>('1809614', 'Yangqiu Song', 'yangqiu song')<br/>('1700883', 'Changshui Zhang', 'changshui zhang')</td><td></td></tr><tr><td>ffd81d784549ee51a9b0b7b8aaf20d5581031b74</td><td>Performance Analysis of Retina and DoG @@ -29354,11 +37662,92 @@ <br/>Department of Engineering Science, <br/><b>University of Oxford, UK</b></td><td>('19263506', 'Arsha Nagrani', 'arsha nagrani')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>arsha@robots.ox.ac.uk/ <br/>az@robots.ox.ac.uk/ -</td></tr><tr><td>ff60d4601adabe04214c67e12253ea3359f4e082</td><td></td><td></td><td></td></tr><tr><td>ffc9d6a5f353e5aec3116a10cf685294979c63d9</td><td>Eigenphase-based face recognition: a comparison of phase- +</td></tr><tr><td>ff60d4601adabe04214c67e12253ea3359f4e082</td><td></td><td></td><td></td></tr><tr><td>ffe4bb47ec15f768e1744bdf530d5796ba56cfc1</td><td>AFIF4: Deep Gender Classification based on +<br/>AdaBoost-based Fusion of Isolated Facial Features and +<br/>Foggy Faces +<br/>aDepartment of Electrical Engineering and Computer Science, Lassonde School of +<br/><b>Engineering, York University, Canada</b><br/><b>bFaculty of Computers and Information, Assiut University, Egypt</b></td><td>('40239027', 'Abdelrahman Abdelhamed', 'abdelrahman abdelhamed')</td><td></td></tr><tr><td>ffc9d6a5f353e5aec3116a10cf685294979c63d9</td><td>Eigenphase-based face recognition: a comparison of phase- <br/>information extraction methods <br/>Faculty of Electrical Engineering and Computing, <br/><b>University of Zagreb, Unska 3, 10 000 Zagreb</b></td><td>('35675021', 'Slobodan Ribarić', 'slobodan ribarić')<br/>('3069572', 'Marijo Maračić', 'marijo maračić')</td><td>E-mail: slobodan.ribaric@fer.hr -</td></tr><tr><td>ffaad0204f4af763e3390a2f6053c0e9875376be</td><td>Article +</td></tr><tr><td>ff8ef43168b9c8dd467208a0b1b02e223b731254</td><td>BreakingNews: Article Annotation by +<br/>Image and Text Processing +</td><td>('1780343', 'Arnau Ramisa', 'arnau ramisa')<br/>('47242882', 'Fei Yan', 'fei yan')<br/>('1994318', 'Francesc Moreno-Noguer', 'francesc moreno-noguer')<br/>('1712041', 'Krystian Mikolajczyk', 'krystian mikolajczyk')</td><td></td></tr><tr><td>ff9195f99a1a28ced431362f5363c9a5da47a37b</td><td>Journal of Vision (2016) 16(15):28, 1–8 +<br/>Serial dependence in the perception of attractiveness +<br/><b>University of California</b><br/>Berkeley, CA, USA +<br/><b>University of California</b><br/>Berkeley, CA, USA +<br/>David Whitney +<br/><b>University of California</b><br/>Berkeley, CA, USA +<br/><b>Helen Wills Neuroscience Institute, University of</b><br/>California, Berkeley, CA, USA +<br/><b>Vision Science Group, University of California</b><br/>Berkeley, CA, USA +<br/>The perception of attractiveness is essential for choices +<br/>of food, object, and mate preference. Like perception of +<br/>other visual features, perception of attractiveness is +<br/>stable despite constant changes of image properties due +<br/>to factors like occlusion, visual noise, and eye +<br/>movements. Recent results demonstrate that perception +<br/>of low-level stimulus features and even more complex +<br/>attributes like human identity are biased towards recent +<br/>percepts. This effect is often called serial dependence. +<br/>Some recent studies have suggested that serial +<br/>dependence also exists for perceived facial +<br/>attractiveness, though there is also concern that the +<br/>reported effects are due to response bias. Here we used +<br/>an attractiveness-rating task to test the existence of +<br/>serial dependence in perceived facial attractiveness. Our +<br/>results demonstrate that perceived face attractiveness +<br/>was pulled by the attractiveness level of facial images +<br/>encountered up to 6 s prior. This effect was not due to +<br/>response bias and did not rely on the previous motor +<br/>response. This perceptual pull increased as the difference +<br/>in attractiveness between previous and current stimuli +<br/>increased. Our results reconcile previously conflicting +<br/>findings and extend previous work, demonstrating that +<br/>sequential dependence in perception operates across +<br/>different levels of visual analysis, even at the highest +<br/>levels of perceptual interpretation. +<br/>Introduction +<br/>Humans make aesthetic judgments all the time about +<br/>the attractiveness or desirability of objects and scenes. +<br/>Aesthetic judgments are not merely about judging +<br/>works of art; they are constantly involved in our daily +<br/>activity, influencing or determining our choices of food, +<br/>object (Creusen & Schoormans, 2005), and mate +<br/>preference (Rhodes, Simmons, & Peters, 2005). +<br/>Aesthetic judgments are based on perceptual pro- +<br/>cessing (Arnheim, 1954; Livingstone & Hubel, 2002; +<br/>Solso, 1996). These judgments, like other perceptual +<br/>experiences, are thought to be relatively stable in spite +<br/>of fluctuations in the raw visual input we receive due to +<br/>factors like occlusion, visual noise, and eye movements. +<br/>One mechanism that allows the visual system to achieve +<br/>this stability is serial dependence. Recent results have +<br/>revealed that the perception of visual features such as +<br/>orientation (Fischer & Whitney, 2014), numerosity +<br/>(Cicchini, Anobile, & Burr, 2014), and facial identity +<br/>(Liberman, Fischer, & Whitney, 2014) are systemati- +<br/>cally assimilated toward visual input from the recent +<br/>past. This perceptual pull has been distinguished from +<br/>hysteresis in motor responses or decision processes, and +<br/>has been shown to be tuned by the magnitude of the +<br/>difference between previous and current visual inputs +<br/>(Fischer & Whitney, 2014; Liberman, Fischer, & +<br/>Whitney, 2014). +<br/>Is aesthetics perception similarly stable like feature +<br/>perception? Some previous studies have suggested that +<br/>the answer is yes. It has been shown that there is a +<br/>positive correlation between observers’ successive +<br/>attractiveness ratings of facial images (Kondo, Taka- +<br/>hashi, & Watanabe, 2012; Taubert, Van der Burg, & +<br/>Alais, 2016). This suggests that there is an assimilative +<br/>sequential dependence in attractiveness judgments. +<br/>Citation: Xia, Y., Leib, A. Y., & Whitney, D. (2016). Serial dependence in the perception of attractiveness. Journal of Vision, +<br/>16(15):28, 1–8, doi:10.1167/16.15.28. +<br/>doi: 10 .116 7 /1 6. 15 . 28 +<br/>Received July 13, 2016; published December 22, 2016 +<br/>ISSN 1534-7362 +<br/>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. +</td><td>('27678837', 'Ye Xia', 'ye xia')<br/>('6931574', 'Allison Yamanashi Leib', 'allison yamanashi leib')</td><td></td></tr><tr><td>ffaad0204f4af763e3390a2f6053c0e9875376be</td><td>Article <br/>Non-Convex Sparse and Low-Rank Based Robust <br/>Subspace Segmentation for Data Mining <br/><b>School of Information Science and Technology, Donghua University, Shanghai 200051, China</b><br/><b>City University of Hong Kong, Kowloon 999077, Hong Kong, China</b><br/><b>School of Mathematics and Computer Science, Northeastern State University, Tahlequah, OK 74464, USA</b><br/>Received: 16 June 2017; Accepted: 10 July 2017; Published: 15 July 2017 @@ -29387,7 +37776,10 @@ </td><td>('9401261', 'Ziaul Haque Choudhury', 'ziaul haque choudhury')<br/>('9401261', 'Ziaul Haque Choudhury', 'ziaul haque choudhury')</td><td></td></tr><tr><td>c5468665d98ce7349d38afb620adbf51757ab86f</td><td>Pose-Encoded Spherical Harmonics for Robust Face <br/>Recognition Using a Single Image <br/><b>Center for Automation Research, University of Maryland, College Park, MD 20742, USA</b><br/>2 Vision Technologies Lab, Sarnoff Corporation, Princeton, NJ 08873, USA -</td><td>('39265975', 'Zhanfeng Yue', 'zhanfeng yue')<br/>('38480590', 'Wenyi Zhao', 'wenyi zhao')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>c5d13e42071813a0a9dd809d54268712eba7883f</td><td>Face Recognition Robust to Head Pose Changes Based on the RGB-D Sensor +</td><td>('39265975', 'Zhanfeng Yue', 'zhanfeng yue')<br/>('38480590', 'Wenyi Zhao', 'wenyi zhao')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>c588c89a72f89eed29d42f34bfa5d4cffa530732</td><td>Attributes2Classname: A discriminative model for attribute-based +<br/>unsupervised zero-shot learning +<br/><b>HAVELSAN Inc., 2Bilkent University, 3Hacettepe University</b></td><td>('9424554', 'Berkan Demirel', 'berkan demirel')<br/>('1939006', 'Ramazan Gokberk Cinbis', 'ramazan gokberk cinbis')<br/>('2011587', 'Nazli Ikizler-Cinbis', 'nazli ikizler-cinbis')</td><td>bdemirel@havelsan.com.tr, gcinbis@cs.bilkent.edu.tr, nazli@cs.hacettepe.edu.tr +</td></tr><tr><td>c5d13e42071813a0a9dd809d54268712eba7883f</td><td>Face Recognition Robust to Head Pose Changes Based on the RGB-D Sensor <br/><b>West Virginia University, Morgantown, WV</b></td><td>('2997432', 'Cesare Ciaccio', 'cesare ciaccio')<br/>('2671284', 'Lingyun Wen', 'lingyun wen')<br/>('1822413', 'Guodong Guo', 'guodong guo')</td><td>cciaccio@mix.wvu.edu, lwen@mix.wvu.edu, guodong.guo@mail.wvu.edu </td></tr><tr><td>c50d73557be96907f88b59cfbd1ab1b2fd696d41</td><td>JournalofElectronicImaging13(3),474–485(July2004). <br/>Semiconductor sidewall shape estimation @@ -29415,7 +37807,15 @@ <br/>CHINA </td><td>('1695589', 'SHIQING ZHANG', 'shiqing zhang')<br/>('1730594', 'XIAOMING ZHAO', 'xiaoming zhao')<br/>('38909691', 'BICHENG LEI', 'bicheng lei')</td><td>tzczsq@163.com, leibicheng@163.com <br/>tzxyzxm@163.com -</td></tr><tr><td>c5935b92bd23fd25cae20222c7c2abc9f4caa770</td><td>Spatiotemporal Multiplier Networks for Video Action Recognition +</td></tr><tr><td>c5ea084531212284ce3f1ca86a6209f0001de9d1</td><td>Audio-Visual Speech Processing for +<br/>Multimedia Localisation +<br/>by +<br/>Matthew Aaron Benatan +<br/>Submitted in accordance with the requirements +<br/>for the degree of Doctor of Philosophy +<br/><b>The University of Leeds</b><br/>School of Computing +<br/>September 2016 +</td><td></td><td></td></tr><tr><td>c5935b92bd23fd25cae20222c7c2abc9f4caa770</td><td>Spatiotemporal Multiplier Networks for Video Action Recognition <br/><b>Graz University of Technology</b><br/><b>Graz University of Technology</b><br/><b>York University, Toronto</b></td><td>('2322150', 'Christoph Feichtenhofer', 'christoph feichtenhofer')<br/>('1718587', 'Axel Pinz', 'axel pinz')<br/>('1709096', 'Richard P. Wildes', 'richard p. wildes')</td><td>feichtenhofer@tugraz.at <br/>axel.pinz@tugraz.at <br/>wildes@cse.yorku.ca @@ -29501,7 +37901,9 @@ </td></tr><tr><td>c220f457ad0b28886f8b3ef41f012dd0236cd91a</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 <br/>Crystal Loss and Quality Pooling for <br/>Unconstrained Face Verification and Recognition -</td><td>('40497884', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('2068427', 'Ankan Bansal', 'ankan bansal')<br/>('2680836', 'Hongyu Xu', 'hongyu xu')<br/>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>c2e03efd8c5217188ab685e73cc2e52c54835d1a</td><td>Deep Tree-structured Face: A Unified Representation for Multi-task Facial +</td><td>('40497884', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('2068427', 'Ankan Bansal', 'ankan bansal')<br/>('2680836', 'Hongyu Xu', 'hongyu xu')<br/>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>c254b4c0f6d5a5a45680eb3742907ec93c3a222b</td><td>A Fusion-based Gender Recognition Method +<br/>Using Facial Images +</td><td>('24033665', 'Benyamin Ghojogh', 'benyamin ghojogh')<br/>('1779028', 'Saeed Bagheri Shouraki', 'saeed bagheri shouraki')<br/>('1782221', 'Hoda Mohammadzade', 'hoda mohammadzade')<br/>('22395643', 'Ensieh Iranmehr', 'ensieh iranmehr')</td><td></td></tr><tr><td>c2e03efd8c5217188ab685e73cc2e52c54835d1a</td><td>Deep Tree-structured Face: A Unified Representation for Multi-task Facial <br/>Biometrics <br/>Department of Electrical Engineering and Computer Science <br/><b>University of Tennessee, Knoxville</b></td><td>('1691576', 'Rui Guo', 'rui guo')<br/>('9120475', 'Liu Liu', 'liu liu')<br/>('40560485', 'Wei Wang', 'wei wang')<br/>('2885826', 'Ali Taalimi', 'ali taalimi')<br/>('1690083', 'Chi Zhang', 'chi zhang')<br/>('1698645', 'Hairong Qi', 'hairong qi')</td><td>{rguo1, lliu25, wwang34, ataalimi, czhang24, hqi} @utk.edu @@ -29516,7 +37918,23 @@ <br/>MVA2013 IAPR International Conference on Machine Vision Applications, May 20-23, 2013, Kyoto, JAPAN <br/>Efficient Measuring of Facial Action Unit Activation Intensities <br/>using Active Appearance Models -<br/><b>Computer Vision Group, Friedrich Schiller University of Jena, Germany</b><br/><b>University Hospital Jena, Germany</b></td><td>('1708249', 'Daniel Haase', 'daniel haase')<br/>('8993584', 'Michael Kemmler', 'michael kemmler')<br/>('1814631', 'Orlando Guntinas-Lichius', 'orlando guntinas-lichius')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td></td></tr><tr><td>f6742010372210d06e531e7df7df9c01a185e241</td><td>Dimensional Affect and Expression in +<br/><b>Computer Vision Group, Friedrich Schiller University of Jena, Germany</b><br/><b>University Hospital Jena, Germany</b></td><td>('1708249', 'Daniel Haase', 'daniel haase')<br/>('8993584', 'Michael Kemmler', 'michael kemmler')<br/>('1814631', 'Orlando Guntinas-Lichius', 'orlando guntinas-lichius')<br/>('1728382', 'Joachim Denzler', 'joachim denzler')</td><td></td></tr><tr><td>f60a85bd35fa85739d712f4c93ea80d31aa7de07</td><td>VisDA: The Visual Domain Adaptation Challenge +<br/><b>Boston University</b><br/><b>EECS, University of California Berkeley</b></td><td>('2960713', 'Xingchao Peng', 'xingchao peng')<br/>('39058756', 'Ben Usman', 'ben usman')<br/>('34836903', 'Neela Kaushik', 'neela kaushik')<br/>('50196944', 'Judy Hoffman', 'judy hoffman')<br/>('2774612', 'Dequan Wang', 'dequan wang')<br/>('2903226', 'Kate Saenko', 'kate saenko')</td><td>xpeng,usmn,nkaushik,saenko@bu.edu, jhoffman,dqwang@eecs.berkeley.edu +</td></tr><tr><td>f6f06be05981689b94809130e251f9e4bf932660</td><td>An Approach to Illumination and Expression Invariant +<br/>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 91 – No.15, April 2014 +<br/>Multiple Classifier Face Recognition +<br/>Dalton Meitei Thounaojam +<br/><b>National Institute of Technology</b><br/>Silchar +<br/>Assam: 788010 +<br/>India +<br/><b>National Institute of Technology</b><br/>Silchar +<br/>Assam: 788010 +<br/>India +<br/>Romesh Laishram +<br/><b>Manipur Institute of Technology</b><br/>Imphal West: 795001 +<br/>India +</td><td></td><td></td></tr><tr><td>f68ed499e9d41f9c3d16d843db75dc12833d988d</td><td></td><td></td><td></td></tr><tr><td>f6742010372210d06e531e7df7df9c01a185e241</td><td>Dimensional Affect and Expression in <br/>Natural and Mediated Interaction <br/><b>Ritsumeikan, University</b><br/>Kyoto, Japan <br/>October, 2007 @@ -29542,7 +37960,9 @@ <br/>HUMAN AGE USING DWT AND SAMMON MAP <br/><b>Sathyabama University, Chennai, India</b><br/>2Department of Electronics Engineering, NITTTR, Chennai, India <br/>Received 2014-05-08; Revised 2014-05-23; Accepted 2014-11-28 -</td><td>('9513864', 'J. Nithyashri', 'j. nithyashri')<br/>('5014650', 'G. Kulanthaivel', 'g. kulanthaivel')</td><td></td></tr><tr><td>f6c70635241968a6d5fd5e03cde6907022091d64</td><td></td><td></td><td></td></tr><tr><td>f66f3d1e6e33cb9e9b3315d3374cd5f121144213</td><td>The Journal of Neuroscience, October 30, 2013 • 33(44):17435–17443 • 17435 +</td><td>('9513864', 'J. Nithyashri', 'j. nithyashri')<br/>('5014650', 'G. Kulanthaivel', 'g. kulanthaivel')</td><td></td></tr><tr><td>f6c70635241968a6d5fd5e03cde6907022091d64</td><td></td><td></td><td></td></tr><tr><td>f6149fc5b39fa6b33220ccee32a8ee3f6bbcaf4a</td><td>Syn2Real: A New Benchmark for +<br/>Synthetic-to-Real Visual Domain Adaptation +<br/><b>Boston University1, University of Tokyo</b><br/><b>University of California Berkeley</b></td><td>('2960713', 'Xingchao Peng', 'xingchao peng')<br/>('39058756', 'Ben Usman', 'ben usman')<br/>('8915348', 'Kuniaki Saito', 'kuniaki saito')<br/>('34836903', 'Neela Kaushik', 'neela kaushik')<br/>('2903226', 'Kate Saenko', 'kate saenko')</td><td></td></tr><tr><td>f66f3d1e6e33cb9e9b3315d3374cd5f121144213</td><td>The Journal of Neuroscience, October 30, 2013 • 33(44):17435–17443 • 17435 <br/>Behavioral/Cognitive <br/>Top-Down Control of Visual Responses to Fear by the <br/>Amygdala @@ -29624,7 +38044,19 @@ <br/>therefore may control how behaviorally relevant information is <br/>visually coded in a context-sensitive fashion. </td><td>('3162581', 'Nicholas Furl', 'nicholas furl')<br/>('3162581', 'Nicholas Furl', 'nicholas furl')</td><td>Unit, 15 Chaucer Road, Cambridge, CB2 7EF, United Kingdom. E-mail: nick.furl@mrc-cbu.cam.ac.uk. -</td></tr><tr><td>f6abecc1f48f6ec6eede4143af33cc936f14d0d0</td><td></td><td></td><td></td></tr><tr><td>f6fa97fbfa07691bc9ff28caf93d0998a767a5c1</td><td>k2-means for fast and accurate large scale clustering +</td></tr><tr><td>f6ce34d6e4e445cc2c8a9b8ba624e971dd4144ca</td><td>Cross-label Suppression: A Discriminative and Fast +<br/>Dictionary Learning with Group Regularization +<br/>April 24, 2017 +</td><td>('9293691', 'Xiudong Wang', 'xiudong wang')<br/>('2080215', 'Yuantao Gu', 'yuantao gu')</td><td></td></tr><tr><td>f6abecc1f48f6ec6eede4143af33cc936f14d0d0</td><td></td><td></td><td></td></tr><tr><td>f61d5f2a082c65d5330f21b6f36312cc4fab8a3b</td><td>Multi-Level Variational Autoencoder: +<br/>Learning Disentangled Representations from +<br/>Grouped Observations +<br/>OVAL Group +<br/><b>University of Oxford</b><br/>Machine Intelligence and Perception Group +<br/>Microsoft Research +<br/>Cambridge, UK +</td><td>('3365029', 'Diane Bouchacourt', 'diane bouchacourt')<br/>('2870603', 'Ryota Tomioka', 'ryota tomioka')<br/>('2388416', 'Sebastian Nowozin', 'sebastian nowozin')</td><td>diane@robots.ox.ac.uk +<br/>{ryoto,Sebastian.Nowozin}@microsoft.com +</td></tr><tr><td>f6fa97fbfa07691bc9ff28caf93d0998a767a5c1</td><td>k2-means for fast and accurate large scale clustering <br/>Computer Vision Lab <br/>D-ITET <br/>ETH Zurich @@ -29636,6 +38068,9 @@ </td><td>('2794259', 'Eirikur Agustsson', 'eirikur agustsson')<br/>('1732855', 'Radu Timofte', 'radu timofte')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>aeirikur@vision.ee.ethz.ch <br/>timofter@vision.ee.ethz.ch <br/>vangool@vision.ee.ethz.ch +</td></tr><tr><td>f6cf2108ec9d0f59124454d88045173aa328bd2e</td><td>Robust user identification based on facial action units +<br/>unaffected by users’ emotions +<br/><b>Aalen University, Germany</b></td><td>('3114281', 'Ricardo Buettner', 'ricardo buettner')</td><td>ricardo.buettner@hs-aalen.de </td></tr><tr><td>f68f20868a6c46c2150ca70f412dc4b53e6a03c2</td><td>157 <br/>Differential Evolution to Optimize <br/>Hidden Markov Models Training: @@ -29707,12 +38142,35 @@ <br/>can be used. <br/>The presented work in this paper is a part of <br/>a project which aims to construct “An Optimal -</td><td>('2654160', 'Khadoudja Ghanem', 'khadoudja ghanem')<br/>('1749675', 'Amer Draa', 'amer draa')<br/>('2483552', 'Elvis Vyumvuhore', 'elvis vyumvuhore')</td><td></td></tr><tr><td>e9ed17fd8bf1f3d343198e206a4a7e0561ad7e66</td><td>International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463 +</td><td>('2654160', 'Khadoudja Ghanem', 'khadoudja ghanem')<br/>('1749675', 'Amer Draa', 'amer draa')<br/>('2483552', 'Elvis Vyumvuhore', 'elvis vyumvuhore')</td><td></td></tr><tr><td>f6e00d6430cbbaa64789d826d093f7f3e323b082</td><td>Visual Object Recognition +<br/><b>University of Texas at Austin</b><br/><b>RWTH Aachen University</b><br/>SYNTHESIS LECTURES ON COMPUTER +<br/>VISION # 1 +</td><td>('1794409', 'Kristen Grauman', 'kristen grauman')<br/>('1789756', 'Bastian Leibe', 'bastian leibe')</td><td></td></tr><tr><td>e9a5a38e7da3f0aa5d21499149536199f2e0e1f7</td><td>Article +<br/>A Bayesian Scene-Prior-Based Deep Network Model +<br/>for Face Verification +<br/><b>North China University of Technology</b><br/><b>Curtin University, Perth, WA 6102, Australia</b><br/>† These authors contributed equally to this work. +<br/>Received: 12 May 2018; Accepted: 8 June 2018 ; Published: 11 June 2018 +</td><td>('2104779', 'Huafeng Wang', 'huafeng wang')<br/>('2239474', 'Haixia Pan', 'haixia pan')<br/>('3229158', 'Wenfeng Song', 'wenfeng song')<br/>('1713220', 'Wanquan Liu', 'wanquan liu')<br/>('47311804', 'Ning Song', 'ning song')<br/>('2361868', 'Yuehai Wang', 'yuehai wang')</td><td>Beijing 100144, China; wangyuehai@ncut.edu.cn +<br/>2 Department of Software, Beihang University, Beijing 100191, China; swfbuaa@163.com +<br/>* Correspondence: wanghuafeng@ncut.edu.cn (H.W.); W.Liu@curtin.edu.au (W.L.); zy1621125@buaa.edu.cn +<br/>(N.S.); haixiapan@buaa.edu.cn (H.P.); Tel.: +86-189-1192-4121 (H.W.) +</td></tr><tr><td>e9ed17fd8bf1f3d343198e206a4a7e0561ad7e66</td><td>International Journal of Enhanced Research in Science Technology & Engineering, ISSN: 2319-7463 <br/>Vol. 3 Issue 1, January-2014, pp: (362-365), Impact Factor: 1.252, Available online at: www.erpublications.com <br/>Cognitive Learning for Social Robot through <br/>Facial Expression from Video Input <br/>1Department of Automation & Robotics, 2Department of Computer Science & Engg. -</td><td>('26944751', 'Neeraj Rai', 'neeraj rai')<br/>('2586264', 'Deepak Rai', 'deepak rai')<br/>('26477055', 'Ajay Kumar Garg', 'ajay kumar garg')</td><td></td></tr><tr><td>e9e40e588f8e6510fa5537e0c9e083ceed5d07ad</td><td>Fast Face Detection Using Graphics Processor +</td><td>('26944751', 'Neeraj Rai', 'neeraj rai')<br/>('2586264', 'Deepak Rai', 'deepak rai')<br/>('26477055', 'Ajay Kumar Garg', 'ajay kumar garg')</td><td></td></tr><tr><td>e988be047b28ba3b2f1e4cdba3e8c94026139fcf</td><td>Multi-Task Convolutional Neural Network for +<br/>Pose-Invariant Face Recognition +</td><td>('2399004', 'Xi Yin', 'xi yin')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td></td></tr><tr><td>e9d43231a403b4409633594fa6ccc518f035a135</td><td>Deformable Part Models with CNN Features +<br/>Kokkinos1,2 +<br/>1 Ecole Centrale Paris,2 INRIA, 3TTI-Chicago (cid:63) +</td><td>('2381485', 'Stavros Tsogkas', 'stavros tsogkas')<br/>('2776496', 'George Papandreou', 'george papandreou')</td><td></td></tr><tr><td>e90e12e77cab78ba8f8f657db2bf4ae3dabd5166</td><td>Nonconvex Sparse Spectral Clustering by Alternating Direction Method of +<br/>Multipliers and Its Convergence Analysis +<br/><b>National University of Singapore</b><br/><b>Key Laboratory of Machine Perception (MOE), School of EECS, Peking University</b><br/><b>Cooperative Medianet Innovation Center, Shanghai Jiao Tong University</b><br/><b>AI Institute</b></td><td>('33224509', 'Canyi Lu', 'canyi lu')<br/>('33221685', 'Jiashi Feng', 'jiashi feng')<br/>('33383055', 'Zhouchen Lin', 'zhouchen lin')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td>canyilu@gmail.com, elefjia@nus.edu.sg, zlin@pku.edu.cn, eleyans@nus.edu.sg +</td></tr><tr><td>e9c008d31da38d9eef67a28d2c77cb7daec941fb</td><td>Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing +<br/>the Early Softmax Saturation +<br/><b>School of Information and Communication Engineering, Beijing University of Posts and Telecommunications</b><br/><b>School of Computer Science, Beijing University of Posts and Telecommunications, Beijing China</b></td><td>('3450321', 'Binghui Chen', 'binghui chen')<br/>('1774956', 'Weihong Deng', 'weihong deng')<br/>('8491162', 'Junping Du', 'junping du')</td><td>chenbinghui@bupt.edu.cn, whdeng@bupt.edu.cn, junpingd@bupt.edu.cn +</td></tr><tr><td>e9e40e588f8e6510fa5537e0c9e083ceed5d07ad</td><td>Fast Face Detection Using Graphics Processor <br/><b>National Institute of Technology Karnataka</b><br/>Surathkal, India </td><td>('36598334', 'K.Vinay Kumar', 'k.vinay kumar')</td><td></td></tr><tr><td>e9bb045e702ee38e566ce46cc1312ed25cb59ea7</td><td>Integrating Geometric and Textural Features for <br/>Facial Emotion Classification using SVM @@ -29735,12 +38193,39 @@ <br/>Electrical and Computer Engineering <br/><b>University of Memphis</b><br/>Memphis, TN 38152, USA </td><td>('2497319', 'M. Iftekhar Tanveer', 'm. iftekhar tanveer')<br/>('2464507', 'Sreya Ghosh', 'sreya ghosh')<br/>('33019079', 'A.K.M. Mahbubur Rahman', 'a.k.m. mahbubur rahman')<br/>('1828610', 'Mohammed Yeasin', 'mohammed yeasin')</td><td>{mtanveer,aanam,sghosh,arahman,myeasin}@memphis.edu +</td></tr><tr><td>e9363f4368b04aeaa6d6617db0a574844fc59338</td><td>BENCHIP: Benchmarking Intelligence +<br/>Processors +<br/>1ICT CAS,2Cambricon,3Alibaba Infrastructure Service, Alibaba Group +<br/>4IFLYTEK,5JD,6RDA Microelectronics,7AMD +</td><td>('2631042', 'Jinhua Tao', 'jinhua tao')<br/>('1678776', 'Zidong Du', 'zidong du')<br/>('50770616', 'Qi Guo', 'qi guo')<br/>('4304175', 'Huiying Lan', 'huiying lan')<br/>('48571185', 'Lei Zhang', 'lei zhang')<br/>('7523063', 'Shengyuan Zhou', 'shengyuan zhou')<br/>('49046597', 'Cong Liu', 'cong liu')<br/>('49343896', 'Shan Tang', 'shan tang')<br/>('38253244', 'Allen Rush', 'allen rush')<br/>('47482936', 'Willian Chen', 'willian chen')<br/>('39419985', 'Shaoli Liu', 'shaoli liu')<br/>('7377735', 'Yunji Chen', 'yunji chen')<br/>('7934735', 'Tianshi Chen', 'tianshi chen')</td><td></td></tr><tr><td>f1250900074689061196d876f551ba590fc0a064</td><td>Learning to Recognize Actions from Limited Training +<br/>Examples Using a Recurrent Spiking Neural Model +<br/><b>School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA</b><br/>2Intel Labs, Hillsboro, OR, USA 97124 +</td><td>('9352814', 'Priyadarshini Panda', 'priyadarshini panda')<br/>('1753812', 'Narayan Srinivasa', 'narayan srinivasa')</td><td>*Correspondence: narayan.srinivasa@intel.com +</td></tr><tr><td>f1b4583c576d6d8c661b4b2c82bdebf3ba3d7e53</td><td>Faster Than Real-time Facial Alignment: A 3D Spatial Transformer Network +<br/>Approach in Unconstrained Poses +<br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA +</td><td>('47894545', 'Chenchen Zhu', 'chenchen zhu')<br/>('1769788', 'Khoa Luu', 'khoa luu')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td>cbhagava@andrew.cmu.edu, zcckernel@cmu.edu, kluu@andrew.cmu.edu, msavvid@ri.cmu.edu </td></tr><tr><td>f16a605abb5857c39a10709bd9f9d14cdaa7918f</td><td>Fast greyscale road sign model matching <br/>and recognition <br/>Centre de Visió per Computador <br/>Edifici O – Campus UAB, 08193 Bellaterra, Barcelona, Catalonia, Spain </td><td>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('1724155', 'Petia Radeva', 'petia radeva')</td><td>{sescalera,petia}@cvc.uab.es -</td></tr><tr><td>f1748303cc02424704b3a35595610890229567f9</td><td></td><td></td><td></td></tr><tr><td>f1d090fcea63d9f9e835c49352a3cd576ec899c1</td><td>Iosifidis, A., Tefas, A., & Pitas, I. (2015). Single-Hidden Layer Feedforward +</td></tr><tr><td>f1aa120fb720f6cfaab13aea4b8379275e6d40a2</td><td>InverseFaceNet: Deep Single-Shot Inverse Face Rendering From A Single Image +<br/><b>Max-Planck-Institute for Informatics</b><br/><b>University of Erlangen-Nuremberg 3 University of Bath</b><br/>Figure 1. Our single-shot deep inverse face renderer InverseFaceNet obtains a high-quality geometry, reflectance and illumination estimate +<br/>from just a single input image. We jointly recover the face pose, shape, expression, reflectance and incident scene illumination. From left to +<br/>right: input photo, our estimated face model, its geometry, and the pointwise Euclidean error compared to Garrido et al. [14]. +</td><td>('3022958', 'Hyeongwoo Kim', 'hyeongwoo kim')<br/>('34105638', 'Justus Thies', 'justus thies')<br/>('1699058', 'Michael Zollhöfer', 'michael zollhöfer')<br/>('1819028', 'Christian Richardt', 'christian richardt')<br/>('1680185', 'Christian Theobalt', 'christian theobalt')<br/>('9102722', 'Ayush Tewari', 'ayush tewari')</td><td></td></tr><tr><td>f1748303cc02424704b3a35595610890229567f9</td><td></td><td></td><td></td></tr><tr><td>f1ba2fe3491c715ded9677862fea966b32ca81f0</td><td>ISSN: 2321-7782 (Online) +<br/>Volume 1, Issue 7, December 2013 +<br/>International Journal of Advance Research in +<br/>Computer Science and Management Studies +<br/>Research Paper +<br/>Available online at: www.ijarcsms.com +<br/>Face Tracking and Recognition in Videos: +<br/>HMM Vs KNN +<br/>Assistant Professor +<br/>Department of Computer Engineering +<br/><b>MIT College of Engineering (Pune University</b><br/>Pune - India +</td><td></td><td></td></tr><tr><td>f1d090fcea63d9f9e835c49352a3cd576ec899c1</td><td>Iosifidis, A., Tefas, A., & Pitas, I. (2015). Single-Hidden Layer Feedforward <br/>Neual Network Training Using Class Geometric Information. In . J. J. <br/>Computational Intelligence: International Joint Conference, IJCCI 2014 <br/>Rome, Italy, October 22-24, 2014 Revised Selected Papers. (Vol. III, pp. @@ -29755,7 +38240,14 @@ <br/>This document is made available in accordance with publisher policies. Please cite only the published <br/>version using the reference above. Full terms of use are available: <br/>http://www.bristol.ac.uk/pure/about/ebr-terms.html -<br/> </td><td>('1685469', 'A. Rosa', 'a. rosa')<br/>('9246794', 'J. M. Cadenas', 'j. m. cadenas')<br/>('2092535', 'A. Dourado', 'a. dourado')<br/>('39545211', 'K. Madani', 'k. madani')</td><td></td></tr><tr><td>f19777e37321f79e34462fc4c416bd56772031bf</td><td>International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012 1 +<br/> </td><td>('1685469', 'A. Rosa', 'a. rosa')<br/>('9246794', 'J. M. Cadenas', 'j. m. cadenas')<br/>('2092535', 'A. Dourado', 'a. dourado')<br/>('39545211', 'K. Madani', 'k. madani')</td><td></td></tr><tr><td>f113aed343bcac1021dc3e57ba6cc0647a8f5ce1</td><td>International Journal of Science and Research (IJSR) +<br/>ISSN (Online): 2319-7064 +<br/>Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +<br/>A Survey on Mining of Weakly Labeled Web Facial +<br/>Images and Annotation +<br/><b>Pune Institute of Computer Technology, Pune, India</b><br/><b>Pune Institute of Computer Technology, Pune, India</b><br/>the +<br/>the proposed system which +</td><td></td><td></td></tr><tr><td>f19777e37321f79e34462fc4c416bd56772031bf</td><td>International Journal of Scientific & Engineering Research, Volume 3, Issue 6, June-2012 1 <br/>ISSN 2229-5518 <br/>Literature Review of Image Compression Algorithm <br/> Dr. B. Chandrasekhar @@ -29779,7 +38271,13 @@ <br/>Die Dissertation wurde am 16.06.2009 bei der Technischen Universit¨at M¨unchen einge- <br/>reicht und durch die Fakult¨at f¨ur Elektrotechnik und Informationstechnik am 30.10.2009 <br/>angenommen. -</td><td></td><td></td></tr><tr><td>e76798bddd0f12ae03de26b7c7743c008d505215</td><td></td><td></td><td></td></tr><tr><td>e793f8644c94b81b7a0f89395937a7f8ad428a89</td><td>LPM for Action Recognition in Temporally +</td><td></td><td></td></tr><tr><td>e76798bddd0f12ae03de26b7c7743c008d505215</td><td></td><td></td><td></td></tr><tr><td>e7cac91da51b78eb4a28e194d3f599f95742e2a2</td><td>RESEARCH ARTICLE +<br/>Positive Feeling, Negative Meaning: +<br/>Visualizing the Mental Representations of In- +<br/>Group and Out-Group Smiles +<br/><b>Saarland University, Saarbr cken, Germany, 2 Utrecht University, Utrecht, the Netherlands</b><br/><b>Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands</b><br/>☯ These authors contributed equally to this work. +</td><td>('34533048', 'Andrea Paulus', 'andrea paulus')<br/>('40358273', 'Michaela Rohr', 'michaela rohr')<br/>('2365875', 'Ron Dotsch', 'ron dotsch')<br/>('3905267', 'Dirk Wentura', 'dirk wentura')</td><td>* a.paulus@mx.uni-saarland.de +</td></tr><tr><td>e793f8644c94b81b7a0f89395937a7f8ad428a89</td><td>LPM for Action Recognition in Temporally <br/>Untrimmed Videos <br/>School of Electrical Engineering and Computer Scinece <br/><b>University of Ottawa, Ottawa, On, Canada</b></td><td>('36047295', 'Feng Shi', 'feng shi')<br/>('1745632', 'Emil Petriu', 'emil petriu')</td><td>{fshi098, laganier, petriu}@site.uottawa.ca @@ -29867,6 +38365,9 @@ </td><td>('1731883', 'Alexander M. Bronstein', 'alexander m. bronstein')<br/>('1732570', 'Michael M. Bronstein', 'michael m. bronstein')<br/>('1692832', 'Ron Kimmel', 'ron kimmel')</td><td>Email: alexbron@ieee.org <br/>bronstein@ieee.org <br/>ron@cs.technion.ac.il +</td></tr><tr><td>e7b2b0538731adaacb2255235e0a07d5ccf09189</td><td>Learning Deep Representations with +<br/>Probabilistic Knowledge Transfer +<br/><b>Aristotle University of Thessaloniki, Thessaloniki 541 24, Greece</b></td><td>('3200630', 'Nikolaos Passalis', 'nikolaos passalis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')</td><td>passalis@csd.auth.gr, tefas@aiia.csd.auth.gr </td></tr><tr><td>e726acda15d41b992b5a41feabd43617fab6dc23</td><td></td><td></td><td></td></tr><tr><td>e74816bc0803460e20edbd30a44ab857b06e288e</td><td>Semi-Automated Annotation of Discrete States <br/>in Large Video Datasets <br/>Lex Fridman @@ -29879,7 +38380,19 @@ <br/>RECOGNITION OF IDENTICAL TWINS <br/>1Department of Electrical,Computer and Biomedical Engineering, Qazvin branch, Islamic <br/><b>Amirkabir University of Technology, Tehran</b><br/><b>Azad University, Qazvin, Iran</b><br/>Iran -</td><td>('1692435', 'Karim Faez', 'karim faez')</td><td></td></tr><tr><td>cbcf5da9f09b12f53d656446fd43bc6df4b2fa48</td><td>ISSN: 2277-3754 +</td><td>('1692435', 'Karim Faez', 'karim faez')</td><td></td></tr><tr><td>cbca355c5467f501d37b919d8b2a17dcb39d3ef9</td><td>CANSIZOGLU, JONES: SUPER-RESOLUTION OF VERY LR FACES FROM VIDEOS +<br/>Super-resolution of Very Low-Resolution +<br/>Faces from Videos +<br/>Esra Ataer-Cansizoglu +<br/><b>Mitsubishi Electric Research Labs</b><br/>(MERL) +<br/>Cambridge, MA, USA +</td><td>('1961683', 'Michael Jones', 'michael jones')</td><td>cansizoglu@merl.com +<br/>mjones@merl.com +</td></tr><tr><td>cbbd13c29d042743f0139f1e044b6bca731886d0</td><td>Not-So-CLEVR: learning same–different relations strains +<br/>feedforward neural networks +<br/>†equal contributions +<br/>Department of Cognitive, Linguistic & Psychological Sciences +<br/><b>Carney Institute for Brain Science</b><br/><b>Brown University, Providence, RI 02912, USA</b></td><td>('5546699', 'Junkyung Kim', 'junkyung kim')</td><td></td></tr><tr><td>cbcf5da9f09b12f53d656446fd43bc6df4b2fa48</td><td>ISSN: 2277-3754 <br/>ISO 9001:2008 Certified <br/>International Journal of Engineering and Innovative Technology (IJEIT) <br/>Volume 2, Issue 6, December 2012 @@ -29891,7 +38404,26 @@ <br/><b>Stanford University</b><br/>B.S. Computer Science <br/><b>Stanford University</b></td><td></td><td>tanner12@stanford.edu <br/>bakis@stanford.edu -</td></tr><tr><td>cb9092fe74ea6a5b2bb56e9226f1c88f96094388</td><td></td><td></td><td></td></tr><tr><td>cb08f679f2cb29c7aa972d66fe9e9996c8dfae00</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 +</td></tr><tr><td>cb004e9706f12d1de83b88c209ac948b137caae0</td><td>Face Aging Effect Simulation using Hidden Factor +<br/>Analysis Joint Sparse Representation +</td><td>('1787137', 'Hongyu Yang', 'hongyu yang')<br/>('31454775', 'Di Huang', 'di huang')<br/>('40013375', 'Yunhong Wang', 'yunhong wang')<br/>('46506697', 'Heng Wang', 'heng wang')<br/>('2289713', 'Yuanyan Tang', 'yuanyan tang')</td><td></td></tr><tr><td>cb2917413c9b36c3bb9739bce6c03a1a6eb619b3</td><td>MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition +<br/><b>University of Science and Technology of China</b><br/>2Microsoft Research Asia +</td><td>('49455479', 'Yizhou Zhou', 'yizhou zhou')<br/>('48305246', 'Xiaoyan Sun', 'xiaoyan sun')<br/>('2057216', 'Zheng-Jun Zha', 'zheng-jun zha')<br/>('8434337', 'Wenjun Zeng', 'wenjun zeng')</td><td>zyz0205@mail.ustc.edu.cn, zhazj@ustc.edu.cn +<br/>{xysun,wezeng}@microsoft.com +</td></tr><tr><td>cb9092fe74ea6a5b2bb56e9226f1c88f96094388</td><td></td><td></td><td></td></tr><tr><td>cb13e29fb8af6cfca568c6dc523da04d1db1fff5</td><td>Paper accepted to Frontiers in Psychology +<br/>Received: 02 Dec 2017 +<br/>Accepted: 12 June 2018 +<br/>DOI: 10.3389/fpsyg.2018.01128 +<br/>A Survey of Automatic Facial +<br/>Micro-expression Analysis: +<br/>Databases, Methods and Challenges +<br/><b>Multimedia University, Faculty of Engineering, Cyberjaya, 63100 Selangor, Malaysia</b><br/><b>Multimedia University, Faculty of Computing and Informatics, Cyberjaya</b><br/>Selangor, Malaysia +<br/><b>University of Nottingham, School of Psychology, University Park, Nottingham NG</b><br/>2RD, United Kingdom +<br/><b>Multimedia University, Research Institute for Digital Security, Cyberjaya</b><br/>Selangor, Malaysia +<br/><b>Monash University Malaysia, School of Information Technology, Sunway</b><br/>Selangor, Malaysia +<br/>Correspondence*: +</td><td>('2154760', 'Yee-Hui Oh', 'yee-hui oh')<br/>('2339975', 'John See', 'john see')<br/>('35256518', 'Anh Cat Le Ngo', 'anh cat le ngo')<br/>('6633183', 'Raphael C.-W. Phan', 'raphael c.-w. phan')<br/>('34287833', 'Vishnu Monn Baskaran', 'vishnu monn baskaran')<br/>('2339975', 'John See', 'john see')</td><td>johnsee@mmu.edu.my +</td></tr><tr><td>cb08f679f2cb29c7aa972d66fe9e9996c8dfae00</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 13, NO. 9, SEPTEMBER 2014 <br/>Action Understanding <br/>with Multiple Classes of Actors </td><td>('2026123', 'Chenliang Xu', 'chenliang xu')<br/>('2228109', 'Caiming Xiong', 'caiming xiong')<br/>('3587688', 'Jason J. Corso', 'jason j. corso')</td><td></td></tr><tr><td>cb84229e005645e8623a866d3d7956c197f85e11</td><td>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. X, NO. X, MONTH 201X @@ -29901,6 +38433,22 @@ <br/><b>University of Florida</b><br/>Electrical & Computer Engineering </td><td>('3445153', 'Nima Karimian', 'nima karimian')<br/>('2171076', 'Damon L. Woodard', 'damon l. woodard')<br/>('2925373', 'Domenic Forte', 'domenic forte')</td><td>nima@engr.uconn.edu <br/>dwoodard, dforte@ece.ufl.edu +</td></tr><tr><td>cbb27980eb04f68d9f10067d3d3c114efa9d0054</td><td>An Attention Model for group-level emotion recognition +<br/><b>Indian Institute of Technology</b><br/>Roorkee +<br/>Roorkee, India +<br/><b>Indian Institute of Technology</b><br/>Roorkee +<br/>Roorkee, India +<br/><b>Indian Institute of Technology</b><br/>Roorkee +<br/>Roorkee, India +<br/>École de Technologie Supérieure +<br/>Montreal, Canada +<br/>École de Technologie Supérieure +<br/>Montreal, Canada +</td><td>('51127375', 'Aarush Gupta', 'aarush gupta')<br/>('51134535', 'Dakshit Agrawal', 'dakshit agrawal')<br/>('51118849', 'Hardik Chauhan', 'hardik chauhan')<br/>('3055538', 'Jose Dolz', 'jose dolz')<br/>('3048367', 'Marco Pedersoli', 'marco pedersoli')</td><td>agupta1@cs.iitr.ac.in +<br/>dagrawal@cs.iitr.ac.in +<br/>haroi.uee2014@iitr.ac.in +<br/>jose.dolz@livia.etsmtl.ca +<br/>Marco.Pedersoli@etsmtl.ca </td></tr><tr><td>cbe859d151466315a050a6925d54a8d3dbad591f</td><td>GAZE SHIFTS AS DYNAMICAL RANDOM SAMPLING <br/>Dipartimento di Scienze dell’Informazione <br/>Universit´a di Milano @@ -29925,7 +38473,12 @@ <br/>Alexander G. Hauptmann, Chair <br/>Submitted in partial fulfillment of the requirements <br/>for the degree of Doctor of Philosophy. -</td><td>('34692532', 'Zhenzhong Lan', 'zhenzhong lan')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')<br/>('34692532', 'Zhenzhong Lan', 'zhenzhong lan')</td><td></td></tr><tr><td>f83dd9ff002a40228bbe3427419b272ab9d5c9e4</td><td>Facial Features Matching using a Virtual Structuring Element +</td><td>('34692532', 'Zhenzhong Lan', 'zhenzhong lan')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')<br/>('34692532', 'Zhenzhong Lan', 'zhenzhong lan')</td><td></td></tr><tr><td>f842b13bd494be1bbc1161dc6df244340b28a47f</td><td>An Improved Face Recognition Technique Based +<br/>on Modular Multi-directional Two-dimensional +<br/>Principle Component Analysis Approach +<br/><b>Hanshan Normal University, Chaozhou, 521041, China</b><br/><b>Hanshan Normal University, Chaozhou, 521041, China</b></td><td>('48477766', 'Xiaoqing Dong', 'xiaoqing dong')<br/>('2747115', 'Hongcai Chen', 'hongcai chen')</td><td>Email: dxqzq110@163.com +<br/>Email: czhschc@126.com +</td></tr><tr><td>f83dd9ff002a40228bbe3427419b272ab9d5c9e4</td><td>Facial Features Matching using a Virtual Structuring Element <br/>Intelligent Systems Lab Amsterdam, <br/><b>University of Amsterdam</b><br/>Kruislaan 403, 1098 SJ Amsterdam, The Netherlands </td><td>('9301018', 'Roberto Valenti', 'roberto valenti')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')<br/>('1695527', 'Theo Gevers', 'theo gevers')</td><td></td></tr><tr><td>f8c94afd478821681a1565d463fc305337b02779</td><td> @@ -29959,6 +38512,12 @@ <br/>ISSN 2229-5518 <br/>Artificial Neural Network Design and Parameter <br/>Optimization for Facial Expressions Recognition +</td><td></td><td></td></tr><tr><td>f8f872044be2918de442ba26a30336d80d200c42</td><td>IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 03, 2015 | ISSN (online): 2321-0613 +<br/>Facial Emotion Recognition Techniques: A Survey +<br/>1,2Department of Computer Science and Engineering +<br/><b>Dr C V Raman Institute of Science and Technology</b><br/>defense +<br/>systems, +<br/>surveillance </td><td></td><td></td></tr><tr><td>f8a5bc2bd26790d474a1f6cc246b2ba0bcde9464</td><td>ORIGINAL RESEARCH <br/>published: 19 December 2017 <br/>doi: 10.3389/fpsyg.2017.02181 @@ -30030,6 +38589,14 @@ <br/>Frontiers in Psychology | www.frontiersin.org <br/>December 2017 | Volume 8 | Article 2181 </td><td>('28239829', 'Margarida V. Garrido', 'margarida v. garrido')<br/>('38831356', 'Marília Prada', 'marília prada')<br/>('28239829', 'Margarida V. Garrido', 'margarida v. garrido')</td><td>margarida.garrido@iscte-iul.pt +</td></tr><tr><td>f87b22e7f0c66225824a99cada71f9b3e66b5742</td><td>Robust Emotion Recognition from Low Quality and Low Bit Rate Video: +<br/>A Deep Learning Approach +<br/><b>Beckman Institute, University of Illinois at Urbana-Champaign</b><br/><b>Texas AandM University</b><br/><b>University of Missouri, Kansas City</b><br/>§ Snap Inc, USA +<br/><b>University of Washington</b></td><td>('50563570', 'Bowen Cheng', 'bowen cheng')<br/>('2969311', 'Zhangyang Wang', 'zhangyang wang')<br/>('4622305', 'Zhaobin Zhang', 'zhaobin zhang')<br/>('49970050', 'Zhu Li', 'zhu li')<br/>('1771885', 'Ding Liu', 'ding liu')<br/>('1706007', 'Jianchao Yang', 'jianchao yang')<br/>('47156875', 'Shuai Huang', 'shuai huang')<br/>('1739208', 'Thomas S. Huang', 'thomas s. huang')</td><td>{bcheng9, dingliu2, t-huang1}@illinois.edu +<br/>atlaswang@tamu.edu +<br/>{zzktb@mail., lizhu@}umkc.edu +<br/>jianchao.yang@snap.com +<br/>shuaih@uw.edu </td></tr><tr><td>cef841f27535c0865278ee9a4bc8ee113b4fb9f3</td><td></td><td></td><td></td></tr><tr><td>ce6d60b69eb95477596535227958109e07c61e1e</td><td>Unconstrained Face Verification Using Fisher Vectors <br/>Computed From Frontalized Faces <br/>Center for Automation Research @@ -30124,13 +38691,35 @@ <br/><b>University College London</b><br/>Department of Computer Science <br/><b>University College London</b><br/>Supervisor: Prof. Bernard F. Buxton <br/>February 2016 -</td><td>('2768033', 'Houari Abdallahi', 'houari abdallahi')</td><td></td></tr><tr><td>ce691a37060944c136d2795e10ed7ba751cd8394</td><td></td><td></td><td></td></tr><tr><td>ce3f3088d0c0bf236638014a299a28e492069753</td><td></td><td></td><td></td></tr><tr><td>ceeb67bf53ffab1395c36f1141b516f893bada27</td><td>Face Alignment by Local Deep Descriptor Regression +</td><td>('2768033', 'Houari Abdallahi', 'houari abdallahi')</td><td></td></tr><tr><td>ce691a37060944c136d2795e10ed7ba751cd8394</td><td></td><td></td><td></td></tr><tr><td>ce3f3088d0c0bf236638014a299a28e492069753</td><td></td><td></td><td></td></tr><tr><td>ceaa5eb51f761b5f84bd88b58c8f484fcd2a22d6</td><td>UC San Diego +<br/>UC San Diego Electronic Theses and Dissertations +<br/>Title +<br/>Inhibitions of ascorbate fatty acid derivatives on three rabbit muscle glycolytic enzymes +<br/>Permalink +<br/>https://escholarship.org/uc/item/8x33n1gj +<br/>Author +<br/>Pham, Duyen-Anh +<br/>Publication Date +<br/>2011-01-01 +<br/>Peer reviewed|Thesis/dissertation +<br/>eScholarship.org +<br/>Powered by the California Digital Library +<br/><b>University of California</b></td><td></td><td></td></tr><tr><td>ce450e4849490924488664b44769b4ca57f1bc1a</td><td>Procedural Generation of Videos to Train Deep Action Recognition Networks +<br/>1Computer Vision Group, NAVER LABS Europe, Meylan, France +<br/>2Centre de Visi´o per Computador, Universitat Aut`onoma de Barcelona, Bellaterra, Spain +<br/><b>Toyota Research Institute, Los Altos, CA, USA</b></td><td>('1799820', 'Adrien Gaidon', 'adrien gaidon')<br/>('3407519', 'Yohann Cabon', 'yohann cabon')</td><td>{cesar.desouza, yohann.cabon}@europe.naverlabs.com, adrien.gaidon@tri.global, antonio@cvc.uab.es +</td></tr><tr><td>ceeb67bf53ffab1395c36f1141b516f893bada27</td><td>Face Alignment by Local Deep Descriptor Regression <br/><b>University of Maryland</b><br/><b>College Park, MD</b><br/><b>University of Maryland</b><br/><b>College Park, MD</b><br/><b>University of Maryland</b><br/><b>College Park, MD</b><br/><b>Rutgers University</b><br/>New Brunswick, NJ 08901 </td><td>('40080979', 'Amit Kumar', 'amit kumar')<br/>('26988560', 'Rajeev Ranjan', 'rajeev ranjan')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')</td><td>akumar14@umd.edu <br/>rranjan1@umd.edu <br/>rama@umiacs.umd.edu <br/>vishal.m.patel@rutgers.edu -</td></tr><tr><td>ce9a61bcba6decba72f91497085807bface02daf</td><td>Eigen-Harmonics Faces: Face Recognition under Generic Lighting +</td></tr><tr><td>ce032dae834f383125cdd852e7c1bc793d4c3ba3</td><td>Motion Interchange Patterns for Action +<br/>Recognition in Unconstrained Videos +<br/><b>The Weizmann Institute of Science, Israel</b><br/><b>Tel-Aviv University, Israel</b><br/><b>The Open University, Israel</b></td><td>('3294355', 'Orit Kliper-Gross', 'orit kliper-gross')<br/>('2916582', 'Yaron Gurovich', 'yaron gurovich')<br/>('1756099', 'Tal Hassner', 'tal hassner')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td></td></tr><tr><td>ce9e1dfa7705623bb67df3a91052062a0a0ca456</td><td>Deep Feature Interpolation for Image Content Changes +<br/>Kilian Weinberger1 +<br/><b>Cornell University</b><br/><b>George Washington University</b><br/>*Authors contributed equally +</td><td>('3222840', 'Paul Upchurch', 'paul upchurch')<br/>('1791337', 'Kavita Bala', 'kavita bala')</td><td></td></tr><tr><td>ce9a61bcba6decba72f91497085807bface02daf</td><td>Eigen-Harmonics Faces: Face Recognition under Generic Lighting <br/>1Graduate School, CAS, Beijing, China, 100080 <br/>2ICT-ISVISION Joint R&D Laboratory for Face Recognition, CAS, Beijing, China, 100080 <br/>Emails: {lyqing, sgshan, wgao}jdl.ac.cn @@ -30165,7 +38754,33 @@ <br/><b>Engineering, G.H.Raisoni College of Engineering</b><br/>Technology for Women, Nagpur, Maharashtra, India. </td><td>('2776196', 'Deepti Yadav', 'deepti yadav')</td><td></td></tr><tr><td>ce933821661a0139a329e6c8243e335bfa1022b1</td><td>Temporal Modeling Approaches for Large-scale <br/>Youtube-8M Video Understanding -<br/><b>Baidu IDL and Tsinghua University</b></td><td>('9921390', 'Fu Li', 'fu li')<br/>('2551285', 'Chuang Gan', 'chuang gan')<br/>('3025977', 'Xiao Liu', 'xiao liu')<br/>('38812373', 'Yunlong Bian', 'yunlong bian')<br/>('1716690', 'Xiang Long', 'xiang long')<br/>('2653177', 'Yandong Li', 'yandong li')<br/>('2027571', 'Zhichao Li', 'zhichao li')<br/>('1743129', 'Jie Zhou', 'jie zhou')<br/>('35247507', 'Shilei Wen', 'shilei wen')</td><td></td></tr><tr><td>e0dedb6fc4d370f4399bf7d67e234dc44deb4333</td><td>Supplementary Material: Multi-Task Video Captioning with Video and +<br/><b>Baidu IDL and Tsinghua University</b></td><td>('9921390', 'Fu Li', 'fu li')<br/>('2551285', 'Chuang Gan', 'chuang gan')<br/>('3025977', 'Xiao Liu', 'xiao liu')<br/>('38812373', 'Yunlong Bian', 'yunlong bian')<br/>('1716690', 'Xiang Long', 'xiang long')<br/>('2653177', 'Yandong Li', 'yandong li')<br/>('2027571', 'Zhichao Li', 'zhichao li')<br/>('1743129', 'Jie Zhou', 'jie zhou')<br/>('35247507', 'Shilei Wen', 'shilei wen')</td><td></td></tr><tr><td>e03bda45248b4169e2a20cb9124ae60440cad2de</td><td>Learning a Dictionary of Shape-Components in Visual Cortex: +<br/>Comparison with Neurons, Humans and Machines +<br/>by +<br/>Ing´enieur de l’Ecole Nationale Sup´erieure +<br/>des T´el´ecommunications de Bretagne, 2000 +<br/>and +<br/>MS, Universit´e de Rennes, 2000 +<br/>Submitted to the Department of Brain and Cognitive Sciences +<br/>in partial fulfillment of the requirements for the degree of +<br/>Doctor of Philosophy +<br/>at the +<br/><b>MASSACHUSETTS INSTITUTE OF TECHNOLOGY</b><br/>June 2006 +<br/><b>c(cid:13) Massachusetts Institute of Technology 2006. All rights reserved</b><br/>Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +<br/>Department of Brain and Cognitive Sciences +<br/>April 24, 2006 +<br/>Certified by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +<br/>Tomaso Poggio +<br/>Eugene McDermott Professor in the Brain Sciences and Human Behavior +<br/>Thesis Supervisor +<br/>Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . +<br/>Matt Wilson +<br/>Professor of Neurobiology and +<br/>Chairman, Department Graduate Committee +</td><td>('1981539', 'Thomas Serre', 'thomas serre')</td><td></td></tr><tr><td>e03e86ac61cfac9148b371d75ce81a55e8b332ca</td><td>Unsupervised Learning using Sequential +<br/>Verification for Action Recognition +<br/><b>cid:63)The Robotics Institute, Carnegie Mellon University</b><br/>†Facebook AI Research +</td><td>('1806773', 'Ishan Misra', 'ishan misra')<br/>('1709305', 'Martial Hebert', 'martial hebert')<br/>('1699161', 'C. Lawrence Zitnick', 'c. lawrence zitnick')</td><td></td></tr><tr><td>e0dedb6fc4d370f4399bf7d67e234dc44deb4333</td><td>Supplementary Material: Multi-Task Video Captioning with Video and <br/>Entailment Generation <br/>UNC Chapel Hill <br/>1 Experimental Setup @@ -30250,7 +38865,13 @@ <br/>to lower case and tokenize the sentences and <br/>remove punctuations. </td><td>('10721120', 'Ramakanth Pasunuru', 'ramakanth pasunuru')<br/>('7736730', 'Mohit Bansal', 'mohit bansal')</td><td>{ram, mbansal}@cs.unc.edu -</td></tr><tr><td>e0638e0628021712ac76e3472663ccc17bd8838c</td><td> VOL. 9, NO. 2, FEBRUARY 2014 ISSN 1819-6608 +</td></tr><tr><td>e096b11b3988441c0995c13742ad188a80f2b461</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>DeepProposals: Hunting Objects and Actions by Cascading +<br/>Deep Convolutional Layers +<br/>Van Gool +<br/>Received: date / Accepted: date +</td><td>('3060081', 'Amir Ghodrati', 'amir ghodrati')</td><td></td></tr><tr><td>e0638e0628021712ac76e3472663ccc17bd8838c</td><td> VOL. 9, NO. 2, FEBRUARY 2014 ISSN 1819-6608 <br/>ARPN Journal of Engineering and Applied Sciences <br/>©2006-2014 Asian Research Publishing Network (ARPN). All rights reserved. <br/>www.arpnjournals.com @@ -30273,18 +38894,221 @@ <br/>YangY1503@163.com (Y.Y.); wangy_neu@163.com (Y.W.) <br/>2 New York University Shanghai, 1555 Century Ave, Pudong, Shanghai 200122, China; wz723@nyu.edu <br/>* Correspondence: wangqimath@mail.neu.edu.cn; Tel.: +86-024-8368-7680 -</td></tr><tr><td>e0bfcf965b402f3f209f26ae20ee88bc4d0002ab</td><td>AI Thinking for Cloud Education Platform with Personalized Learning +</td></tr><tr><td>e01bb53b611c679141494f3ffe6f0b91953af658</td><td>FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors +<br/><b>Nanjing University of Science and Technology</b><br/>2Youtu Lab, Tencent +<br/><b>Michigan State University</b><br/><b>University of Adelaide</b><br/>Figure 1: Visual results of different super-resolution methods on scale factor 8. +</td><td>('50579509', 'Yu Chen', 'yu chen')<br/>('49499405', 'Jian Yang', 'jian yang')</td><td></td></tr><tr><td>e0bfcf965b402f3f209f26ae20ee88bc4d0002ab</td><td>AI Thinking for Cloud Education Platform with Personalized Learning <br/><b>University of Texas at San Antonio</b><br/><b>University of Texas at San Antonio</b><br/><b>University of Texas at San Antonio</b><br/><b>University of Texas at San Antonio</b><br/><b>University of Texas at San Antonio</b></td><td>('2055316', 'Paul Rad', 'paul rad')<br/>('2918902', 'Mehdi Roopaei', 'mehdi roopaei')<br/>('1716725', 'Nicole Beebe', 'nicole beebe')<br/>('9324267', 'Mehdi Shadaram', 'mehdi shadaram')<br/>('1839489', 'Yoris A. Au', 'yoris a. au')</td><td>Paul.rad@utsa.edu <br/> Mehdi.roopaei@utsa.edu <br/>Nicole.beebe@utsa.edu <br/>Mehdi.shadaram@utsa.edu <br/>Yoris.au@utsa.edu -</td></tr><tr><td>e0ed0e2d189ff73701ec72e167d44df4eb6e864d</td><td>Recognition of static and dynamic facial expressions: a study review +</td></tr><tr><td>e0939b4518a5ad649ba04194f74f3413c793f28e</td><td>Technical Report +<br/>UCAM-CL-TR-636 +<br/>ISSN 1476-2986 +<br/>Number 636 +<br/>Computer Laboratory +<br/>Mind-reading machines: +<br/>automated inference +<br/>of complex mental states +<br/>July 2005 +<br/>15 JJ Thomson Avenue +<br/>Cambridge CB3 0FD +<br/>United Kingdom +<br/>phone +44 1223 763500 +<br/>http://www.cl.cam.ac.uk/ +</td><td></td><td></td></tr><tr><td>e0ed0e2d189ff73701ec72e167d44df4eb6e864d</td><td>Recognition of static and dynamic facial expressions: a study review <br/>Estudos de Psicologia, 18(1), janeiro-março/2013, 125-130 -<br/><b>Federal University of Para ba</b></td><td>('39169435', 'Nelson Torro Alves', 'nelson torro alves')</td><td></td></tr><tr><td>e0765de5cabe7e287582532456d7f4815acd74c1</td><td></td><td></td><td></td></tr><tr><td>e013c650c7c6b480a1b692bedb663947cd9d260f</td><td>860 +<br/><b>Federal University of Para ba</b></td><td>('39169435', 'Nelson Torro Alves', 'nelson torro alves')</td><td></td></tr><tr><td>e00d391d7943561f5c7b772ab68e2bb6a85e64c4</td><td>Robust continuous clustering +<br/><b>University of Maryland, College Park, MD 20740; and bIntel Labs, Santa Clara, CA</b><br/><b>Edited by David L. Donoho, Stanford University, Stanford, CA, and approved August 7, 2017 (received for review January</b><br/>Clustering is a fundamental procedure in the analysis of scientific +<br/>data. It is used ubiquitously across the sciences. Despite decades +<br/>of research, existing clustering algorithms have limited effective- +<br/>ness in high dimensions and often require tuning parameters for +<br/>different domains and datasets. We present a clustering algo- +<br/>rithm that achieves high accuracy across multiple domains and +<br/>scales efficiently to high dimensions and large datasets. The pre- +<br/>sented algorithm optimizes a smooth continuous objective, which +<br/>is based on robust statistics and allows heavily mixed clusters to +<br/>be untangled. The continuous nature of the objective also allows +<br/>clustering to be integrated as a module in end-to-end feature +<br/>learning pipelines. We demonstrate this by extending the algo- +<br/>rithm to perform joint clustering and dimensionality reduction +<br/>by efficiently optimizing a continuous global objective. The pre- +<br/>sented approach is evaluated on large datasets of faces, hand- +<br/>written digits, objects, newswire articles, sensor readings from +<br/>the Space Shuttle, and protein expression levels. Our method +<br/>achieves high accuracy across all datasets, outperforming the best +<br/>prior algorithm by a factor of 3 in average rank. +<br/>clustering | data analysis | unsupervised learning +<br/>Clustering is one of the fundamental experimental procedures +<br/>in data analysis. It is used in virtually all natural and social +<br/>sciences and has played a central role in biology, astronomy, +<br/>psychology, medicine, and chemistry. Data-clustering algorithms +<br/>have been developed for more than half a century (1). Significant +<br/>advances in the last two decades include spectral clustering (2–4), +<br/>generalizations of classic center-based methods (5, 6), mixture +<br/>models (7, 8), mean shift (9), affinity propagation (10), subspace +<br/>clustering (11–13), nonparametric methods (14, 15), and feature +<br/>selection (16–20). +<br/>Despite these developments, no single algorithm has emerged +<br/>to displace the k-means scheme and its variants (21). This +<br/>is despite the known drawbacks of such center-based meth- +<br/><b>ods, including sensitivity to initialization, limited effectiveness in</b><br/>high-dimensional spaces, and the requirement that the number +<br/>of clusters be set in advance. The endurance of these methods +<br/>is in part due to their simplicity and in part due to difficulties +<br/>associated with some of the new techniques, such as additional +<br/>hyperparameters that need to be tuned, high computational cost, +<br/>and varying effectiveness across domains. Consequently, scien- +<br/>tists who analyze large high-dimensional datasets with unknown +<br/>distribution must maintain and apply multiple different cluster- +<br/>ing algorithms in the hope that one will succeed. Books have +<br/>been written to guide practitioners through the landscape of +<br/>data-clustering techniques (22). +<br/>We present a clustering algorithm that is fast, easy to use, and +<br/>effective in high dimensions. The algorithm optimizes a clear +<br/>continuous objective, using standard numerical methods that +<br/>scale to massive datasets. The number of clusters need not be +<br/>known in advance. +<br/>The operation of the algorithm can be understood by contrast- +<br/>ing it with other popular clustering techniques. In center-based +<br/>algorithms such as k-means (1, 24), a small set of putative cluster +<br/>centers is initialized from the data and then iteratively refined. In +<br/>affinity propagation (10), data points communicate over a graph +<br/>structure to elect a subset of the points as representatives. In the +<br/>presented algorithm, each data point has a dedicated representa- +<br/>tive, initially located at the data point. Over the course of the algo- +<br/>rithm, the representatives move and coalesce into easily separable +<br/>clusters. The progress of the algorithm is visualized in Fig. 1. +<br/>Our formulation is based on recent convex relaxations for clus- +<br/>tering (25, 26). However, our objective is deliberately not convex. +<br/>We use redescending robust estimators that allow even heavily +<br/>mixed clusters to be untangled by optimizing a single contin- +<br/>uous objective. Despite the nonconvexity of the objective, the +<br/>optimization can still be performed using standard linear least- +<br/>squares solvers, which are highly efficient and scalable. Since the +<br/>algorithm expresses clustering as optimization of a continuous +<br/>objective based on robust estimation, we call it robust continu- +<br/>ous clustering (RCC). +<br/>One of the characteristics of the presented formulation is that +<br/>clustering is reduced to optimization of a continuous objective. +<br/>This enables the integration of clustering in end-to-end fea- +<br/>ture learning pipelines. We demonstrate this by extending RCC +<br/>to perform joint clustering and dimensionality reduction. The +<br/>extended algorithm, called RCC-DR, learns an embedding of +<br/>the data into a low-dimensional space in which it is clustered. +<br/>Embedding and clustering are performed jointly, by an algorithm +<br/>that optimizes a clear global objective. +<br/>We evaluate RCC and RCC-DR on a large number of datasets +<br/>from a variety of domains. These include image datasets, docu- +<br/>ment datasets, a dataset of sensor readings from the Space Shut- +<br/>tle, and a dataset of protein expression levels in mice. Exper- +<br/>iments demonstrate that our method significantly outperforms +<br/>prior state-of-the-art techniques. RCC-DR is particularly robust +<br/>across datasets from different domains, outperforming the best +<br/>prior algorithm by a factor of 3 in average rank. +<br/>Formulation +<br/>We consider the problem of clustering a set of n data points. +<br/>The input is denoted by X = [x1, x2, . . . , xn ], where xi ∈ RD. +<br/>Our approach operates on a set of representatives U = +<br/>[u1, u2, . . . , un ], where ui ∈ RD. The representatives U are ini- +<br/>tialized at the corresponding data points X. The optimization +<br/>operates on the representation U, which coalesces to reveal the +<br/>cluster structure latent in the data. Thus, the number of clusters +<br/>Significance +<br/>Clustering is a fundamental experimental procedure in data +<br/>analysis. It is used in virtually all natural and social sciences +<br/>and has played a central role in biology, astronomy, psychol- +<br/>ogy, medicine, and chemistry. Despite the importance and +<br/>ubiquity of clustering, existing algorithms suffer from a vari- +<br/>ety of drawbacks and no universal solution has emerged. We +<br/>present a clustering algorithm that reliably achieves high accu- +<br/>racy across domains, handles high data dimensionality, and +<br/>scales to large datasets. The algorithm optimizes a smooth +<br/>global objective, using efficient numerical methods. Experi- +<br/>ments demonstrate that our method outperforms state-of- +<br/>the-art clustering algorithms by significant factors in multiple +<br/>domains. +<br/>Author contributions: S.A.S. and V.K. designed research, performed research, analyzed +<br/>data, and wrote the paper. +<br/>The authors declare no conflict of interest. +<br/>This article is a PNAS Direct Submission. +<br/>Freely available online through the PNAS open access option. +<br/>This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. +<br/>1073/pnas.1700770114/-/DCSupplemental. +<br/>9814–9819 | PNAS | September 12, 2017 | vol. 114 | no. 37 +<br/>www.pnas.org/cgi/doi/10.1073/pnas.1700770114 +</td><td>('49485254', 'Sohil Atul Shah', 'sohil atul shah')<br/>('1770944', 'Vladlen Koltun', 'vladlen koltun')</td><td>1To whom correspondence should be addressed. Email: sohilas@umd.edu. +</td></tr><tr><td>e0765de5cabe7e287582532456d7f4815acd74c1</td><td></td><td></td><td></td></tr><tr><td>e065a2cb4534492ccf46d0afc81b9ad8b420c5ec</td><td>SFace: An Efficient Network for Face Detection +<br/>in Large Scale Variations +<br/><b>College of Software, Beihang University</b><br/>Megvii Inc. (Face++)† +</td><td>('38504661', 'Jianfeng Wang', 'jianfeng wang')<br/>('48009795', 'Ye Yuan', 'ye yuan')<br/>('2789329', 'Boxun Li', 'boxun li')<br/>('2352391', 'Gang Yu', 'gang yu')<br/>('2017810', 'Sun Jian', 'sun jian')</td><td>{wjfwzzc}@buaa.edu.cn, {yuanye,liboxun,yugang,sunjian}@megvii.com +</td></tr><tr><td>e00241f00fb31c660df6c6f129ca38370e6eadb3</td><td>What have we learned from deep representations for action recognition? +<br/>TU Graz +<br/>TU Graz +<br/><b>York University, Toronto</b><br/><b>University of Oxford</b></td><td>('2322150', 'Christoph Feichtenhofer', 'christoph feichtenhofer')<br/>('1718587', 'Axel Pinz', 'axel pinz')<br/>('1709096', 'Richard P. Wildes', 'richard p. wildes')<br/>('1688869', 'Andrew Zisserman', 'andrew zisserman')</td><td>feichtenhofer@tugraz.at +<br/>axel.pinz@tugraz.at +<br/>wildes@cse.yorku.ca +<br/>az@robots.ox.ac.uk +</td></tr><tr><td>e013c650c7c6b480a1b692bedb663947cd9d260f</td><td>860 <br/>Robust Image Analysis With Sparse Representation <br/>on Quantized Visual Features -</td><td>('8180253', 'Bing-Kun Bao', 'bing-kun bao')<br/>('36601906', 'Guangyu Zhu', 'guangyu zhu')<br/>('38203359', 'Jialie Shen', 'jialie shen')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>e0dc6f1b740479098c1d397a7bc0962991b5e294</td><td>快速人脸检测技术综述 +</td><td>('8180253', 'Bing-Kun Bao', 'bing-kun bao')<br/>('36601906', 'Guangyu Zhu', 'guangyu zhu')<br/>('38203359', 'Jialie Shen', 'jialie shen')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>e0244a8356b57a5721c101ead351924bcfb2eef4</td><td>Journal of Experimental Psychology: General +<br/>2017, Vol. 146, No. 10, 1379 –1401 +<br/>0096-3445/17/$12.00 +<br/>© 2017 American Psychological Association +<br/>http://dx.doi.org/10.1037/xge0000292 +<br/>Power as an Emotional Liability: Implications for Perceived Authenticity +<br/>and Trust After a Transgression +<br/><b>University of Southern California</b><br/><b>Webster University</b><br/><b>University of Haifa</b><br/>Alexandra Mislin +<br/><b>American University</b><br/><b>University of Washington, Seattle</b><br/>Gerben A. van Kleef +<br/><b>University of Amsterdam</b><br/>People may express a variety of emotions after committing a transgression. Through 6 empirical studies and +<br/>a meta-analysis, we investigate how the perceived authenticity of such emotional displays and resulting levels +<br/>of trust are shaped by the transgressor’s power. Past findings suggest that individuals with power tend to be +<br/>more authentic because they have more freedom to act on the basis of their own personal inclinations. Yet, +<br/>our findings reveal that (a) a transgressor’s display of emotion is perceived to be less authentic when that +<br/>party’s power is high rather than low; (b) this perception of emotional authenticity, in turn, directly influences +<br/>(and mediates) the level of trust in that party; and (c) perceivers ultimately exert less effort when asked to make +<br/>a case for leniency toward high rather than low-power transgressors. This tendency to discount the emotional +<br/>authenticity of the powerful was found to arise from power increasing the transgressor’s perceived level of +<br/>emotional control and strategic motivation, rather than a host of alternative mechanisms. These results were +<br/>also found across different types of emotions (sadness, anger, fear, happiness, and neutral), expressive +<br/>modalities, operationalizations of the transgression, and participant populations. Altogether, our findings +<br/>demonstrate that besides the wealth of benefits power can afford, it also comes with a notable downside. The +<br/>findings, furthermore, extend past research on perceived emotional authenticity, which has focused on how +<br/>and when specific emotions are expressed, by revealing how this perception can depend on considerations that +<br/>have nothing to do with the expression itself. +<br/>Keywords: trust, emotion, power, authenticity, perception +<br/>Supplemental materials: http://dx.doi.org/10.1037/xge0000292.supp +<br/>Research suggests that those who attain positions of power tend +<br/>to be more emotionally skilled (Côté, Lopes, Salovey, & Miners, +<br/>2010; George, 2000). Indeed, it is the very possession of such +<br/>skills that has been suggested to help these parties attain and +<br/>succeed in leadership positions (e.g., Lewis, 2000; Rubin, Munz, +<br/><b>School of Business, University of Southern California; Alexandra Mislin</b><br/>Department of Management, Kogod School of Business, American Uni- +<br/><b>chael G. Foster School of Business, University of Washington, Seattle</b><br/><b>A. van Kleef, University of Amsterdam</b><br/>This research was supported in part by a faculty research grant from +<br/><b>Webster University</b><br/>Correspondence concerning this article should be addressed to Peter H. +<br/>Kim, Marshall School of Business, Department of Management and Or- +<br/><b>ganization, University of Southern California, Hoffman Hall 515, Los</b><br/>1379 +<br/>& Bommer, 2005). Yet, this tendency for the powerful to be +<br/>emotionally skilled may not necessarily prove beneficial, to the +<br/>extent that those evaluating such powerful individuals subscribe to +<br/>this notion as well, and may even undermine the effectiveness of +<br/>high-power parties’ emotional expressions when they might need +<br/>them most. In particular, through six empirical studies and a +<br/>meta-analysis, we investigate the possibility that perceivers’ gen- +<br/>eral beliefs about the powerful as emotionally skilled would lead +<br/>perceivers to discount the authenticity of the emotions the power- +<br/>ful express, and that this would ultimately impair the effectiveness +<br/>of those emotional displays for addressing a transgression. +<br/>Theoretical Background +<br/>Power, which has been defined as an individual’s capacity to +<br/>modify others’ states by providing or withholding resources or +<br/>administering punishments (Keltner, Gruenfeld, & Anderson, +<br/>2003), has been widely recognized to offer numerous benefits to +<br/><b>those who possess it, including the ability to act based on one s</b><br/>own inclinations, perceive greater choice, and obtain greater ben- +<br/>efits from both work and nonwork interactions (e.g., Galinsky, +</td><td>('34770901', 'Peter H. Kim', 'peter h. kim')<br/>('47847686', 'Ece Tuncel', 'ece tuncel')<br/>('3198839', 'Arik Cheshin', 'arik cheshin')<br/>('50222018', 'Ryan Fehr', 'ryan fehr')<br/>('34770901', 'Peter H. Kim', 'peter h. kim')<br/>('47847686', 'Ece Tuncel', 'ece tuncel')<br/>('50222018', 'Ryan Fehr', 'ryan fehr')<br/>('3198839', 'Arik Cheshin', 'arik cheshin')</td><td>Angeles, CA 90089-1421. E-mail: kimpeter@usc.edu +</td></tr><tr><td>e0dc6f1b740479098c1d397a7bc0962991b5e294</td><td>快速人脸检测技术综述 <br/>李月敏 1 陈杰 2 高文 1,2,3 尹宝才 1 <br/>1(北京工业大学计算机学院多媒体与智能软件技术实验室 北京 100022) <br/>2(哈尔滨工业大学计算机科学与技术学院 哈尔滨 150001) @@ -30344,7 +39168,10 @@ <br/><b>University of Pennsylvania</b><br/>Philadelphia, PA 19104 </td><td>('2720935', 'Jihun Ham', 'jihun ham')<br/>('1732066', 'Daniel D. Lee', 'daniel d. lee')</td><td>jhham@seas.upenn.edu <br/>ddlee@seas.upenn.edu -</td></tr><tr><td>46e86cdb674440f61b6658ef3e84fea95ea51fb4</td><td></td><td></td><td></td></tr><tr><td>46b7ee97d7dfbd61cc3745e8dfdd81a15ab5c1d4</td><td>3D FACIAL GEOMETRIC FEATURES FOR CONSTRAINED LOCAL MODEL +</td></tr><tr><td>46e86cdb674440f61b6658ef3e84fea95ea51fb4</td><td></td><td></td><td></td></tr><tr><td>46f2611dc4a9302e0ac00a79456fa162461a8c80</td><td>for Action Classification +<br/><b>ESAT-PSI, KU Leuven, 2CV:HCI, KIT, Karlsruhe, 3University of Bonn, 4Sensifai</b></td><td>('3310120', 'Ali Diba', 'ali diba')<br/>('3169187', 'Mohsen Fayyaz', 'mohsen fayyaz')<br/>('50633941', 'Vivek Sharma', 'vivek sharma')<br/>('2946643', 'Juergen Gall', 'juergen gall')<br/>('1681236', 'Luc Van Gool', 'luc van gool')</td><td>1{firstname.lastname}@kuleuven.be, 2{firstname.lastname}@kit.edu, +<br/>3{lastname}@iai.uni-bonn.de, 4{firstname.lastname}@sensifai.com +</td></tr><tr><td>46b7ee97d7dfbd61cc3745e8dfdd81a15ab5c1d4</td><td>3D FACIAL GEOMETRIC FEATURES FOR CONSTRAINED LOCAL MODEL <br/><b>cid:2) Imperial College London, United Kingdom</b><br/><b>University of Twente, EEMCS, Netherlands</b></td><td>('1694605', 'Maja Pantic', 'maja pantic')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('3183108', 'Akshay Asthana', 'akshay asthana')<br/>('1902288', 'Shiyang Cheng', 'shiyang cheng')</td><td>{shiyang.cheng11, s.zafeiriou, a.asthana, m.pantic}@imperial.ac.uk </td></tr><tr><td>46ae4d593d89b72e1a479a91806c39095cd96615</td><td>A CONDITIONAL RANDOM FIELD APPROACH FOR FACE IDENTIFICATION IN <br/>BROADCAST NEWS USING OVERLAID TEXT @@ -30389,7 +39216,10 @@ <br/>{mtsezgin|oaltiok15|ysahillioglu}@ku.edu.tr </td></tr><tr><td>46c87fded035c97f35bb991fdec45634d15f9df2</td><td>Spatial-Aware Object Embeddings for Zero-Shot Localization <br/>and Classification of Actions -<br/><b>University of Amsterdam</b></td><td>('2606260', 'Pascal Mettes', 'pascal mettes')</td><td></td></tr><tr><td>46f32991ebb6235509a6d297928947a8c483f29e</td><td>In Proc. IEEE Computer Vision and Pattern Recognition (CVPR), Madison (WI), June 2003 +<br/><b>University of Amsterdam</b></td><td>('2606260', 'Pascal Mettes', 'pascal mettes')</td><td></td></tr><tr><td>46e72046a9bb2d4982d60bcf5c63dbc622717f0f</td><td>Learning Discriminative Features with Class Encoder +<br/>Center for Biometrics and Security Research & National Laboratory of Pattern Recognition +<br/><b>Institute of Automation, Chinese Academy of Sciences</b><br/><b>University of Chinese Academy of Science</b></td><td>('1704812', 'Hailin Shi', 'hailin shi')<br/>('8362374', 'Xiangyu Zhu', 'xiangyu zhu')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('40397682', 'Shengcai Liao', 'shengcai liao')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td>{hailin.shi, xiangyu.zhu, zlei, scliao, szli}@nlpr.ia.ac.cn +</td></tr><tr><td>46f32991ebb6235509a6d297928947a8c483f29e</td><td>In Proc. IEEE Computer Vision and Pattern Recognition (CVPR), Madison (WI), June 2003 <br/>Recognizing Expression Variant Faces <br/>from a Single Sample Image per Class <br/>Aleix M. Mart(cid:19)(cid:16)nez @@ -30402,7 +39232,18 @@ <br/>1P.G. Student, Department of Computer Engineering, MCERC, Nashik (M.S.), India. <br/>2Associate Professor, Department of Computer Engineering, <br/>MCERC, Nashik (M.S.), India -</td><td>('40075681', 'Shraddha S. Shinde', 'shraddha s. shinde')<br/>('2590072', 'Anagha P. Khedkar', 'anagha p. khedkar')</td><td></td></tr><tr><td>469ee1b00f7bbfe17c698ccded6f48be398f2a44</td><td>MIT International Journal of Computer Science and Information Technology, Vol. 4, No. 2, August 2014, pp. 82-88 +</td><td>('40075681', 'Shraddha S. Shinde', 'shraddha s. shinde')<br/>('2590072', 'Anagha P. Khedkar', 'anagha p. khedkar')</td><td></td></tr><tr><td>4641986af5fc8836b2c883ea1a65278d58fe4577</td><td>Scene Graph Generation by Iterative Message Passing +<br/><b>Stanford University</b><br/><b>Stanford University</b></td><td>('2068265', 'Danfei Xu', 'danfei xu')</td><td>{danfei, yukez, chrischoy, feifeili}@cs.stanford.edu +</td></tr><tr><td>464b3f0824fc1c3a9eaf721ce2db1b7dfe7cb05a</td><td>Deep Adaptive Temporal Pooling for Activity Recognition +<br/><b>Singapore University of Technology and Design</b><br/><b>Singapore University of Technology and Design</b><br/>Singapore, Singapore +<br/>Singapore, Singapore +<br/><b>Institute for Infocomm Research</b><br/>Singapore, Singapore +<br/><b>Keele University</b><br/>Keele, Staffordshire, United Kingdom +</td><td>('1729827', 'Ngai-Man Cheung', 'ngai-man cheung')<br/>('2527741', 'Sibo Song', 'sibo song')<br/>('1802086', 'Vijay Chandrasekhar', 'vijay chandrasekhar')<br/>('1709001', 'Bappaditya Mandal', 'bappaditya mandal')</td><td>ngaiman_cheung@sutd.edu.sg +<br/>sibo_song@mymail.sutd.edu.sg +<br/>vijay@i2r.a-star.edu.sg +<br/>b.mandal@keele.ac.uk +</td></tr><tr><td>469ee1b00f7bbfe17c698ccded6f48be398f2a44</td><td>MIT International Journal of Computer Science and Information Technology, Vol. 4, No. 2, August 2014, pp. 82-88 <br/>ISSN 2230-7621©MIT Publications <br/>82 <br/>SURVEy: Techniques for @@ -30448,6 +39289,9 @@ </td><td>('40557104', 'Lu Xu', 'lu xu')<br/>('2697879', 'Jinhai Xiang', 'jinhai xiang')<br/>('1982703', 'Xiaohui Yuan', 'xiaohui yuan')</td><td>Email: xulu coi@webmail.hzau.edu.cn <br/>Email: jimmy xiang@mail.hzau.edu.cn <br/>Email: Xiaohui.Yuan@unt.edu +</td></tr><tr><td>2c424f21607ff6c92e640bfe3da9ff105c08fac4</td><td>Learning Structured Output Representation +<br/>using Deep Conditional Generative Models +<br/><b>NEC Laboratories America, Inc</b><br/><b>University of Michigan, Ann Arbor</b></td><td>('1729571', 'Kihyuk Sohn', 'kihyuk sohn')<br/>('3084614', 'Xinchen Yan', 'xinchen yan')<br/>('1697141', 'Honglak Lee', 'honglak lee')</td><td>ksohn@nec-labs.com, {xcyan,honglak}@umich.edu </td></tr><tr><td>2c258eec8e4da9e65018f116b237f7e2e0b2ad17</td><td>Deep Quantization: Encoding Convolutional Activations <br/>with Deep Generative Model ∗ <br/><b>University of Science and Technology of China, Hefei, China</b><br/>Microsoft Research, Beijing, China @@ -30456,7 +39300,12 @@ <br/>Seattle, Washington, May 26-30, 2015 <br/>978-1-4799-6922-7/15/$31.00 ©2015 IEEE <br/>3039 -</td><td></td><td></td></tr><tr><td>2c61a9e26557dd0fe824909adeadf22a6a0d86b0</td><td></td><td></td><td></td></tr><tr><td>2c34bf897bad780e124d5539099405c28f3279ac</td><td>Robust Face Recognition via Block Sparse Bayesian Learning +</td><td></td><td></td></tr><tr><td>2c61a9e26557dd0fe824909adeadf22a6a0d86b0</td><td></td><td></td><td></td></tr><tr><td>2c93c8da5dfe5c50119949881f90ac5a0a4f39fe</td><td>Advanced local motion patterns for macro and micro facial +<br/>expression recognition +<br/>B. Allaerta,∗, IM. Bilascoa, C. Djerabaa +<br/>aUniv. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - +<br/>Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France +</td><td></td><td></td></tr><tr><td>2c34bf897bad780e124d5539099405c28f3279ac</td><td>Robust Face Recognition via Block Sparse Bayesian Learning <br/><b>School of Financial Information Engineering, Southwestern University of Finance and Economics, Chengdu</b><br/>China <br/><b>Institute of Chinese Payment System, Southwestern University of Finance and Economics, Chengdu 610074, China</b><br/><b>University of California at San Diego, La Jolla, CA</b><br/>USA <br/><b>Samsung RandD Institute America - Dallas, 1301 East Lookout Drive, Richardson, TX 75082, USA</b></td><td>('2775350', 'Taiyong Li', 'taiyong li')<br/>('1791667', 'Zhilin Zhang', 'zhilin zhang')</td><td></td></tr><tr><td>2c203050a6cca0a0bff80e574bda16a8c46fe9c2</td><td>Discriminative Deep Hashing for Scalable Face Image Retrieval @@ -30502,6 +39351,12 @@ </td><td>('1727735', 'Changhan Park', 'changhan park')<br/>('1684329', 'Joonki Paik', 'joonki paik')</td><td></td></tr><tr><td>2c3430e0cbe6c8d7be3316a88a5c13a50e90021d</td><td>Multi-feature Spectral Clustering with Minimax Optimization <br/>School of Electrical and Electronic Engineering <br/><b>Nanyang Technological University, Singapore</b></td><td>('19172541', 'Hongxing Wang', 'hongxing wang')<br/>('1764228', 'Chaoqun Weng', 'chaoqun weng')<br/>('34316743', 'Junsong Yuan', 'junsong yuan')</td><td>{hwang8, weng0018}@e.ntu.edu.sg, jsyuan@ntu.edu.sg +</td></tr><tr><td>2cac8ab4088e2bdd32dcb276b86459427355085c</td><td>A Face-to-Face Neural Conversation Model +<br/>Hang Chu1 +<br/><b>University of Toronto 2Vector Institute</b></td><td>('46598920', 'Daiqing Li', 'daiqing li')</td><td>{chuhang1122, daiqing, fidler}@cs.toronto.edu +</td></tr><tr><td>2cde051e04569496fb525d7f1b1e5ce6364c8b21</td><td>Sparse 3D convolutional neural networks +<br/><b>University of Warwick</b><br/>August 26, 2015 +</td><td>('39294240', 'Ben Graham', 'ben graham')</td><td>b.graham@warwick.ac.uk </td></tr><tr><td>2c2786ea6386f2d611fc9dbf209362699b104f83</td><td></td><td>('31914125', 'Mohammad Shahidul Islam', 'mohammad shahidul islam')</td><td></td></tr><tr><td>2c92839418a64728438c351a42f6dc5ad0c6e686</td><td>Pose-Aware Face Recognition in the Wild <br/>Prem Natarajan2 <br/><b>USC Institute for Robotics and Intelligent Systems (IRIS), Los Angeles, CA</b><br/>G´erard Medioni1 @@ -30564,7 +39419,11 @@ <br/>redistribution to servers or lists, or to reuse any copyrighted <br/>component of this work in other works must be obtained from <br/>the IEEE. -</td><td></td><td></td></tr><tr><td>2cdc40f20b70ca44d9fd8e7716080ee05ca7924a</td><td>Real-time Convolutional Neural Networks for +</td><td></td><td></td></tr><tr><td>2c1ffb0feea5f707c890347d2c2882be0494a67a</td><td>Learning to learn high capacity generative models from few examples +<br/>The Variational Homoencoder: +<br/>Tommi Jaakkola1 +<br/><b>Massachusetts Institute of Technology</b><br/>2MIT-IBM Watson AI Lab +</td><td>('51152627', 'Luke B. Hewitt', 'luke b. hewitt')<br/>('51150953', 'Maxwell I. Nye', 'maxwell i. nye')<br/>('3071104', 'Andreea Gane', 'andreea gane')<br/>('1763295', 'Joshua B. Tenenbaum', 'joshua b. tenenbaum')</td><td></td></tr><tr><td>2cdc40f20b70ca44d9fd8e7716080ee05ca7924a</td><td>Real-time Convolutional Neural Networks for <br/>Emotion and Gender Classification <br/>Hochschule Bonn-Rhein-Sieg <br/>Sankt Augustin Germany @@ -30710,10 +39569,23 @@ <br/>was used as the distance measure. <br/>Texture information should be used to achieve state <br/>of the art recognition results. -<br/>FaceCamera1Camera2SamplePoint </td><td>('1994157', 'Brian Amberg', 'brian amberg')<br/>('1745076', 'Andrew Blake', 'andrew blake')<br/>('3293655', 'Sami Romdhani', 'sami romdhani')<br/>('1687079', 'Thomas Vetter', 'thomas vetter')</td><td></td></tr><tr><td>2c8f24f859bbbc4193d4d83645ef467bcf25adc2</td><td>845 +<br/>FaceCamera1Camera2SamplePoint </td><td>('1994157', 'Brian Amberg', 'brian amberg')<br/>('1745076', 'Andrew Blake', 'andrew blake')<br/>('3293655', 'Sami Romdhani', 'sami romdhani')<br/>('1687079', 'Thomas Vetter', 'thomas vetter')</td><td></td></tr><tr><td>2c5d1e0719f3ad7f66e1763685ae536806f0c23b</td><td>AENet: Learning Deep Audio Features for Video +<br/>Analysis +</td><td>('47893464', 'Naoya Takahashi', 'naoya takahashi')<br/>('3037160', 'Michael Gygli', 'michael gygli')<br/>('7329802', 'Luc van Gool', 'luc van gool')</td><td></td></tr><tr><td>2c8f24f859bbbc4193d4d83645ef467bcf25adc2</td><td>845 <br/>Classification in the Presence of <br/>Label Noise: a Survey -</td><td>('1786603', 'Benoît Frénay', 'benoît frénay')<br/>('1782629', 'Michel Verleysen', 'michel verleysen')</td><td></td></tr><tr><td>2ca43325a5dbde91af90bf850b83b0984587b3cc</td><td>For Your Eyes Only – Biometric Protection of PDF Documents +</td><td>('1786603', 'Benoît Frénay', 'benoît frénay')<br/>('1782629', 'Michel Verleysen', 'michel verleysen')</td><td></td></tr><tr><td>2c1f8ddbfbb224271253a27fed0c2425599dfe47</td><td>Understanding and Comparing Deep Neural Networks +<br/>for Age and Gender Classification +<br/><b>Fraunhofer Heinrich Hertz Institute</b><br/><b>Singapore University of Technology and Design</b><br/>10587 Berlin, Germany +<br/>Klaus-Robert M¨uller +<br/><b>Berlin Institute of Technology</b><br/>10623 Berlin, Germany +<br/>Singapore 487372, Singapore +<br/><b>Fraunhofer Heinrich Hertz Institute</b><br/>10587 Berlin, Germany +</td><td>('3633358', 'Sebastian Lapuschkin', 'sebastian lapuschkin')<br/>('40344011', 'Alexander Binder', 'alexander binder')<br/>('1699054', 'Wojciech Samek', 'wojciech samek')</td><td>sebastian.lapuschkin@hhi.fraunhofer.de +<br/>alexander binder@sutd.edu.sg +<br/>klaus-robert.mueller@tu-berlin.de +<br/>wojciech.samek@hhi.fraunhofer.de +</td></tr><tr><td>2ca43325a5dbde91af90bf850b83b0984587b3cc</td><td>For Your Eyes Only – Biometric Protection of PDF Documents <br/><b>Faculty of ETI, Gdansk University of Technology, Gdansk, Poland</b></td><td>('2026734', 'J. Siciarek', 'j. siciarek')</td><td></td></tr><tr><td>2cfc28a96b57e0817cc9624a5d553b3aafba56f3</td><td>P2F2: Privacy-Preserving Face Finder <br/><b>New Jersey Institute of Technology</b></td><td>('9037517', 'Nora Almalki', 'nora almalki')<br/>('1692516', 'Reza Curtmola', 'reza curtmola')<br/>('34645435', 'Xiaoning Ding', 'xiaoning ding')<br/>('1690806', 'Cristian Borcea', 'cristian borcea')</td><td>Email: {naa34, crix, xiaoning.ding, narain.gehani, borcea}@njit.edu </td></tr><tr><td>2cdd5b50a67e4615cb0892beaac12664ec53b81f</td><td>To appear in ACM TOG 33(6). @@ -30735,9 +39607,14 @@ </td></tr><tr><td>2cdde47c27a8ecd391cbb6b2dea64b73282c7491</td><td>ORDER-AWARE CONVOLUTIONAL POOLING FOR VIDEO BASED ACTION RECOGNITION <br/>Order-aware Convolutional Pooling for Video Based <br/>Action Recognition -</td><td>('1722767', 'Peng Wang', 'peng wang')<br/>('2161037', 'Lingqiao Liu', 'lingqiao liu')<br/>('1780381', 'Chunhua Shen', 'chunhua shen')<br/>('1724393', 'Heng Tao Shen', 'heng tao shen')</td><td></td></tr><tr><td>2c7c3a74da960cc76c00965bd3e343958464da45</td><td></td><td></td><td></td></tr><tr><td>2cf5f2091f9c2d9ab97086756c47cd11522a6ef3</td><td>MPIIGaze: Real-World Dataset and Deep +</td><td>('1722767', 'Peng Wang', 'peng wang')<br/>('2161037', 'Lingqiao Liu', 'lingqiao liu')<br/>('1780381', 'Chunhua Shen', 'chunhua shen')<br/>('1724393', 'Heng Tao Shen', 'heng tao shen')</td><td></td></tr><tr><td>2c62b9e64aeddf12f9d399b43baaefbca8e11148</td><td>Evaluation of Dense 3D Reconstruction from 2D Face Images in the Wild +<br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK</b><br/><b>Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK</b><br/><b>School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China</b><br/><b>Biometrics Research Lab, College of Computer Science, Sichuan University, Chengdu 610065, China</b><br/><b>Image Understanding and Interactive Robotics, Reutlingen University, 72762 Reutlingen, Germany</b></td><td>('2976854', 'Zhen-Hua Feng', 'zhen-hua feng')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('7345195', 'Qijun Zhao', 'qijun zhao')</td><td>{z.feng, j.kittler, p.koppen}@surrey.ac.uk, patrikhuber@gmail.com, +<br/>wu_xiaojun@jiangnan.edu.cn, p.j.b.hancock@stir.ac.uk, qjzhao@scu.edu.cn +</td></tr><tr><td>2c7c3a74da960cc76c00965bd3e343958464da45</td><td></td><td></td><td></td></tr><tr><td>2cf5f2091f9c2d9ab97086756c47cd11522a6ef3</td><td>MPIIGaze: Real-World Dataset and Deep <br/>Appearance-Based Gaze Estimation -</td><td>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('1751242', 'Yusuke Sugano', 'yusuke sugano')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td></td></tr><tr><td>2c17d36bab56083293456fe14ceff5497cc97d75</td><td>Unconstrained Face Alignment via Cascaded Compositional Learning +</td><td>('2520795', 'Xucong Zhang', 'xucong zhang')<br/>('1751242', 'Yusuke Sugano', 'yusuke sugano')<br/>('1739548', 'Mario Fritz', 'mario fritz')<br/>('3194727', 'Andreas Bulling', 'andreas bulling')</td><td></td></tr><tr><td>2c19d3d35ef7062061b9e16d040cebd7e45f281d</td><td>End-to-end Video-level Representation Learning for Action Recognition +<br/><b>Institute of Automation, Chinese Academy of Sciences (CASIA</b><br/><b>University of Chinese Academy of Sciences (UCAS</b></td><td>('1696573', 'Jiagang Zhu', 'jiagang zhu')<br/>('1726367', 'Wei Zou', 'wei zou')<br/>('48147901', 'Zheng Zhu', 'zheng zhu')</td><td>{zhujiagang2015, wei.zou}@ia.ac.cn, zhuzheng14@mails.ucas.ac.cn +</td></tr><tr><td>2c17d36bab56083293456fe14ceff5497cc97d75</td><td>Unconstrained Face Alignment via Cascaded Compositional Learning <br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b><br/>2SenseTime Group Limited </td><td>('2226254', 'Shizhan Zhu', 'shizhan zhu')<br/>('40475617', 'Cheng Li', 'cheng li')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>zs014@ie.cuhk.edu.hk, chengli@sensetime.com, ccloy@ie.cuhk.edu.hk, xtang@ie.cuhk.edu.hk </td></tr><tr><td>2c4b96f6c1a520e75eb37c6ee8b844332bc0435c</td><td>Automatic Emotion Recognition in Robot-Children Interaction for ASD @@ -30769,7 +39646,14 @@ </td><td>('3190846', 'Arnaud Dapogny', 'arnaud dapogny')<br/>('2521061', 'Kevin Bailly', 'kevin bailly')<br/>('1701986', 'Séverine Dubuisson', 'séverine dubuisson')</td><td>arnaud.dapogny@isir.upmc.fr <br/>kevin.bailly@isir.upmc.fr <br/>severine.dubuisson@isir.upmc.fr -</td></tr><tr><td>795ea140df2c3d29753f40ccc4952ef24f46576c</td><td></td><td></td><td></td></tr><tr><td>79b669abf65c2ca323098cf3f19fa7bdd837ff31</td><td> Deakin Research Online +</td></tr><tr><td>79f6a8f777a11fd626185ab549079236629431ac</td><td>Copyright +<br/>by +<br/>2013 +</td><td>('35788904', 'Sung Ju Hwang', 'sung ju hwang')</td><td></td></tr><tr><td>795ea140df2c3d29753f40ccc4952ef24f46576c</td><td></td><td></td><td></td></tr><tr><td>79dc84a3bf76f1cb983902e2591d913cee5bdb0e</td><td></td><td></td><td></td></tr><tr><td>79744fc71bea58d2e1918c9e254b10047472bd76</td><td>Disentangling 3D Pose in A Dendritic CNN +<br/>for Unconstrained 2D Face Alignment +<br/>Department of Electrical and Computer Engineering, CFAR and UMIACS +<br/><b>University of Maryland-College Park, USA</b></td><td>('50333013', 'Amit Kumar', 'amit kumar')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>akumar14@umiacs.umd.edu, rama@umiacs.umd.edu +</td></tr><tr><td>79b669abf65c2ca323098cf3f19fa7bdd837ff31</td><td> Deakin Research Online <br/>This is the published version: <br/>Rana, Santu, Liu, Wanquan, Lazarescu, Mihai and Venkatesh, Svetha 2008, Efficient tensor <br/>based face recognition, in ICPR 2008 : Proceedings of the 19th International Conference on @@ -30787,9 +39671,10 @@ <br/>Improving visual recognition with games <br/>Preece <br/>School of Information -<br/><b>University of Maryland</b><br/><b>College Park, United States</b></td><td>('6519022', 'Darcy Lewis', 'darcy lewis')<br/>('2662457', 'Dana Rotman', 'dana rotman')</td><td></td></tr><tr><td>79dd787b2877cf9ce08762d702589543bda373be</td><td>Face Detection Using SURF Cascade +<br/><b>University of Maryland</b><br/><b>College Park, United States</b></td><td>('6519022', 'Darcy Lewis', 'darcy lewis')<br/>('2662457', 'Dana Rotman', 'dana rotman')</td><td></td></tr><tr><td>79c3a7131c6c176b02b97d368cd0cd0bc713ff7e</td><td></td><td></td><td></td></tr><tr><td>79dd787b2877cf9ce08762d702589543bda373be</td><td>Face Detection Using SURF Cascade <br/>Intel Labs China -</td><td>('35423937', 'Jianguo Li', 'jianguo li')<br/>('40279370', 'Tao Wang', 'tao wang')<br/>('2470865', 'Yimin Zhang', 'yimin zhang')</td><td></td></tr><tr><td>7966146d72f9953330556baa04be746d18702047</td><td>Harnessing Human Manipulation +</td><td>('35423937', 'Jianguo Li', 'jianguo li')<br/>('40279370', 'Tao Wang', 'tao wang')<br/>('2470865', 'Yimin Zhang', 'yimin zhang')</td><td></td></tr><tr><td>799c02a3cde2c0805ea728eb778161499017396b</td><td>PersonRank: Detecting Important People in Images +<br/><b>School of Electronics and Information Technology, Sun Yat-Sen University, GuangZhou, China</b><br/><b>School of Data and Computer Science, Sun Yat-Sen University, GuangZhou, China</b></td><td>('9186191', 'Benchao Li', 'benchao li')<br/>('3333315', 'Wei-Shi Zheng', 'wei-shi zheng')</td><td></td></tr><tr><td>7966146d72f9953330556baa04be746d18702047</td><td>Harnessing Human Manipulation <br/>NSF/ARL Workshop on Cloud Robotics: Challenges and Opportunities <br/>February 27-28, 2013 <br/><b>The Robotics Institute Carnegie Mellon University</b><br/><b>Georgia Institute of Technology</b></td><td>('1781040', 'Matthew T. Mason', 'matthew t. mason')<br/>('1735665', 'Nancy Pollard', 'nancy pollard')<br/>('1760708', 'Alberto Rodriguez', 'alberto rodriguez')<br/>('38637733', 'Ryan Kerwin', 'ryan kerwin')</td><td><matt.mason, nsp, albertor>@cs.cmu.edu @@ -30804,7 +39689,13 @@ </td><td>('2086289', 'Hong Liu', 'hong liu')<br/>('1687248', 'Hongbin Zha', 'hongbin zha')<br/>('2976781', 'Yuwen Wu', 'yuwen wu')</td><td>wuyw@cis.pku.edu.cn <br/>liuhong@cis.pku.edu.cn <br/>zha@cis.pku.edu.cn -</td></tr><tr><td>793e7f1ba18848908da30cbad14323b0389fd2a8</td><td></td><td></td><td></td></tr><tr><td>2d990b04c2bd61d3b7b922b8eed33aeeeb7b9359</td><td>Discriminative Dictionary Learning with +</td></tr><tr><td>793e7f1ba18848908da30cbad14323b0389fd2a8</td><td></td><td></td><td></td></tr><tr><td>79db191ca1268dc88271abef3179c4fe4ee92aed</td><td>Facial Expression Based Automatic Album +<br/>Creation +<br/><b>School of Computer Science, CECS, Australian National University, Canberra</b><br/><b>School of Engineering, CECS, Australian National University, Canberra, Australia</b><br/>3 Vision & Sensing, Faculty of Information Sciences and Engineering, +<br/>Australia +<br/><b>University of Canberra, Australia</b></td><td>('1735697', 'Abhinav Dhall', 'abhinav dhall')<br/>('3183108', 'Akshay Asthana', 'akshay asthana')<br/>('1717204', 'Roland Goecke', 'roland goecke')</td><td>abhinav.dhall@anu.edu.au, aasthana@rsise.anu.edu.au, +<br/>roland.goecke@ieee.org +</td></tr><tr><td>2d990b04c2bd61d3b7b922b8eed33aeeeb7b9359</td><td>Discriminative Dictionary Learning with <br/>Pairwise Constraints <br/><b>University of Maryland, College Park, MD</b></td><td>('2723427', 'Huimin Guo', 'huimin guo')<br/>('34145947', 'Zhuolin Jiang', 'zhuolin jiang')<br/>('1693428', 'Larry S. Davis', 'larry s. davis')</td><td>{hmguo,zhuolin,lsd}@umiacs.umd.edu </td></tr><tr><td>2d25045ec63f9132371841c0beccd801d3733908</td><td>Sensors 2015, 15, 6719-6739; doi:10.3390/s150306719 @@ -30830,11 +39721,18 @@ <br/><b>State Key Laboratory for Novel Software Technology, Nanjing University, China</b><br/><b>University of Michigan, Ann Arbor</b></td><td>('40188401', 'Jonathan C. Stroud', 'jonathan c. stroud')<br/>('2285916', 'Tong Lu', 'tong lu')<br/>('8342699', 'Jia Deng', 'jia deng')</td><td></td></tr><tr><td>2d294c58b2afb529b26c49d3c92293431f5f98d0</td><td>4413 <br/>Maximum Margin Projection Subspace Learning <br/>for Visual Data Analysis -</td><td>('1793625', 'Symeon Nikitidis', 'symeon nikitidis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td></td></tr><tr><td>2d1f86e2c7ba81392c8914edbc079ac64d29b666</td><td></td><td></td><td></td></tr><tr><td>2d164f88a579ba53e06b601d39959aaaae9016b7</td><td>Dynamic Facial Expression Recognition Using +</td><td>('1793625', 'Symeon Nikitidis', 'symeon nikitidis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')<br/>('1698588', 'Ioannis Pitas', 'ioannis pitas')</td><td></td></tr><tr><td>2d1f86e2c7ba81392c8914edbc079ac64d29b666</td><td></td><td></td><td></td></tr><tr><td>2d9e58ea582e054e9d690afca8b6a554c3687ce6</td><td>Learning Local Feature Aggregation Functions +<br/>with Backpropagation +<br/>Multimedia Understanding Group +<br/><b>Aristotle University of Thessaloniki, Greece</b></td><td>('3493855', 'Angelos Katharopoulos', 'angelos katharopoulos')<br/>('3493472', 'Despoina Paschalidou', 'despoina paschalidou')<br/>('1789830', 'Christos Diou', 'christos diou')<br/>('1708199', 'Anastasios Delopoulos', 'anastasios delopoulos')</td><td>{katharas, pdespoin}@auth.gr; diou@mug.ee.auth.gr; adelo@eng.auth.gr +</td></tr><tr><td>2d164f88a579ba53e06b601d39959aaaae9016b7</td><td>Dynamic Facial Expression Recognition Using <br/>A Bayesian Temporal Manifold Model <br/>Department of Computer Science <br/><b>Queen Mary University of London</b><br/>Mile End Road, London E1 4NS, UK </td><td>('10795229', 'Caifeng Shan', 'caifeng shan')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('2803283', 'Peter W. McOwan', 'peter w. mcowan')</td><td>{cfshan, sgg, pmco}@dcs.qmul.ac.uk +</td></tr><tr><td>2d8001ffee6584b3f4d951d230dc00a06e8219f8</td><td>Feature Agglomeration Networks for Single Stage Face Detection +<br/><b>School of Information Systems, Singapore Management University, Singapore</b><br/><b>College of Computer Science and Technology, Zhejiang University, Hangzhou, China</b><br/>§DeepIR Inc., Beijing, China +</td><td>('1826176', 'Jialiang Zhang', 'jialiang zhang')<br/>('2791484', 'Xiongwei Wu', 'xiongwei wu')<br/>('1704030', 'Jianke Zhu', 'jianke zhu')</td><td>{chhoi,xwwu.2015@phdis}@smu.edu.sg;{zjialiang,jkzhu}@zju.edu.cn </td></tr><tr><td>2d23fa205acca9c21e3e1a04674f1e5a9528550e</td><td>The Fast and the Flexible: <br/>Extended Pseudo Two-Dimensional Warping for <br/>Face Recognition @@ -30980,6 +39878,72 @@ <br/>Machine Learning using C# </td><td></td><td>Author: Neda Firoz (nedafiroz1910@gmail.com) <br/>Advisor: Dr. Prashant Ankur Jain (prashant.jain@shiats.edu.in) +</td></tr><tr><td>2dfe0e7e81f65716b09c590652a4dd8452c10294</td><td>ORIGINAL RESEARCH +<br/>published: 06 June 2018 +<br/>doi: 10.3389/fpsyg.2018.00864 +<br/>Incongruence Between Observers’ +<br/>and Observed Facial Muscle +<br/>Activation Reduces Recognition of +<br/>Emotional Facial Expressions From +<br/>Video Stimuli +<br/><b>Centre for Applied Autism Research, University of Bath, Bath, United Kingdom, 2 Social and</b><br/><b>Cognitive Neuroscience Laboratory, Centre of Biology and Health Sciences, Mackenzie Presbyterian University, S o Paulo</b><br/><b>Brazil, University Hospital Zurich, Z rich</b><br/><b>Switzerland, Psychosomatic Medicine, and Psychotherapy, University Hospital Frankfurt</b><br/>Frankfurt, Germany +<br/>According to embodied cognition accounts, viewing others’ facial emotion can elicit +<br/>the respective emotion representation in observers which entails simulations of sensory, +<br/>motor, and contextual experiences. In line with that, published research found viewing +<br/>others’ +<br/>facial emotion to elicit automatic matched facial muscle activation, which +<br/>was further found to facilitate emotion recognition. Perhaps making congruent facial +<br/>muscle activity explicit produces an even greater recognition advantage. If there is +<br/><b>con icting sensory information, i.e., incongruent facial muscle activity, this might impede</b><br/>recognition. The effects of actively manipulating facial muscle activity on facial emotion +<br/>recognition from videos were investigated across three experimental conditions: (a) +<br/>explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), +<br/>(b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing +<br/>(control condition). It was hypothesised that (1) experimental condition (a) and (b) result +<br/>in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion +<br/>recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) +<br/>lowers recognition accuracy for expressions with a salient facial feature in the lower, +<br/>but not the upper face area, compared to (c). Participants (42 males, 42 females) +<br/>underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography +<br/>(EMG) was recorded from five facial muscle sites. The experimental conditions’ order +<br/>was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity +<br/>for expressions with facial feature saliency in the lower face region, which reduced +<br/>recognition of lower face region emotions. Explicit imitation caused stimulus-congruent +<br/>facial muscle activity without modulating recognition. Methodological +<br/>implications are +<br/>discussed. +<br/>Keywords: facial emotion recognition, imitation, facial muscle activity, facial EMG, embodiment, videos, dynamic +<br/>stimuli, facial expressions of emotion +<br/>Edited by: +<br/>Eva G. Krumhuber, +<br/><b>University College London</b><br/>United Kingdom +<br/>Reviewed by: +<br/>Sebastian Korb, +<br/>Universität Wien, Austria +<br/>Michal Olszanowski, +<br/><b>SWPS University of Social Sciences</b><br/>and Humanities, Poland +<br/>*Correspondence: +<br/>Tanja S. H. Wingenbach +<br/>Specialty section: +<br/>This article was submitted to +<br/>Emotion Science, +<br/>a section of the journal +<br/>Frontiers in Psychology +<br/>Received: 15 December 2017 +<br/>Accepted: 14 May 2018 +<br/>Published: 06 June 2018 +<br/>Citation: +<br/>Wingenbach TSH, Brosnan M, +<br/>Pfaltz MC, Plichta MM and Ashwin C +<br/>(2018) Incongruence Between +<br/>Observers’ and Observed Facial +<br/>Muscle Activation Reduces +<br/>Recognition of Emotional Facial +<br/>Expressions From Video Stimuli. +<br/>Front. Psychol. 9:864. +<br/>doi: 10.3389/fpsyg.2018.00864 +<br/>Frontiers in Psychology | www.frontiersin.org +<br/>June 2018 | Volume 9 | Article 864 +</td><td>('39455300', 'Mark Brosnan', 'mark brosnan')<br/>('34495803', 'Monique C. Pfaltz', 'monique c. pfaltz')<br/>('2976177', 'Michael M. Plichta', 'michael m. plichta')<br/>('2708124', 'Chris Ashwin', 'chris ashwin')</td><td>tanja.wingenbach@bath.edu </td></tr><tr><td>2d072cd43de8d17ce3198fae4469c498f97c6277</td><td>Random Cascaded-Regression Copse for Robust <br/>Facial Landmark Detection <br/>and Xiao-Jun Wu @@ -31067,7 +40031,10 @@ <br/>March 2015 <br/>Dissertation Committee: <br/>Professor Conrad Rudolph -</td><td>('11012197', 'Ramya Malur Srinivasan', 'ramya malur srinivasan')<br/>('1688416', 'Amit K Roy-Chowdhury', 'amit k roy-chowdhury')<br/>('1686303', 'Ertem Tuncel', 'ertem tuncel')<br/>('2357146', 'Tamar Shinar', 'tamar shinar')</td><td></td></tr><tr><td>2d79d338c114ece1d97cde1aa06ab4cf17d38254</td><td>iLab-20M: A large-scale controlled object dataset to investigate deep learning +</td><td>('11012197', 'Ramya Malur Srinivasan', 'ramya malur srinivasan')<br/>('1688416', 'Amit K Roy-Chowdhury', 'amit k roy-chowdhury')<br/>('1686303', 'Ertem Tuncel', 'ertem tuncel')<br/>('2357146', 'Tamar Shinar', 'tamar shinar')</td><td></td></tr><tr><td>2d8d089d368f2982748fde93a959cf5944873673</td><td>Proceedings of NAACL-HLT 2018, pages 788–794 +<br/>New Orleans, Louisiana, June 1 - 6, 2018. c(cid:13)2018 Association for Computational Linguistics +<br/>788 +</td><td></td><td></td></tr><tr><td>2d79d338c114ece1d97cde1aa06ab4cf17d38254</td><td>iLab-20M: A large-scale controlled object dataset to investigate deep learning <br/><b>Center for Research in Computer Vision, University of Central Florida</b><br/><b>Amirkabir University of Technology, University of Southern California</b></td><td>('3177797', 'Ali Borji', 'ali borji')<br/>('2391309', 'Saeed Izadi', 'saeed izadi')<br/>('7326223', 'Laurent Itti', 'laurent itti')</td><td>aborji@crcv.ucf.edu, sizadi@aut.ac.ir, itti@usc.edu </td></tr><tr><td>2df4d05119fe3fbf1f8112b3ad901c33728b498a</td><td>Facial landmark detection using structured output deep <br/>neural networks @@ -31078,7 +40045,12 @@ <br/>September 24, 2015 </td><td></td><td></td></tr><tr><td>2d3482dcff69c7417c7b933f22de606a0e8e42d4</td><td>Labeled Faces in the Wild: Updates and <br/>New Reporting Procedures -<br/><b>University of Massachusetts, Amherst Technical Report UM-CS</b></td><td>('3219900', 'Gary B. Huang', 'gary b. huang')<br/>('1714536', 'Erik Learned-Miller', 'erik learned-miller')</td><td></td></tr><tr><td>2d748f8ee023a5b1fbd50294d176981ded4ad4ee</td><td>TRIPLET SIMILARITY EMBEDDING FOR FACE VERIFICATION +<br/><b>University of Massachusetts, Amherst Technical Report UM-CS</b></td><td>('3219900', 'Gary B. Huang', 'gary b. huang')<br/>('1714536', 'Erik Learned-Miller', 'erik learned-miller')</td><td></td></tr><tr><td>2d4a3e9361505616fa4851674eb5c8dd18e0c3cf</td><td>Towards Privacy-Preserving Visual Recognition +<br/>via Adversarial Training: A Pilot Study +<br/><b>Texas AandM University, College Station TX 77843, USA</b><br/>2 Adobe Research, San Jose CA 95110, USA +</td><td>('1733940', 'Zhenyu Wu', 'zhenyu wu')<br/>('2969311', 'Zhangyang Wang', 'zhangyang wang')<br/>('8056043', 'Zhaowen Wang', 'zhaowen wang')<br/>('39909162', 'Hailin Jin', 'hailin jin')</td><td>{wuzhenyu sjtu,atlaswang}@tamu.edu +<br/>{zhawang,hljin}@adobe.com +</td></tr><tr><td>2d748f8ee023a5b1fbd50294d176981ded4ad4ee</td><td>TRIPLET SIMILARITY EMBEDDING FOR FACE VERIFICATION <br/><b>Center for Automation Research, UMIACS, University of Maryland, College Park, MD</b><br/>1Department of Electrical and Computer Engineering, </td><td>('2716670', 'Swami Sankaranarayanan', 'swami sankaranarayanan')<br/>('2943431', 'Azadeh Alavi', 'azadeh alavi')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{swamiviv, azadeh, rama}@umiacs.umd.edu </td></tr><tr><td>2d3c17ced03e4b6c4b014490fe3d40c62d02e914</td><td>COMPUTER ANIMATION AND VIRTUAL WORLDS @@ -31087,7 +40059,9 @@ <br/>SPECIAL ISSUE PAPER <br/>Video-driven state-aware facial animation <br/><b>State Key Lab of CADandCG, Zhejiang University, Hangzhou, Zhejiang, China</b><br/>2 Microsoft Corporation, Seattle, WA, USA -</td><td>('2894564', 'Ming Zeng', 'ming zeng')<br/>('1680293', 'Lin Liang', 'lin liang')<br/>('3227032', 'Xinguo Liu', 'xinguo liu')<br/>('1679542', 'Hujun Bao', 'hujun bao')</td><td></td></tr><tr><td>4188bd3ef976ea0dec24a2512b44d7673fd4ad26</td><td>1050 +</td><td>('2894564', 'Ming Zeng', 'ming zeng')<br/>('1680293', 'Lin Liang', 'lin liang')<br/>('3227032', 'Xinguo Liu', 'xinguo liu')<br/>('1679542', 'Hujun Bao', 'hujun bao')</td><td></td></tr><tr><td>41f26101fed63a8d149744264dd5aa79f1928265</td><td>Spot On: Action Localization from +<br/>Pointly-Supervised Proposals +<br/><b>University of Amsterdam</b><br/><b>Delft University of Technology</b></td><td>('2606260', 'Pascal Mettes', 'pascal mettes')<br/>('1738975', 'Jan C. van Gemert', 'jan c. van gemert')</td><td></td></tr><tr><td>4188bd3ef976ea0dec24a2512b44d7673fd4ad26</td><td>1050 <br/>Nonlinear Non-Negative Component <br/>Analysis Algorithms </td><td>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')<br/>('2871609', 'Maria Petrou', 'maria petrou')</td><td></td></tr><tr><td>416b559402d0f3e2b785074fcee989d44d82b8e5</td><td>Multi-View Super Vector for Action Recognition @@ -31114,7 +40088,11 @@ <br/>Framework-Based Modified Local Directional Number <br/>Pattern with Various Classifiers for Face Recognition <br/><b>St. Xavier s Catholic College of Engineering, Nagercoil, India</b><br/><b>VelTech Dr. R.R. and Dr. S.R. Technical University, Chennai</b><br/><b>Manonmaniam Sundaranar University, Tirunelveli</b><br/>India. -</td><td>('9375880', 'R. Reena Rose', 'r. reena rose')</td><td></td></tr><tr><td>4140498e96a5ff3ba816d13daf148fffb9a2be3f</td><td>2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition +</td><td>('9375880', 'R. Reena Rose', 'r. reena rose')</td><td></td></tr><tr><td>411318684bd2d42e4b663a37dcf0532a48f0146d</td><td>Improved Face Verification with Simple +<br/>Weighted Feature Combination +<br/><b>College of Electronics and Information Engineering, Tongji University</b><br/>4800 Cao’an Highway, Shanghai 201804, People’s Republic of China +</td><td>('1775391', 'Xinyu Zhang', 'xinyu zhang')<br/>('48566761', 'Jiang Zhu', 'jiang zhu')<br/>('34647494', 'Mingyu You', 'mingyu you')</td><td>{1510464,zhujiang,myyou}@tongji.edu.cn +</td></tr><tr><td>4140498e96a5ff3ba816d13daf148fffb9a2be3f</td><td>2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition <br/>2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition <br/>2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition <br/>2017 IEEE 12th International Conference on Automatic Face & Gesture Recognition @@ -31126,7 +40104,10 @@ <br/><b>Northwestern University</b><br/>Evanston, IL 60208-3118 </td><td>('2563314', 'Derek J. Shiell', 'derek j. shiell')<br/>('3271105', 'Louis H. Terry', 'louis h. terry')<br/>('2691927', 'Petar S. Aleksic', 'petar s. aleksic')<br/>('1695338', 'Aggelos K. Katsaggelos', 'aggelos k. katsaggelos')</td><td>d-shiell@northwestern.edu, l-terry@northwestern.edu, <br/>apetar@eecs.northwestern.edu, aggk@eecs.northwestern.edu -</td></tr><tr><td>41aa8c1c90d74f2653ef4b3a2e02ac473af61e47</td><td>Compositional Structure Learning for Action Understanding +</td></tr><tr><td>414715421e01e8c8b5743c5330e6d2553a08c16d</td><td>PoTion: Pose MoTion Representation for Action Recognition +<br/>1Inria∗ +<br/>2NAVER LABS Europe +</td><td>('2492127', 'Philippe Weinzaepfel', 'philippe weinzaepfel')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>41aa8c1c90d74f2653ef4b3a2e02ac473af61e47</td><td>Compositional Structure Learning for Action Understanding <br/>1Department of Computer Science and Engineering, SUNY at Buffalo <br/>2Department of Statistics, UCLA <br/><b>University of Michigan</b><br/>October 23, 2014 @@ -31343,7 +40324,27 @@ </td></tr><tr><td>83ca4cca9b28ae58f461b5a192e08dffdc1c76f3</td><td>DETECTING EMOTIONAL STRESS FROM FACIAL EXPRESSIONS FOR DRIVING SAFETY <br/>Signal Processing Laboratory (LTS5), <br/>´Ecole Polytechnique F´ed´erale de Lausanne, Switzerland -</td><td>('1697965', 'Hua Gao', 'hua gao')<br/>('1710257', 'Jean-Philippe Thiran', 'jean-philippe thiran')</td><td></td></tr><tr><td>831fbef657cc5e1bbf298ce6aad6b62f00a5b5d9</td><td></td><td></td><td></td></tr><tr><td>832e1d128059dd5ed5fa5a0b0f021a025903f9d5</td><td>Pairwise Conditional Random Forests for Facial Expression Recognition +</td><td>('1697965', 'Hua Gao', 'hua gao')<br/>('1710257', 'Jean-Philippe Thiran', 'jean-philippe thiran')</td><td></td></tr><tr><td>8356832f883207187437872742d6b7dc95b51fde</td><td>Adversarial Perturbations Against Real-Time Video +<br/>Classification Systems +<br/><b>University of California, Riverside</b><br/><b>University of California, Riverside</b><br/><b>University of California, Riverside</b><br/>Riverside, California +<br/>Riverside, California +<br/><b>University of California, Riverside</b><br/>Riverside, California +<br/>Riverside, California +<br/><b>University of California, Riverside</b><br/>Riverside, California +<br/>Amit K. Roy Chowdhury +<br/><b>University of California, Riverside</b><br/>Riverside, California +<br/>United States Army Research +<br/>Laboratory +</td><td>('26576993', 'Shasha Li', 'shasha li')<br/>('2252367', 'Chengyu Song', 'chengyu song')<br/>('1718484', 'Ajaya Neupane', 'ajaya neupane')<br/>('49616225', 'Sujoy Paul', 'sujoy paul')<br/>('38774813', 'Srikanth V. Krishnamurthy', 'srikanth v. krishnamurthy')<br/>('1703726', 'Ananthram Swami', 'ananthram swami')</td><td>sli057@ucr.edu +<br/>csong@cs.ucr.edu +<br/>ajaya@ucr.edu +<br/>spaul003@ucr.edu +<br/>krish@cs.ucr.edu +<br/>amitrc@ece.ucr.edu +<br/>ananthram.swami.civ@mail.mil +</td></tr><tr><td>831fbef657cc5e1bbf298ce6aad6b62f00a5b5d9</td><td></td><td></td><td></td></tr><tr><td>835e510fcf22b4b9097ef51b8d0bb4e7b806bdfd</td><td>Unsupervised Learning of Sequence Representations by +<br/>Autoencoders +<br/><b>aPattern Recognition Laboratory, Delft University of Technology</b></td><td>('1678473', 'Wenjie Pei', 'wenjie pei')</td><td></td></tr><tr><td>832e1d128059dd5ed5fa5a0b0f021a025903f9d5</td><td>Pairwise Conditional Random Forests for Facial Expression Recognition <br/>S´everine Dubuisson1 <br/>1 Sorbonne Universit´es, UPMC Univ Paris 06, CNRS, ISIR UMR 7222, 4 place Jussieu 75005 Paris </td><td>('3190846', 'Arnaud Dapogny', 'arnaud dapogny')<br/>('2521061', 'Kevin Bailly', 'kevin bailly')</td><td>arnaud.dapogny@isir.upmc.fr @@ -31361,6 +40362,14 @@ </td></tr><tr><td>83b4899d2899dd6a8d956eda3c4b89f27f1cd308</td><td>1-4244-1437-7/07/$20.00 ©2007 IEEE <br/>I - 377 <br/>ICIP 2007 +</td><td></td><td></td></tr><tr><td>83295bce2340cb87901499cff492ae6ff3365475</td><td>Deep Multi-Center Learning for Face Alignment +<br/><b>Shanghai Jiao Tong University, China</b><br/><b>School of Computer Science and Software Engineering, East China Normal University, China</b></td><td>('3403352', 'Zhiwen Shao', 'zhiwen shao')<br/>('7296339', 'Hengliang Zhu', 'hengliang zhu')<br/>('1767677', 'Xin Tan', 'xin tan')<br/>('2107352', 'Yangyang Hao', 'yangyang hao')<br/>('8452947', 'Lizhuang Ma', 'lizhuang ma')</td><td>{shaozhiwen, hengliang zhu, tanxin2017, haoyangyang2014}@sjtu.edu.cn, ma-lz@cs.sjtu.edu.cn +</td></tr><tr><td>83e96ed8a4663edaa3a5ca90b7ce75a1bb595b05</td><td>ARANDJELOVI´C:RECOGNITIONFROMAPPEARANCESUBSPACESACROSSSCALE +<br/>Recognition from Appearance Subspaces +<br/>Across Image Sets of Variable Scale +<br/>Ognjen Arandjelovi´c +<br/>http://mi.eng.cam.ac.uk/~oa214 +<br/><b>Trinity College</b><br/><b>University of Cambridge</b><br/>CB2 1TQ, UK </td><td></td><td></td></tr><tr><td>830e5b1043227fe189b3f93619ef4c58868758a7</td><td></td><td></td><td></td></tr><tr><td>8323af714efe9a3cadb31b309fcc2c36c8acba8f</td><td>Automatic Real-Time <br/>Facial Expression Recognition <br/>for Signed Language Translation @@ -31457,20 +40466,60 @@ </td></tr><tr><td>8320dbdd3e4712cca813451cd94a909527652d63</td><td>EAR BIOMETRICS <br/>and Wilhelm Burger <br/><b>Johannes Kepler University(cid:1) Institute of Systems Science(cid:1) A(cid:2) -</td><td>('12811570', 'Mark Burge', 'mark burge')</td><td></td></tr><tr><td>834b15762f97b4da11a2d851840123dbeee51d33</td><td>Landmark-free smile intensity estimation +</td><td>('12811570', 'Mark Burge', 'mark burge')</td><td></td></tr><tr><td>837e99301e00c2244023a8a48ff98d7b521c93ac</td><td>Local Feature Evaluation for a Constrained +<br/>Local Model Framework +<br/><b>Graduate School of Engineering, Tottori University</b><br/>101 Minami 4-chome, Koyama-cho, Tottori 680-8550, Japan +</td><td>('1770332', 'Maiya Hori', 'maiya hori')<br/>('48532779', 'Shogo Kawai', 'shogo kawai')<br/>('2020088', 'Hiroki Yoshimura', 'hiroki yoshimura')<br/>('1679437', 'Yoshio Iwai', 'yoshio iwai')</td><td>hori@ike.tottori-u.ac.jp +</td></tr><tr><td>834b15762f97b4da11a2d851840123dbeee51d33</td><td>Landmark-free smile intensity estimation <br/>IMAGO Research Group - Universidade Federal do Paran´a <br/>Fig. 1. Overview of our method for smile intensity estimation </td><td>('1800955', 'Olga R. P. Bellon', 'olga r. p. bellon')</td><td>{julio.batista,olga,luciano}@ufpr.br </td></tr><tr><td>833f6ab858f26b848f0d747de502127406f06417</td><td>978-1-4244-5654-3/09/$26.00 ©2009 IEEE <br/>61 <br/>ICIP 2009 -</td><td></td><td></td></tr><tr><td>8309e8f27f3fb6f2ac1b4343a4ad7db09fb8f0ff</td><td>Generic versus Salient Region-based Partitioning +</td><td></td><td></td></tr><tr><td>8334da483f1986aea87b62028672836cb3dc6205</td><td>Fully Associative Patch-based 1-to-N Matcher for Face Recognition +<br/>Computational Biomedicine Lab +<br/><b>University of Houston</b></td><td>('39089616', 'Lingfeng Zhang', 'lingfeng zhang')<br/>('1706204', 'Ioannis A. Kakadiaris', 'ioannis a. kakadiaris')</td><td>{lzhang34, ioannisk}@uh.edu +</td></tr><tr><td>831b4d8b0c0173b0bac0e328e844a0fbafae6639</td><td>Consensus-Driven Propagation in +<br/>Massive Unlabeled Data for Face Recognition +<br/><b>CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong</b><br/>2 SenseTime Group Limited +<br/><b>Nanyang Technological University</b></td><td>('31818765', 'Xiaohang Zhan', 'xiaohang zhan')<br/>('3243969', 'Ziwei Liu', 'ziwei liu')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('1807606', 'Dahua Lin', 'dahua lin')<br/>('1717179', 'Chen Change Loy', 'chen change loy')</td><td>{zx017, zwliu, dhlin}@ie.cuhk.edu.hk +<br/>yanjunjie@sensetime.com +<br/>ccloy@ieee.org +</td></tr><tr><td>8309e8f27f3fb6f2ac1b4343a4ad7db09fb8f0ff</td><td>Generic versus Salient Region-based Partitioning <br/>for Local Appearance Face Recognition <br/>Computer Science Depatment, Universit¨at Karlsruhe (TH) <br/>Am Fasanengarten 5, Karlsruhe 76131, Germany <br/>http://isl.ira.uka.de/cvhci </td><td>('1742325', 'Rainer Stiefelhagen', 'rainer stiefelhagen')</td><td>{ekenel,stiefel}@ira.uka.de -</td></tr><tr><td>1b635f494eff2e5501607ebe55eda7bdfa8263b8</td><td>USC at THUMOS 2014 +</td></tr><tr><td>1b02b9413b730b96b91d16dcd61b2420aef97414</td><td>Détection de marqueurs affectifs et attentionnels de +<br/>personnes âgées en interaction avec un robot +<br/>To cite this version: +<br/>avec un robot. +<br/>Intelligence artificielle [cs.AI]. Université Paris-Saclay, 2015. Français. <NNT : +<br/>2015SACLS081>. <tel-01280505> +<br/>HAL Id: tel-01280505 +<br/>https://tel.archives-ouvertes.fr/tel-01280505 +<br/>Submitted on 29 Feb 2016 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('47829802', 'Fan Yang', 'fan yang')<br/>('47829802', 'Fan Yang', 'fan yang')</td><td></td></tr><tr><td>1b55c4e804d1298cbbb9c507497177014a923d22</td><td>Incremental Class Representation +<br/>Learning for Face Recognition +<br/>Degree’s Thesis +<br/>Audiovisual Systems Engineering +<br/>Author: +<br/>Universitat Politècnica de Catalunya (UPC) +<br/>2016 - 2017 +</td><td>('2470219', 'Elisa Sayrol', 'elisa sayrol')<br/>('2585946', 'Josep Ramon Morros', 'josep ramon morros')</td><td></td></tr><tr><td>1b635f494eff2e5501607ebe55eda7bdfa8263b8</td><td>USC at THUMOS 2014 <br/><b>University of Southern California, Institute for Robotics and Intelligent Systems</b><br/>Los Angeles, CA 90089, USA </td><td>('1726241', 'Chen Sun', 'chen sun')<br/>('27735100', 'Ram Nevatia', 'ram nevatia')</td><td></td></tr><tr><td>1b6394178dbc31d0867f0b44686d224a19d61cf4</td><td>EPML: Expanded Parts based Metric Learning for <br/>Occlusion Robust Face Verification @@ -31491,13 +40540,42 @@ <br/>´emanant des ´etablissements d’enseignement et de <br/>recherche fran¸cais ou ´etrangers, des laboratoires <br/>publics ou priv´es. -</td><td>('2515597', 'Gaurav Sharma', 'gaurav sharma')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>1bd50926079e68a6e32dc4412e9d5abe331daefb</td><td></td><td></td><td></td></tr><tr><td>1b150248d856f95da8316da868532a4286b9d58e</td><td>Analyzing 3D Objects in Cluttered Images +</td><td>('2515597', 'Gaurav Sharma', 'gaurav sharma')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>1bd50926079e68a6e32dc4412e9d5abe331daefb</td><td></td><td></td><td></td></tr><tr><td>1bdef21f093c41df2682a07f05f3548717c7a3d1</td><td>Towards Automated Classification of Emotional Facial Expressions +<br/>1Department of Mathematics and Computer Science, 2Department of Psychology +<br/><b>Rutgers University Newark, 101 Warren St., Newark, NJ, 07102 USA</b></td><td></td><td>Lewis J. Baker (lewis.j.baker@rutgers.edu)1, Vanessa LoBue (vlobue@rutgers.edu)2, +<br/>Elizabeth Bonawitz (elizabeth.bonawitz@rutgers.edu)2, & Patrick Shafto (patrick.shafto@gmail.com)1 +</td></tr><tr><td>1b150248d856f95da8316da868532a4286b9d58e</td><td>Analyzing 3D Objects in Cluttered Images <br/>UC Irvine <br/>UC Irvine </td><td>('1888731', 'Mohsen Hejrati', 'mohsen hejrati')<br/>('1770537', 'Deva Ramanan', 'deva ramanan')</td><td>shejrati@ics.uci.edu <br/>dramanan@ics.uci.edu </td></tr><tr><td>1be498d4bbc30c3bfd0029114c784bc2114d67c0</td><td>Age and Gender Estimation of Unfiltered Faces -</td><td>('2037829', 'Eran Eidinger', 'eran eidinger')<br/>('1792038', 'Roee Enbar', 'roee enbar')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>1b5875dbebc76fec87e72cee7a5263d325a77376</td><td>Learnt Quasi-Transitive Similarity for Retrieval from Large Collections of Faces +</td><td>('2037829', 'Eran Eidinger', 'eran eidinger')<br/>('1792038', 'Roee Enbar', 'roee enbar')<br/>('1756099', 'Tal Hassner', 'tal hassner')</td><td></td></tr><tr><td>1bbec7190ac3ba34ca91d28f145e356a11418b67</td><td>Action Recognition with Dynamic Image Networks +<br/>Citation for published version: +<br/>Bilen, H, Fernando, B, Gravves, E & Vedaldi, A 2017, 'Action Recognition with Dynamic Image Networks' +<br/>IEEE Transactions on Pattern Analysis and Machine Intelligence. DOI: 10.1109/TPAMI.2017.2769085 +<br/>Digital Object Identifier (DOI): +<br/>10.1109/TPAMI.2017.2769085 +<br/>Link: +<br/>Link to publication record in Edinburgh Research Explorer +<br/>Document Version: +<br/>Peer reviewed version +<br/>Published In: +<br/>IEEE Transactions on Pattern Analysis and Machine Intelligence +<br/>General rights +<br/>Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) +<br/>and / or other copyright owners and it is a condition of accessing these publications that users recognise and +<br/>abide by the legal requirements associated with these rights. +<br/>Take down policy +<br/><b>The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer</b><br/>content complies with UK legislation. If you believe that the public display of this file breaches copyright please +<br/>investigate your claim. +<br/>Download date: 25. Dec. 2017 +<br/> Edinburgh Research Explorer </td><td></td><td>contact openaccess@ed.ac.uk providing details, and we will remove access to the work immediately and +</td></tr><tr><td>1b3587363d37dd197b6adbcfa79d49b5486f27d8</td><td>Multimodal Grounding for Language Processing +<br/><b>Language Technology Lab, University of Duisburg-Essen</b><br/>(cid:52) Ubiquitous Knowledge Processing Lab (UKP) and Research Training Group AIPHES +<br/>Department of Computer Science, Technische Universit¨at Darmstadt +<br/>www.ukp.tu-darmstadt.de +</td><td>('2752573', 'Lisa Beinborn', 'lisa beinborn')<br/>('25080314', 'Teresa Botschen', 'teresa botschen')<br/>('1730400', 'Iryna Gurevych', 'iryna gurevych')</td><td></td></tr><tr><td>1b5875dbebc76fec87e72cee7a5263d325a77376</td><td>Learnt Quasi-Transitive Similarity for Retrieval from Large Collections of Faces <br/>Ognjen Arandjelovi´c <br/><b>University of St Andrews, United Kingdom</b></td><td></td><td>ognjen.arandjelovic@gmail.com </td></tr><tr><td>1bdfb3deae6e6c0df6537efcd1d7edcb4d7a96e9</td><td>Groupwise Constrained Reconstruction for Subspace Clustering @@ -31619,7 +40697,11 @@ <br/>System Using Independent Component Analysis <br/><b>Student, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India</b><br/><b>Guide, HOD, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India</b><br/><b>Co-Guide, Computer Science, Shah and Anchor Kuttchi Engineering College, Mumbai, India</b><br/>---------------------------------------------------------------------***--------------------------------------------------------------------- <br/>cards, tokens and keys. Biometric based methods examine -</td><td>('32330340', 'Manimala Mahato', 'manimala mahato')</td><td></td></tr><tr><td>1bc23c771688109bed9fd295ce82d7e702726327</td><td></td><td>('1706007', 'Jianchao Yang', 'jianchao yang')</td><td></td></tr><tr><td>1bad8a9640cdbc4fe7de12685651f44c4cff35ce</td><td>THETIS: THree Dimensional Tennis Shots +</td><td>('32330340', 'Manimala Mahato', 'manimala mahato')</td><td></td></tr><tr><td>1b71d3f30238cb6621021a95543cce3aab96a21b</td><td>Fine-grained Video Classification and Captioning +<br/><b>University of Toronto1, Twenty Billion Neurons</b></td><td>('2454800', 'Farzaneh Mahdisoltani', 'farzaneh mahdisoltani')<br/>('40586522', 'Guillaume Berger', 'guillaume berger')<br/>('3462264', 'Waseem Gharbieh', 'waseem gharbieh')<br/>('1710604', 'Roland Memisevic', 'roland memisevic')</td><td>1 {farzaneh, fleet}@cs.toronto.edu, {firstname.lastname}@twentybn.com +</td></tr><tr><td>1b4f6f73c70353869026e5eec1dd903f9e26d43f</td><td>Robust Subjective Visual Property Prediction +<br/>from Crowdsourced Pairwise Labels +</td><td>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('1697755', 'Timothy M. Hospedales', 'timothy m. hospedales')<br/>('1700927', 'Tao Xiang', 'tao xiang')<br/>('3081531', 'Jiechao Xiong', 'jiechao xiong')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('1717863', 'Yizhou Wang', 'yizhou wang')<br/>('1746280', 'Yuan Yao', 'yuan yao')</td><td></td></tr><tr><td>1bc23c771688109bed9fd295ce82d7e702726327</td><td></td><td>('1706007', 'Jianchao Yang', 'jianchao yang')</td><td></td></tr><tr><td>1bad8a9640cdbc4fe7de12685651f44c4cff35ce</td><td>THETIS: THree Dimensional Tennis Shots <br/>A human action dataset <br/>Sofia Gourgari <br/>Konstantinos Karpouzis @@ -31641,7 +40723,12 @@ </td><td>('1715001', 'Jun Wang', 'jun wang')<br/>('1791319', 'Shangfei Wang', 'shangfei wang')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>junwong@mail.ustc.edu.cn <br/>sfwang@ustc.edu.cn <br/>qji@ecse.rpi.edu -</td></tr><tr><td>1b27ca161d2e1d4dd7d22b1247acee5c53db5104</td><td></td><td></td><td></td></tr><tr><td>7711a7404f1f1ac3a0107203936e6332f50ac30c</td><td>Action Classification and Highlighting in Videos +</td></tr><tr><td>1b27ca161d2e1d4dd7d22b1247acee5c53db5104</td><td></td><td></td><td></td></tr><tr><td>1badfeece64d1bf43aa55c141afe61c74d0bd25e</td><td>OL ´E: Orthogonal Low-rank Embedding, +<br/>A Plug and Play Geometric Loss for Deep Learning +<br/>1Universidad de la Rep´ublica +<br/>Uruguay +<br/><b>Duke University</b><br/>USA +</td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('1699339', 'Guillermo Sapiro', 'guillermo sapiro')</td><td></td></tr><tr><td>7711a7404f1f1ac3a0107203936e6332f50ac30c</td><td>Action Classification and Highlighting in Videos <br/>Disney Research Pittsburgh <br/>Disney Research Pittsburgh </td><td>('1730844', 'Atousa Torabi', 'atousa torabi')<br/>('14517812', 'Leonid Sigal', 'leonid sigal')</td><td>atousa.torabi@disneyresearch.com @@ -31661,7 +40748,10 @@ <br/>Presented for the <br/>Doctor of Philosophy Degree <br/><b>The University of Tennessee, Knoxville</b><br/>December 2008 -</td><td>('21051127', 'Hong Chang', 'hong chang')</td><td></td></tr><tr><td>77b1db2281292372c38926cc4aca32ef056011dc</td><td>451492 EMR0010.1177/1754073912451492Widen Children’s Interpretation of Facial ExpressionsEmotion Review +</td><td>('21051127', 'Hong Chang', 'hong chang')</td><td></td></tr><tr><td>7789a5d87884f8bafec8a82085292e87d4e2866f</td><td>A Unified Tensor-based Active Appearance Face +<br/>Model +<br/>Member, IEEE +</td><td>('2976854', 'Zhen-Hua Feng', 'zhen-hua feng')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td></td></tr><tr><td>77b1db2281292372c38926cc4aca32ef056011dc</td><td>451492 EMR0010.1177/1754073912451492Widen Children’s Interpretation of Facial ExpressionsEmotion Review <br/>2012 <br/>SPECIAL SECTION: FACIAL EXPRESSIONS <br/>Children’s Interpretation of Facial Expressions: @@ -31710,7 +40800,14 @@ <br/>sjb@cs.ucsd.edu </td></tr><tr><td>7754b708d6258fb8279aa5667ce805e9f925dfd0</td><td>Facial Action Unit Recognition by Exploiting <br/>Their Dynamic and Semantic Relationships -</td><td>('1686235', 'Yan Tong', 'yan tong')<br/>('2460793', 'Wenhui Liao', 'wenhui liao')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td></td></tr><tr><td>77037a22c9b8169930d74d2ce6f50f1a999c1221</td><td>Robust Face Recognition With Kernelized +</td><td>('1686235', 'Yan Tong', 'yan tong')<br/>('2460793', 'Wenhui Liao', 'wenhui liao')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td></td></tr><tr><td>77db171a523fc3d08c91cea94c9562f3edce56e1</td><td>Poursaberi et al. EURASIP Journal on Image and Video Processing 2012, 2012:17 +<br/>http://jivp.eurasipjournals.com/content/2012/1/17 +<br/>R ES EAR CH +<br/>Open Access +<br/>Gauss–Laguerre wavelet textural feature fusion +<br/>with geometrical information for facial expression +<br/>identification +</td><td>('1786383', 'Ahmad Poursaberi', 'ahmad poursaberi')<br/>('1870195', 'Hossein Ahmadi', 'hossein ahmadi')</td><td></td></tr><tr><td>77037a22c9b8169930d74d2ce6f50f1a999c1221</td><td>Robust Face Recognition With Kernelized <br/>Locality-Sensitive Group Sparsity Representation </td><td>('1907978', 'Shoubiao Tan', 'shoubiao tan')<br/>('2796142', 'Xi Sun', 'xi sun')<br/>('2710497', 'Wentao Chan', 'wentao chan')<br/>('33306018', 'Lei Qu', 'lei qu')</td><td></td></tr><tr><td>779ad364cae60ca57af593c83851360c0f52c7bf</td><td>Steerable Pyramids Feature Based Classification Using Fisher <br/>Linear Discriminant for Face Recognition @@ -31720,6 +40817,15 @@ </td></tr><tr><td>7792fbc59f3eafc709323cdb63852c5d3a4b23e9</td><td>Pose from Action: Unsupervised Learning of <br/>Pose Features based on Motion <br/><b>Robotics Institute</b><br/><b>Carnegie Mellon University</b></td><td>('3234247', 'Senthil Purushwalkam', 'senthil purushwalkam')<br/>('1737809', 'Abhinav Gupta', 'abhinav gupta')</td><td>{spurushw@andrew,abhinavg@cs}.cmu.edu +</td></tr><tr><td>77fbbf0c5729f97fcdbfdc507deee3d388cd4889</td><td>SMITH & DYER: 3D FACIAL LANDMARK ESTIMATION +<br/>Pose-Robust 3D Facial Landmark Estimation +<br/>from a Single 2D Image +<br/>http://www.cs.wisc.edu/~bmsmith +<br/>http://www.cs.wisc.edu/~dyer +<br/>Department of Computer Sciences +<br/><b>University of Wisconsin-Madison</b><br/>Madison, WI USA +</td><td>('2721523', 'Brandon M. Smith', 'brandon m. smith')<br/>('1724754', 'Charles R. Dyer', 'charles r. dyer')</td><td></td></tr><tr><td>776362314f1479f5319aaf989624ac604ba42c65</td><td>Attribute learning in large-scale datasets +<br/><b>Stanford University</b></td><td>('2192178', 'Olga Russakovsky', 'olga russakovsky')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td>{olga,feifeili}@cs.stanford.edu </td></tr><tr><td>77d31d2ec25df44781d999d6ff980183093fb3de</td><td>The Multiverse Loss for Robust Transfer Learning <br/>Supplementary <br/>1. Omitted proofs @@ -31880,7 +40986,18 @@ </td><td>('3295771', 'Hamid Sadeghi', 'hamid sadeghi')<br/>('1697809', 'Mohammad-Reza Mohammadi', 'mohammad-reza mohammadi')</td><td>hamid.sadeghi@aut.ac.ir <br/>raie@aut.ac.ir <br/>mrmohammadi@ee.sharif.edu -</td></tr><tr><td>486a82f50835ea888fbc5c6babf3cf8e8b9807bc</td><td>MSU TECHNICAL REPORT MSU-CSE-15-11, JULY 24, 2015 +</td></tr><tr><td>48186494fc7c0cc664edec16ce582b3fcb5249c0</td><td>P-CNN: Pose-based CNN Features for Action Recognition +<br/>Guilhem Ch´eron∗ † +<br/>INRIA +</td><td>('1785596', 'Ivan Laptev', 'ivan laptev')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>48499deeaa1e31ac22c901d115b8b9867f89f952</td><td>Interim Report of Final Year Project +<br/>HKU-Face: A Large Scale Dataset for +<br/>Deep Face Recognition +<br/>3035140108 +<br/>Haoyu Li +<br/>3035141841 +<br/>COMP4801 Final Year Project +<br/>Project Code: 17007 +</td><td>('3347561', 'Haicheng Wang', 'haicheng wang')</td><td></td></tr><tr><td>486a82f50835ea888fbc5c6babf3cf8e8b9807bc</td><td>MSU TECHNICAL REPORT MSU-CSE-15-11, JULY 24, 2015 <br/>Face Search at Scale: 80 Million Gallery </td><td>('7496032', 'Dayong Wang', 'dayong wang')<br/>('40653304', 'Charles Otto', 'charles otto')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>48fea82b247641c79e1994f4ac24cad6b6275972</td><td>Mining Discriminative Components With Low-Rank And <br/>Sparsity Constraints for Face Recognition @@ -31894,6 +41011,9 @@ </td></tr><tr><td>48a417cfeba06feb4c7ab30f06c57ffbc288d0b5</td><td>Robust Dictionary Learning by Error Source Decomposition <br/><b>Northwestern University</b><br/>2145 Sheridan Road, Evanston, IL 60208 </td><td>('2240134', 'Zhuoyuan Chen', 'zhuoyuan chen')<br/>('39955137', 'Ying Wu', 'ying wu')</td><td>zhuoyuanchen2014@u.northwestern.edu,yingwu@eecs.northwestern.edu +</td></tr><tr><td>4850af6b54391fc33c8028a0b7fafe05855a96ff</td><td>Discovering Useful Parts for Pose Estimation in Sparsely Annotated Datasets +<br/>1Department of Computer Science and 2Department of Biology +<br/><b>Boston University and 2University of North Carolina</b></td><td>('2025025', 'Mikhail Breslav', 'mikhail breslav')<br/>('1711465', 'Tyson L. Hedrick', 'tyson l. hedrick')<br/>('1749590', 'Stan Sclaroff', 'stan sclaroff')<br/>('1723703', 'Margrit Betke', 'margrit betke')</td><td>breslav@bu.edu, thedrick@bio.unc.edu, sclaroff@bu.edu, betke@bu.edu </td></tr><tr><td>48c41ffab7ff19d24e8df3092f0b5812c1d3fb6e</td><td>Multi-Modal Embedding for Main Product Detection in Fashion <br/>1Institut de Robtica i Informtica Industrial (CSIC-UPC) <br/>2Wide Eyes Technologies @@ -31919,11 +41039,35 @@ <br/>South Africa </td><td>('3122515', 'Hima Vadapalli', 'hima vadapalli')</td><td></td></tr><tr><td>48729e4de8aa478ee5eeeb08a72a446b0f5367d5</td><td>COMPRESSED FACE HALLUCINATION <br/>Electrical Engineering and Computer Science -<br/><b>University of California, Merced, CA 95344, USA</b></td><td>('2391885', 'Sifei Liu', 'sifei liu')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>48174c414cfce7f1d71c4401d2b3d49ba91c5338</td><td>Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes +<br/><b>University of California, Merced, CA 95344, USA</b></td><td>('2391885', 'Sifei Liu', 'sifei liu')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>48e6c6d981efe2c2fb0ae9287376fcae59da9878</td><td>Sidekick Policy Learning +<br/>for Active Visual Exploration +<br/><b>The University of Texas at Austin, Austin, TX</b><br/>2 Facebook AI Research, 300 W. Sixth St. Austin, TX 78701 +</td><td>('21810992', 'Santhosh K. Ramakrishnan', 'santhosh k. ramakrishnan')<br/>('1794409', 'Kristen Grauman', 'kristen grauman')</td><td>srama@cs.utexas.edu, grauman@fb.com(cid:63) +</td></tr><tr><td>48174c414cfce7f1d71c4401d2b3d49ba91c5338</td><td>Robust Performance-driven 3D Face Tracking in Long Range Depth Scenes <br/><b>Rutgers University, USA</b><br/><b>Hong Kong Polytechnic University, Hong Kong</b><br/><b>School of Computer Engineering, Nanyang Technological University, Singapore</b></td><td>('1965812', 'Chongyu Chen', 'chongyu chen')<br/>('40643777', 'Luc N. Dao', 'luc n. dao')<br/>('1736042', 'Vladimir Pavlovic', 'vladimir pavlovic')<br/>('1688642', 'Jianfei Cai', 'jianfei cai')<br/>('1775268', 'Tat-Jen Cham', 'tat-jen cham')</td><td>{hxp1,vladimir}@cs.rutgers.edu <br/>{nldao,asjfcai,astfcham}@ntu.edu.sg <br/>cscychen@comp.polyu.edu.hk -</td></tr><tr><td>488375ae857a424febed7c0347cc9590989f01f7</td><td>Convolutional neural networks for the analysis of broadcasted +</td></tr><tr><td>48a5b6ee60475b18411a910c6084b3a32147b8cd</td><td>Pedestrian attribute recognition with part-based CNN +<br/>and combined feature representations +<br/>Baskurt +<br/>To cite this version: +<br/>recognition with part-based CNN and combined feature representations. VISAPP2018, Jan 2018, +<br/>Funchal, Portugal. <hal-01625470> +<br/>HAL Id: hal-01625470 +<br/>https://hal.archives-ouvertes.fr/hal-01625470 +<br/>Submitted on 21 Jun 2018 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destinée au dépôt et à la diffusion de documents +<br/>scientifiques de niveau recherche, publiés ou non, +<br/>émanant des établissements d’enseignement et de +<br/>recherche français ou étrangers, des laboratoires +<br/>publics ou privés. +</td><td>('1705461', 'Yiqiang Chen', 'yiqiang chen')<br/>('1762557', 'Stefan Duffner', 'stefan duffner')<br/>('10469201', 'Andrei Stoian', 'andrei stoian')<br/>('1733569', 'Jean-Yves Dufour', 'jean-yves dufour')<br/>('1705461', 'Yiqiang Chen', 'yiqiang chen')<br/>('1762557', 'Stefan Duffner', 'stefan duffner')<br/>('10469201', 'Andrei Stoian', 'andrei stoian')<br/>('1733569', 'Jean-Yves Dufour', 'jean-yves dufour')<br/>('1739898', 'Atilla Baskurt', 'atilla baskurt')</td><td></td></tr><tr><td>488375ae857a424febed7c0347cc9590989f01f7</td><td>Convolutional neural networks for the analysis of broadcasted <br/>tennis games <br/><b>Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH), Crete, 73100, Greece</b><br/>(cid:63) NantVision Inc., Culver City, CA, 90230, USA. <br/><b>University of Crete, Crete, 73100, Greece</b></td><td>('2272443', 'Grigorios Tsagkatakis', 'grigorios tsagkatakis')<br/>('40495798', 'Mustafa Jaber', 'mustafa jaber')<br/>('1694755', 'Panagiotis Tsakalides', 'panagiotis tsakalides')</td><td></td></tr><tr><td>4836b084a583d2e794eb6a94982ea30d7990f663</td><td>Cascaded Face Alignment via Intimacy Definition Feature @@ -31991,6 +41135,9 @@ </td><td>('1913846', 'Abdullah Gubbi', 'abdullah gubbi')<br/>('2093112', 'Mohammad Fazle Azeem', 'mohammad fazle azeem')</td><td>Nadupadavu, Mangalore, India, Contact: abdullahgubbi@yahoo.com <br/>University, India, Contact: mf.azeem@gmail.com <br/>Mangalore, India. Contact: sharmilabp@gmail.com +</td></tr><tr><td>4896909796f9bd2f70a2cb24bf18daacd6a12128</td><td>Spatial Bag of Features Learning for Large Scale +<br/>Face Image Retrieval +<br/><b>Aristotle University of Thessaloniki, Thessaloniki, Greece</b></td><td>('3200630', 'Nikolaos Passalis', 'nikolaos passalis')<br/>('1737071', 'Anastasios Tefas', 'anastasios tefas')</td><td>passalis@csd.auth.gr, tefas@aiia.csd.auth.gr </td></tr><tr><td>48cfc5789c246c6ad88ff841701204fc9d6577ed</td><td>J Inf Process Syst, Vol.12, No.3, pp.392~409, September 2016 <br/> <br/> @@ -32008,7 +41155,15 @@ <br/><b>Shaheed Zulfikar Ali Bhutto Institute of</b><br/>Science and Technology, Plot # 67, Street # 9, H/8-4 Islamabad, 44000, Pakistan <br/>isb.edu.pk </td><td>('35332495', 'Sajid Ali Khan', 'sajid ali khan')<br/>('1723986', 'Muhammad Nazir', 'muhammad nazir')<br/>('2521631', 'Naveed Riaz', 'naveed riaz')</td><td>sajid.ali@szabist-isb.edu.pk, nazir@szabist-isb.edu.pk, n.r.ansari@szabist- -</td></tr><tr><td>703890b7a50d6535900a5883e8d2a6813ead3a03</td><td></td><td></td><td></td></tr><tr><td>70db3a0d2ca8a797153cc68506b8650908cb0ada</td><td>An Overview of Research Activities in Facial +</td></tr><tr><td>70109c670471db2e0ede3842cbb58ba6be804561</td><td>Noname manuscript No. +<br/>(will be inserted by the editor) +<br/>Zero-Shot Visual Recognition via Bidirectional Latent Embedding +<br/>Received: date / Accepted: date +</td><td>('47599321', 'Qian Wang', 'qian wang')</td><td></td></tr><tr><td>703890b7a50d6535900a5883e8d2a6813ead3a03</td><td></td><td></td><td></td></tr><tr><td>703dc33736939f88625227e38367cfb2a65319fe</td><td>Labeling Temporal Bounds for Object Interactions in Egocentric Video +<br/>Trespassing the Boundaries: +<br/><b>University of Bristol, United Kingdom</b><br/>Walterio Mayol-Cuevas +</td><td>('3420479', 'Davide Moltisanti', 'davide moltisanti')<br/>('2052236', 'Michael Wray', 'michael wray')<br/>('1728459', 'Dima Damen', 'dima damen')</td><td><FirstName>.<LastName>@bristol.ac.uk +</td></tr><tr><td>70db3a0d2ca8a797153cc68506b8650908cb0ada</td><td>An Overview of Research Activities in Facial <br/>Age Estimation Using the FG-NET Aging <br/>Database <br/>Visual Media Computing Lab, @@ -32028,6 +41183,10 @@ </td><td>('1801452', 'Daniel McDuff', 'daniel mcduff')<br/>('1754451', 'Rana El Kaliouby', 'rana el kaliouby')</td><td>djmcduff@media.mit.edu <br/>kaliouby@media.mit.edu <br/>picard@media.mit.edu +</td></tr><tr><td>701f56f0eac9f88387de1f556acef78016b05d52</td><td>Direct Shape Regression Networks for End-to-End Face Alignment +<br/>1 ∗ +<br/><b>University of Texas at Arlington, TX, USA, 2Beihang University, Beijing, China</b><br/><b>Xidian University, Xi an, China, 4 University of Pittsburgh, PA, USA</b></td><td>('6050999', 'Xin Miao', 'xin miao')<br/>('34798935', 'Xiantong Zhen', 'xiantong zhen')<br/>('1720747', 'Vassilis Athitsos', 'vassilis athitsos')<br/>('6820648', 'Xianglong Liu', 'xianglong liu')<br/>('1748032', 'Heng Huang', 'heng huang')<br/>('50542664', 'Cheng Deng', 'cheng deng')</td><td>xin.miao@mavs.uta.edu, zhenxt@gmail.com, xlliu@nlsde.edu.cn, chdeng.xd@gmail.com +<br/>athitsos@uta.edu, heng.huang@pitt.edu </td></tr><tr><td>7002d6fc3e0453320da5c863a70dbb598415e7aa</td><td>Electrical Engineering <br/><b>University of California, Riverside</b><br/>Date: Friday, October 21, 2011 <br/>Location: EBU2 Room 205/206 @@ -32037,12 +41196,23 @@ <br/>Avatar Image </td><td>('1803478', 'Songfan Yang', 'songfan yang')</td><td></td></tr><tr><td>7071cd1ee46db4bc1824c4fd62d36f6d13cad08a</td><td>Face Detection through Scale-Friendly Deep Convolutional Networks <br/><b>The Chinese University of Hong Kong</b></td><td>('1692609', 'Shuo Yang', 'shuo yang')<br/>('3331521', 'Yuanjun Xiong', 'yuanjun xiong')<br/>('1717179', 'Chen Change Loy', 'chen change loy')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{ys014, yjxiong, ccloy, xtang}@ie.cuhk,edu.hk +</td></tr><tr><td>706b9767a444de4fe153b2f3bff29df7674c3161</td><td>Fast Metric Learning For Deep Neural Networks +<br/><b>University of Waikato, Hamilton, New Zealand</b><br/><b>School of Engineering, University of Waikato, Hamilton, New Zealand</b></td><td>('2319565', 'Henry Gouk', 'henry gouk')<br/>('1737420', 'Bernhard Pfahringer', 'bernhard pfahringer')</td><td>hgrg1@students.waikato.ac.nz, bernhard@waikato.ac.nz +<br/>cree@waikato.ac.nz +</td></tr><tr><td>70c58700eb89368e66a8f0d3fc54f32f69d423e1</td><td>INCORPORATING SCALABILITY IN UNSUPERVISED SPATIO-TEMPORAL FEATURE +<br/>LEARNING +<br/><b>University of California, Riverside, CA</b></td><td>('49616225', 'Sujoy Paul', 'sujoy paul')<br/>('2177805', 'Sourya Roy', 'sourya roy')<br/>('1688416', 'Amit K. Roy-Chowdhury', 'amit k. roy-chowdhury')</td><td></td></tr><tr><td>707a542c580bcbf3a5a75cce2df80d75990853cc</td><td>Disentangled Variational Representation for Heterogeneous Face Recognition +<br/>1 Center for Research on Intelligent Perception and Computing (CRIPAC), CASIA, Beijing, China +<br/>2 National Laboratory of Pattern Recognition (NLPR), CASIA, Beijing, China +<br/><b>School of Arti cial Intelligence, University of Chinese Academy of Sciences, Beijing, China</b><br/><b>Johns Hopkins University, 3400 N. Charles St, Baltimore, MD 21218, USA</b></td><td>('2225749', 'Xiang Wu', 'xiang wu')<br/>('32885778', 'Huaibo Huang', 'huaibo huang')<br/>('1741177', 'Vishal M. Patel', 'vishal m. patel')<br/>('1705643', 'Ran He', 'ran he')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>alfredxiangwu@gmail.com, huaibo.huang@cripac.ia.ac.cn, +<br/>vpatel36@jhu.edu, {rhe, znsun}@nlpr.ia.ac.cn </td></tr><tr><td>70569810e46f476515fce80a602a210f8d9a2b95</td><td>Apparent Age Estimation from Face Images Combining General and <br/>Children-Specialized Deep Learning Models <br/>1Orange Labs – France Telecom, 4 rue Clos Courtel, 35512 Cesson-S´evign´e, France <br/>2Eurecom, 450 route des Chappes, 06410 Biot, France </td><td>('3116433', 'Grigory Antipov', 'grigory antipov')<br/>('2341854', 'Moez Baccouche', 'moez baccouche')<br/>('1708844', 'Sid-Ahmed Berrani', 'sid-ahmed berrani')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td>{grigory.antipov,moez.baccouche,sidahmed.berrani}@orange.com, jean-luc.dugelay@eurecom.fr -</td></tr><tr><td>70e79d7b64f5540d309465620b0dab19d9520df1</td><td>International Journal of Scientific & Engineering Research, Volume 8, Issue 3, March-2017 +</td></tr><tr><td>704d88168bdfabe31b6ff484507f4a2244b8c52b</td><td>MLtuner: System Support for Automatic Machine Learning Tuning +<br/><b>Carnegie Mellon University</b></td><td>('1874200', 'Henggang Cui', 'henggang cui')<br/>('1707164', 'Gregory R. Ganger', 'gregory r. ganger')<br/>('1974678', 'Phillip B. Gibbons', 'phillip b. gibbons')</td><td></td></tr><tr><td>70e79d7b64f5540d309465620b0dab19d9520df1</td><td>International Journal of Scientific & Engineering Research, Volume 8, Issue 3, March-2017 <br/>ISSN 2229-5518 <br/>Facial Expression Recognition System <br/>Using Extreme Learning Machine @@ -32068,7 +41238,14 @@ <br/>Department of Intelligent Systems <br/>TU Delft <br/>Delft, The Netherlands -</td><td>('3137870', 'Christina Katsimerou', 'christina katsimerou')<br/>('1728396', 'Ingrid Heynderickx', 'ingrid heynderickx')</td><td></td></tr><tr><td>1e5ca4183929929a4e6f09b1e1d54823b8217b8e</td><td>Classification in the Presence of Heavy +</td><td>('3137870', 'Christina Katsimerou', 'christina katsimerou')<br/>('1728396', 'Ingrid Heynderickx', 'ingrid heynderickx')</td><td></td></tr><tr><td>70c9d11cad12dc1692a4507a97f50311f1689dbf</td><td>Video Frame Synthesis using Deep Voxel Flow +<br/><b>The Chinese University of Hong Kong</b><br/>3Pony.AI Inc. +<br/><b>University of Illinois at Urbana-Champaign</b><br/>4Google Inc. +</td><td>('3243969', 'Ziwei Liu', 'ziwei liu')</td><td>{lz013,xtang}@ie.cuhk.edu.hk +<br/>yiming@pony.ai +<br/>yeh17@illinois.edu +<br/>aseemaa@google.com +</td></tr><tr><td>1e5ca4183929929a4e6f09b1e1d54823b8217b8e</td><td>Classification in the Presence of Heavy <br/>Label Noise: A Markov Chain Sampling <br/>Framework <br/>by @@ -32115,7 +41292,15 @@ </td></tr><tr><td>1e8eee51fd3bf7a9570d6ee6aa9a09454254689d</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TPAMI.2016.2582166, IEEE <br/>Transactions on Pattern Analysis and Machine Intelligence <br/>Face Search at Scale -</td><td>('7496032', 'Dayong Wang', 'dayong wang')<br/>('40653304', 'Charles Otto', 'charles otto')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>1ea8085fe1c79d12adffb02bd157b54d799568e4</td><td></td><td></td><td></td></tr><tr><td>1ebdfceebad642299e573a8995bc5ed1fad173e3</td><td></td><td></td><td></td></tr><tr><td>1eec03527703114d15e98ef9e55bee5d6eeba736</td><td>UNIVERSITÄT KARLSRUHE (TH) +</td><td>('7496032', 'Dayong Wang', 'dayong wang')<br/>('40653304', 'Charles Otto', 'charles otto')<br/>('6680444', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>1ea8085fe1c79d12adffb02bd157b54d799568e4</td><td></td><td></td><td></td></tr><tr><td>1ea74780d529a458123a08250d8fa6ef1da47a25</td><td>Videos from the 2013 Boston Marathon: +<br/>An Event Reconstruction Dataset for +<br/>Synchronization and Localization +<br/>CMU-LTI-018 +<br/><b>Language Technologies Institute</b><br/>School of Computer Science +<br/><b>Carnegie Mellon University</b><br/>5000 Forbes Ave., Pittsburgh, PA 15213 +<br/>www.lti.cs.cmu.edu +<br/>© October 1, 2016 +</td><td>('49252656', 'Jia Chen', 'jia chen')<br/>('1915796', 'Junwei Liang', 'junwei liang')<br/>('47896638', 'Han Lu', 'han lu')<br/>('2927024', 'Shoou-I Yu', 'shoou-i yu')<br/>('7661726', 'Alexander G. Hauptmann', 'alexander g. hauptmann')</td><td></td></tr><tr><td>1ebdfceebad642299e573a8995bc5ed1fad173e3</td><td></td><td></td><td></td></tr><tr><td>1eec03527703114d15e98ef9e55bee5d6eeba736</td><td>UNIVERSITÄT KARLSRUHE (TH) <br/>FAKULTÄT FÜR INFORMATIK <br/>INTERACTIVE SYSTEMS LABS <br/>DIPLOMA THESIS @@ -32142,6 +41327,14 @@ <br/>Department of Statistics <br/><b>Florida State University</b><br/><b>National Institutes of Health</b></td><td>('2455529', 'Adrian Barbu', 'adrian barbu')<br/>('2230628', 'Nathan Lay', 'nathan lay')</td><td>abarbu@stat.fsu.edu <br/>nathan.lay@nih.gov +</td></tr><tr><td>1efacaa0eaa7e16146c34cd20814d1411b35538e</td><td>HEIDARIVINCHEHET AL: ACTIONCOMPLETION:A TEMPORALMODEL.. +<br/>Action Completion: +<br/>A Temporal Model for Moment Detection +<br/>Department of Computer Science +<br/><b>University of Bristol</b><br/>Bristol, UK +</td><td>('10007321', 'Farnoosh Heidarivincheh', 'farnoosh heidarivincheh')<br/>('1728108', 'Majid Mirmehdi', 'majid mirmehdi')<br/>('1728459', 'Dima Damen', 'dima damen')</td><td>Farnoosh.Heidarivincheh@bristol.ac.uk +<br/>M.Mirmehdi@bristol.ac.uk +<br/>Dima.Damen@bristol.ac.uk </td></tr><tr><td>1eba6fc35a027134aa8997413647b49685f6fbd1</td><td>Superpower Glass: Delivering <br/>Unobtrusive Real-time Social Cues <br/>in Wearable Systems @@ -32174,6 +41367,15 @@ </td><td>('3131569', 'Haoxiang Li', 'haoxiang li')<br/>('1721019', 'Jonathan Brandt', 'jonathan brandt')<br/>('1720987', 'Xiaohui Shen', 'xiaohui shen')<br/>('1745420', 'Gang Hua', 'gang hua')</td><td>†hli18@stevens.edu <br/>‡{jbrandt, zlin, xshen}@adobe.com <br/>(cid:92)ganghua@microsoft.com +</td></tr><tr><td>1ef1f33c48bc159881c5c8536cbbd533d31b0e9a</td><td>Z. ZHANG ET AL.: ADVERSARIAL TRAINING FOR ACTION UNIT RECOGNITION +<br/>Identity-based Adversarial Training of Deep +<br/>CNNs for Facial Action Unit Recognition +<br/>Department of Computer Science +<br/><b>State University of New York at</b><br/>Binghamton +<br/>NY, USA. +</td><td>('47294008', 'Zheng Zhang', 'zheng zhang')<br/>('2443456', 'Shuangfei Zhai', 'shuangfei zhai')<br/>('8072251', 'Lijun Yin', 'lijun yin')</td><td>zzhang27@cs.binghamton.edu +<br/>szhai2@cs.binghamton.edu +<br/>lijun@cs.binghamton.edu </td></tr><tr><td>1ef5ce743a44d8a454dbfc2657e1e2e2d025e366</td><td>Global Journal of Computer Science & Technology <br/>Volume 11 Issue Version 1.0 April 2011 <br/>Type: Double Blind Peer Reviewed International Research Journal @@ -32302,7 +41504,12 @@ <br/>EXPRESSION RECOGNITION <br/>USING C-SUPPORT VECTOR <br/>CLASSIFICATION -</td><td>('19172816', 'Christer Loob', 'christer loob')<br/>('2303909', 'Pejman Rasti', 'pejman rasti')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('2531522', 'Tomasz Sapinski', 'tomasz sapinski')<br/>('34969391', 'Dorota Kaminska', 'dorota kaminska')<br/>('3087532', 'Gholamreza Anbarjafari', 'gholamreza anbarjafari')</td><td></td></tr><tr><td>1ee27c66fabde8ffe90bd2f4ccee5835f8dedbb9</td><td>Entropy Regularization +</td><td>('19172816', 'Christer Loob', 'christer loob')<br/>('2303909', 'Pejman Rasti', 'pejman rasti')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('2531522', 'Tomasz Sapinski', 'tomasz sapinski')<br/>('34969391', 'Dorota Kaminska', 'dorota kaminska')<br/>('3087532', 'Gholamreza Anbarjafari', 'gholamreza anbarjafari')</td><td></td></tr><tr><td>1e21b925b65303ef0299af65e018ec1e1b9b8d60</td><td>Under review as a conference paper at ICLR 2017 +<br/>UNSUPERVISED CROSS-DOMAIN IMAGE GENERATION +<br/>Facebook AI Research +<br/>Tel-Aviv, Israel +</td><td>('2188620', 'Yaniv Taigman', 'yaniv taigman')<br/>('33964593', 'Adam Polyak', 'adam polyak')</td><td>{yaniv,adampolyak,wolf}@fb.com +</td></tr><tr><td>1ee27c66fabde8ffe90bd2f4ccee5835f8dedbb9</td><td>Entropy Regularization <br/>The problem of semi-supervised induction consists in learning a decision rule from <br/>labeled and unlabeled data. This task can be undertaken by discriminative methods, <br/>provided that learning criteria are adapted consequently. In this chapter, we moti- @@ -32330,7 +41537,27 @@ <br/>examples. The problem di(cid:11)ers in the respect that the supervisor’s responses are <br/>missing for some training examples. This characteristic is shared with transduction, <br/>which has however a di(cid:11)erent goal, that is, of predicting labels on a set of prede(cid:12)ned -</td><td>('1802711', 'Yves Grandvalet', 'yves grandvalet')<br/>('1751762', 'Yoshua Bengio', 'yoshua bengio')</td><td></td></tr><tr><td>1e41a3fdaac9f306c0ef0a978ae050d884d77d2a</td><td>411 +</td><td>('1802711', 'Yves Grandvalet', 'yves grandvalet')<br/>('1751762', 'Yoshua Bengio', 'yoshua bengio')</td><td></td></tr><tr><td>1ee3b4ba04e54bfbacba94d54bf8d05fd202931d</td><td>Indonesian Journal of Electrical Engineering and Computer Science +<br/>Vol. 12, No. 2, November 2018, pp. 476~481 +<br/>ISSN: 2502-4752, DOI: 10.11591/ijeecs.v12.i2.pp476-481 +<br/> 476 +<br/>Celebrity Face Recognition using Deep Learning +<br/>1,2,3Faculty of Computer and Mathematical Sciences, UniversitiTeknologi MARA (UiTM), +<br/>4Faculty of Computer and Mathematical Sciences, UniversitiTeknologi MARA (UiTM), +<br/> Shah Alam, Selangor, Malaysia +<br/>Campus Jasin, Melaka, Malaysia +<br/>Article Info +<br/>Article history: +<br/>Received May 29, 2018 +<br/>Revised Jul 30, 2018 +<br/>Accepted Aug 3, 2018 +<br/>Keywords: +<br/>AlexNet +<br/>Convolutional neural network +<br/>Deep learning +<br/>Face recognition +<br/>GoogLeNet +</td><td>('2743254', 'Zaidah Ibrahim', 'zaidah ibrahim')</td><td></td></tr><tr><td>1e41a3fdaac9f306c0ef0a978ae050d884d77d2a</td><td>411 <br/>Robust Object Recognition with <br/>Cortex-Like Mechanisms <br/>Tomaso Poggio, Member, IEEE @@ -32340,7 +41567,10 @@ <br/>VALWAY Technology Center, NEC Soft, Ltd., Tokyo, Japan <br/>Keywords: </td><td>('2163491', 'Kazuya Ueki', 'kazuya ueki')<br/>('1719221', 'Masashi Sugiyama', 'masashi sugiyama')</td><td>ueki@mxf.nes.nec.co.jp -</td></tr><tr><td>1e8eec6fc0e4538e21909ab6037c228547a678ba</td><td><b>IMPERIAL COLLEGE</b><br/><b>University of London</b><br/>enVisage : Face Recognition in +</td></tr><tr><td>1efaa128378f988965841eb3f49d1319a102dc36</td><td>JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 +<br/>Hierarchical binary CNNs for landmark +<br/>localization with limited resources +</td><td>('3458121', 'Adrian Bulat', 'adrian bulat')<br/>('2610880', 'Georgios Tzimiropoulos', 'georgios tzimiropoulos')</td><td></td></tr><tr><td>1e8eec6fc0e4538e21909ab6037c228547a678ba</td><td><b>IMPERIAL COLLEGE</b><br/><b>University of London</b><br/>enVisage : Face Recognition in <br/>Videos <br/>Supervisor : Dr. Stefan Rüeger <br/>June 14, 2006 @@ -32348,7 +41578,30 @@ </td></tr><tr><td>1e6ed6ca8209340573a5e907a6e2e546a3bf2d28</td><td>Pooling Faces: Template based Face Recognition with Pooled Face Images <br/>Prem Natarajan1 <br/>Gérard Medioni3 -<br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b><br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b></td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')<br/>('5911467', 'Jungyeon Kim', 'jungyeon kim')<br/>('1689391', 'Jongmoo Choi', 'jongmoo choi')<br/>('35840854', 'Shai Harel', 'shai harel')</td><td></td></tr><tr><td>84fe5b4ac805af63206012d29523a1e033bc827e</td><td></td><td></td><td></td></tr><tr><td>84e4b7469f9c4b6c9e73733fa28788730fd30379</td><td>Duong et al. EURASIP Journal on Advances in Signal Processing (2018) 2018:10 +<br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b><br/><b>Institute for Robotics and Intelligent Systems, USC, CA, USA</b></td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('11269472', 'Iacopo Masi', 'iacopo masi')<br/>('5911467', 'Jungyeon Kim', 'jungyeon kim')<br/>('1689391', 'Jongmoo Choi', 'jongmoo choi')<br/>('35840854', 'Shai Harel', 'shai harel')</td><td></td></tr><tr><td>8451bf3dd6bcd946be14b1a75af8bbb65a42d4b2</td><td>Consensual and Privacy-Preserving Sharing of +<br/>Multi-Subject and Interdependent Data +<br/>EPFL, UNIL–HEC Lausanne +<br/>K´evin Huguenin +<br/>UNIL–HEC Lausanne +<br/>EPFL +<br/>EPFL +</td><td>('1862343', 'Alexandra-Mihaela Olteanu', 'alexandra-mihaela olteanu')<br/>('2461431', 'Italo Dacosta', 'italo dacosta')<br/>('1757221', 'Jean-Pierre Hubaux', 'jean-pierre hubaux')</td><td>alexandramihaela.olteanu@epfl.ch +<br/>kevin.huguenin@unil.ch +<br/>italo.dacosta@epfl.ch +<br/>jean-pierre.hubaux@epfl.ch +</td></tr><tr><td>841855205818d3a6d6f85ec17a22515f4f062882</td><td>Low Resolution Face Recognition in the Wild +<br/>Patrick Flynn1 +<br/>1Department of Computer Science and Engineering +<br/><b>University of Notre Dame</b><br/>2Department of Computer Science +<br/>Pontificia Universidad Cat´olica de Chile +</td><td>('50492554', 'Pei Li', 'pei li')<br/>('47522390', 'Loreto Prieto', 'loreto prieto')<br/>('1797475', 'Domingo Mery', 'domingo mery')</td><td></td></tr><tr><td>84c0f814951b80c3b2e39caf3925b56a9b2e1733</td><td>Manifesto from Dagstuhl Perspectives Workshop 12382 +<br/>Computation and Palaeography: Potentials and Limits∗ +<br/>Edited by +<br/><b>The Open University of</b><br/><b>University of Nebraska Lincoln, USA</b><br/><b>King s College London, UK</b><br/><b>The Blavatnik School of Computer Science, Tel Aviv University, IL</b></td><td>('1756099', 'Tal Hassner', 'tal hassner')<br/>('34564710', 'Malte Rehbein', 'malte rehbein')<br/>('34876976', 'Peter A. Stokes', 'peter a. stokes')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td>Israel, IL, hassner@openu.ac.il +<br/>malte.rehbein@unl.edu +<br/>peter.stokes@kcl.ac.uk +<br/>wolf@cs.tau.ac.il +</td></tr><tr><td>84fe5b4ac805af63206012d29523a1e033bc827e</td><td></td><td></td><td></td></tr><tr><td>84e4b7469f9c4b6c9e73733fa28788730fd30379</td><td>Duong et al. EURASIP Journal on Advances in Signal Processing (2018) 2018:10 <br/>DOI 10.1186/s13634-017-0521-9 <br/>EURASIP Journal on Advances <br/>in Signal Processing @@ -32367,6 +41620,13 @@ <br/>Usage of affective computing in recommender systems <br/>Marko Tkalˇciˇc, Andrej Koˇsir, Jurij Tasiˇc <br/><b>University of Ljubljana, Faculty of Electrical Engineering, Trzaska 25, 1000 Ljubljana, Slovenia</b></td><td></td><td>E-mail: marko.tkalcic@fe.uni-lj.si +</td></tr><tr><td>84fa126cb19d569d2f0147bf6f9e26b54c9ad4f1</td><td>Improved Boosting Performance by Explicit +<br/>Handling of Ambiguous Positive Examples +</td><td>('1750517', 'Miroslav Kobetski', 'miroslav kobetski')<br/>('1736906', 'Josephine Sullivan', 'josephine sullivan')</td><td></td></tr><tr><td>84508e846af3ac509f7e1d74b37709107ba48bde</td><td>Use of the Septum as a Reference Point in a Neurophysiologic Approach to +<br/>Facial Expression Recognition +<br/>Department of Computer Engineering, Faculty of Engineering, +<br/><b>Prince of Songkla University, Hat Yai, Songkhla, 90112 Thailand</b><br/>Telephone: (66)080-7045015, (66)074-287-357 +</td><td>('38928684', 'Igor Stankovic', 'igor stankovic')<br/>('2799130', 'Montri Karnjanadecha', 'montri karnjanadecha')</td><td>E-mail: bizmut@neobee.net, montri@coe.psu.ac.th </td></tr><tr><td>841a5de1d71a0b51957d9be9d9bebed33fb5d9fa</td><td>5017 <br/>PCANet: A Simple Deep Learning Baseline for <br/>Image Classification? @@ -32411,6 +41671,10 @@ </td><td>('30834050', 'Prutha Date', 'prutha date')<br/>('2116290', 'Ashwinkumar Ganesan', 'ashwinkumar ganesan')<br/>('1756624', 'Tim Oates', 'tim oates')</td><td>dprutha1@umbc.edu <br/>gashwin1@umbc.edu <br/>oates@cs.umbc.edu +</td></tr><tr><td>849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b</td><td>Detecting Faces Using Region-based Fully +<br/>Convolutional Networks +<br/>Tencent AI Lab, China +</td><td>('1996677', 'Yitong Wang', 'yitong wang')</td><td>{yitongwang,denisji,encorezhou,hawelwang,michaelzfli}@tencent.com </td></tr><tr><td>846c028643e60fefc86bae13bebd27341b87c4d1</td><td>Face Recognition Under Varying Illumination <br/>Based on MAP Estimation Incorporating <br/>Correlation Between Surface Points @@ -32444,10 +41708,20 @@ <br/>Thesis supervisors <br/>Prof. Dr. Horst Bischof <br/>Prof. Dr. Fernando De la Torre -</td><td>('1993853', 'Martin Köstinger', 'martin köstinger')</td><td></td></tr><tr><td>4a484d97e402ed0365d6cf162f5a60a4d8000ea0</td><td>A Crowdsourcing Approach for Finding Misidentifications of Bibliographic Records +</td><td>('1993853', 'Martin Köstinger', 'martin köstinger')</td><td></td></tr><tr><td>4ab84f203b0e752be83f7f213d7495b04b1c4c79</td><td>CONCAVE LOSSES FOR ROBUST DICTIONARY LEARNING +<br/><b>University of S ao Paulo</b><br/><b>Institute of Mathematics and Statistics</b><br/>Rua do Mat˜ao, 1010 – 05508-090 – S˜ao Paulo-SP, Brazil +<br/>Universit´e de Rouen Normandie +<br/>LITIS EA 4108 +<br/>76800 Saint- ´Etienne-du-Rouvray, France +</td><td>('30146203', 'Rafael Will M. de Araujo', 'rafael will m. de araujo')<br/>('1792962', 'Alain Rakotomamonjy', 'alain rakotomamonjy')</td><td></td></tr><tr><td>4a484d97e402ed0365d6cf162f5a60a4d8000ea0</td><td>A Crowdsourcing Approach for Finding Misidentifications of Bibliographic Records <br/><b>University of Tsukuba</b><br/>2 National Diet Library <br/>3 Doshisha Univeristy -</td><td>('34573158', 'Atsuyuki Morishima', 'atsuyuki morishima')<br/>('32857584', 'Takanori Kawashima', 'takanori kawashima')<br/>('23161591', 'Takashi Harada', 'takashi harada')<br/>('2406721', 'Sho Sato', 'sho sato')</td><td></td></tr><tr><td>4a4da3d1bbf10f15b448577e75112bac4861620a</td><td>FACE, EXPRESSION, AND IRIS RECOGNITION +</td><td>('34573158', 'Atsuyuki Morishima', 'atsuyuki morishima')<br/>('32857584', 'Takanori Kawashima', 'takanori kawashima')<br/>('23161591', 'Takashi Harada', 'takashi harada')<br/>('2406721', 'Sho Sato', 'sho sato')</td><td></td></tr><tr><td>4a3758f283b7c484d3f164528d73bc8667eb1591</td><td>Attribute Enhanced Face Aging with Wavelet-based Generative Adversarial +<br/>Networks +<br/>Center for Research on Intelligent Perception and Computing, CASIA +<br/>National Laboratory of Pattern Recognition, CASIA +</td><td>('1860829', 'Yunfan Liu', 'yunfan liu')<br/>('1682467', 'Qi Li', 'qi li')<br/>('1757186', 'Zhenan Sun', 'zhenan sun')</td><td>yunfan,liu@cripac.ia.ac.cn, {qli, znsun}@nlpr.ia.ac.cn +</td></tr><tr><td>4a4da3d1bbf10f15b448577e75112bac4861620a</td><td>FACE, EXPRESSION, AND IRIS RECOGNITION <br/>USING LEARNING-BASED APPROACHES <br/>by <br/>A dissertation submitted in partial fulfillment of @@ -32458,7 +41732,13 @@ <br/><b>UNIVERSITY OF WISCONSIN MADISON</b><br/>2006 </td><td>('1822413', 'Guodong Guo', 'guodong guo')</td><td></td></tr><tr><td>4abd49538d04ea5c7e6d31701b57ea17bc349412</td><td>Recognizing Fine-Grained and Composite Activities <br/>using Hand-Centric Features and Script Data -</td><td>('34849128', 'Marcus Rohrbach', 'marcus rohrbach')<br/>('40404576', 'Sikandar Amin', 'sikandar amin')</td><td></td></tr><tr><td>4a0f98d7dbc31497106d4f652968c708f7da6692</td><td>Real-time Eye Gaze Direction Classification Using +</td><td>('34849128', 'Marcus Rohrbach', 'marcus rohrbach')<br/>('40404576', 'Sikandar Amin', 'sikandar amin')</td><td></td></tr><tr><td>4aa093d1986b4ad9b073ac9edfb903f62c00e0b0</td><td>Facial Recognition with +<br/>Encoded Local Projections +<br/>Mechanincal and Mechatronics Engineering +<br/><b>University of Waterloo</b><br/>Waterloo, Canada +<br/>Kimia Lab +<br/><b>University of Waterloo</b><br/>Waterloo, Canada +</td><td>('34139904', 'Dhruv Sharma', 'dhruv sharma')<br/>('7641396', 'Sarim Zafar', 'sarim zafar')<br/>('38685017', 'Morteza Babaie', 'morteza babaie')</td><td></td></tr><tr><td>4a0f98d7dbc31497106d4f652968c708f7da6692</td><td>Real-time Eye Gaze Direction Classification Using <br/>Convolutional Neural Network </td><td>('3110004', 'Anjith George', 'anjith george')<br/>('2680543', 'Aurobinda Routray', 'aurobinda routray')</td><td></td></tr><tr><td>4aabd6db4594212019c9af89b3e66f39f3108aac</td><td><b>University of Colorado, Boulder</b><br/>CU Scholar <br/>Undergraduate Honors Theses @@ -32566,6 +41846,11 @@ <br/>Center for Automation Research (CfAR) <br/>Department of Electrical and Computer Engineering <br/><b>University of Maryland, College Park, MD</b></td><td>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{shaohua, rama}@cfar.umd.edu +</td></tr><tr><td>4ac3cd8b6c50f7a26f27eefc64855134932b39be</td><td>Robust Facial Landmark Detection +<br/>via a Fully-Convolutional Local-Global Context Network +<br/><b>Technical University of Munich</b></td><td>('3044182', 'Daniel Merget', 'daniel merget')<br/>('28096417', 'Matthias Rock', 'matthias rock')<br/>('46343645', 'Gerhard Rigoll', 'gerhard rigoll')</td><td>daniel.merget@tum.de +<br/>matthias.rock@tum.de +<br/>mmk@ei.tum.de </td></tr><tr><td>4abaebe5137d40c9fcb72711cdefdf13d9fc3e62</td><td>Dimension Reduction for Regression <br/>with Bottleneck Neural Networks <br/><b>BECS, Aalto University School of Science and Technology, Finland</b></td><td>('2504988', 'Elina Parviainen', 'elina parviainen')</td><td></td></tr><tr><td>4acd683b5f91589002e6f50885df51f48bc985f4</td><td>BRIDGING COMPUTER VISION AND SOCIAL SCIENCE : A MULTI-CAMERA VISION @@ -32583,7 +41868,9 @@ </td><td>('35220006', 'Claudio Ferrari', 'claudio ferrari')<br/>('2973738', 'Giuseppe Lisanti', 'giuseppe lisanti')<br/>('2507859', 'Stefano Berretti', 'stefano berretti')<br/>('8196487', 'Alberto Del Bimbo', 'alberto del bimbo')</td><td></td></tr><tr><td>4a6fcf714f663618657effc341ae5961784504c7</td><td>Scaling up Class-Specific Kernel Discriminant <br/>Analysis for large-scale Face Verification </td><td>('9219875', 'Moncef Gabbouj', 'moncef gabbouj')</td><td></td></tr><tr><td>24b37016fee57057cf403fe2fc3dda78476a8262</td><td>Automatic Recognition of Eye Blinking in Spontaneously Occurring Behavior -<br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b><br/><b>University of Pittsburgh, Pittsburgh</b></td><td>('1683262', 'Tsuyoshi Moriyama', 'tsuyoshi moriyama')<br/>('1724419', 'Jing Xiao', 'jing xiao')</td><td></td></tr><tr><td>24c442ac3f6802296d71b1a1914b5d44e48b4f29</td><td>Pose and expression-coherent face recovery in the wild +<br/><b>Robotics Institute, Carnegie Mellon University, Pittsburgh, PA</b><br/><b>University of Pittsburgh, Pittsburgh</b></td><td>('1683262', 'Tsuyoshi Moriyama', 'tsuyoshi moriyama')<br/>('1724419', 'Jing Xiao', 'jing xiao')</td><td></td></tr><tr><td>24115d209e0733e319e39badc5411bbfd82c5133</td><td>Long-term Recurrent Convolutional Networks for +<br/>Visual Recognition and Description +</td><td>('7408951', 'Jeff Donahue', 'jeff donahue')<br/>('2234342', 'Lisa Anne Hendricks', 'lisa anne hendricks')<br/>('34849128', 'Marcus Rohrbach', 'marcus rohrbach')<br/>('1811430', 'Subhashini Venugopalan', 'subhashini venugopalan')<br/>('1687120', 'Sergio Guadarrama', 'sergio guadarrama')<br/>('2903226', 'Kate Saenko', 'kate saenko')<br/>('1753210', 'Trevor Darrell', 'trevor darrell')</td><td></td></tr><tr><td>24c442ac3f6802296d71b1a1914b5d44e48b4f29</td><td>Pose and expression-coherent face recovery in the wild <br/>Technicolor, Cesson-S´evign´e, France <br/>Franc¸ois Le Clerc <br/>Patrick P´erez @@ -32814,10 +42101,13 @@ <br/>yichenw@microsoft.com <br/>shuangliang@tongji.edu.cn <br/>pingtan@sfu.ca +</td></tr><tr><td>24f022d807352abf071880877c38e53a98254dcd</td><td>Are screening methods useful in feature selection? An +<br/>empirical study +<br/><b>Florida State University, Tallahassee, Florida, U.S.A</b></td><td>('6693611', 'Mingyuan Wang', 'mingyuan wang')<br/>('2455529', 'Adrian Barbu', 'adrian barbu')</td><td>* abarbu@stat.fsu.edu </td></tr><tr><td>241d2c517dbc0e22d7b8698e06ace67de5f26fdf</td><td>Online, Real-Time Tracking <br/>Using a Category-to-Individual Detector(cid:2) <br/><b>California Institute of Technology, USA</b></td><td>('1990633', 'David Hall', 'david hall')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>{dhall,perona}@vision.caltech.edu -</td></tr><tr><td>24e6a28c133b7539a57896393a79d43dba46e0f6</td><td>ROBUST BAYESIAN METHOD FOR SIMULTANEOUS BLOCK SPARSE SIGNAL +</td></tr><tr><td>24869258fef8f47623b5ef43bd978a525f0af60e</td><td><b>UNIVERSITÉDEGRENOBLENoattribuéparlabibliothèqueTHÈSEpourobtenirlegradedeDOCTEURDEL’UNIVERSITÉDEGRENOBLESpécialité:MathématiquesetInformatiquepréparéeauLaboratoireJeanKuntzmanndanslecadredel’ÉcoleDoctoraleMathématiques,SciencesetTechnologiesdel’Information,InformatiqueprésentéeetsoutenuepubliquementparMatthieuGuillauminle27septembre2010ExploitingMultimodalDataforImageUnderstandingDonnéesmultimodalespourl’analysed’imageDirecteursdethèse:CordeliaSchmidetJakobVerbeekJURYM.ÉricGaussierUniversitéJosephFourierPrésidentM.AntonioTorralbaMassachusettsInstituteofTechnologyRapporteurMmeTinneTuytelaarsKatholiekeUniversiteitLeuvenRapporteurM.MarkEveringhamUniversityofLeedsExaminateurMmeCordeliaSchmidINRIAGrenobleExaminatriceM.JakobVerbeekINRIAGrenobleExaminateur</b></td><td></td><td></td></tr><tr><td>24e6a28c133b7539a57896393a79d43dba46e0f6</td><td>ROBUST BAYESIAN METHOD FOR SIMULTANEOUS BLOCK SPARSE SIGNAL <br/>RECOVERY WITH APPLICATIONS TO FACE RECOGNITION <br/>Department of Electrical and Computer Engineering <br/><b>University of California, San Diego</b></td><td>('32352411', 'Igor Fedorov', 'igor fedorov')<br/>('3291075', 'Ritwik Giri', 'ritwik giri')<br/>('1748319', 'Bhaskar D. Rao', 'bhaskar d. rao')<br/>('1690269', 'Truong Q. Nguyen', 'truong q. nguyen')</td><td></td></tr><tr><td>248db911e3a6a63ecd5ff6b7397a5d48ac15e77a</td><td>Enriching Texture Analysis with Semantic Data @@ -32849,7 +42139,10 @@ <br/>Methods Based on SVM <br/><b>Ural Federal University (UrFU</b><br/>Yekaterinburg, Russia </td><td>('11063038', 'Daniil Belkov', 'daniil belkov')<br/>('3457868', 'Konstantin Purtov', 'konstantin purtov')</td><td>d.d.belkov, k.s.purtov@gmail.com, kublanov@mail.ru -</td></tr><tr><td>247a6b0e97b9447850780fe8dbc4f94252251133</td><td>Facial Action Unit Detection: 3D versus 2D Modality +</td></tr><tr><td>24ff832171cb774087a614152c21f54589bf7523</td><td>Beat-Event Detection in Action Movie Franchises +<br/>Jerome Revaud +<br/>Zaid Harchaoui +</td><td>('2319574', 'Danila Potapov', 'danila potapov')<br/>('3271933', 'Matthijs Douze', 'matthijs douze')<br/>('2462253', 'Cordelia Schmid', 'cordelia schmid')</td><td></td></tr><tr><td>247a6b0e97b9447850780fe8dbc4f94252251133</td><td>Facial Action Unit Detection: 3D versus 2D Modality <br/>Electrical and Electronics Engineering <br/><b>Bo gazic i University, Istanbul, Turkey</b><br/>B¨ulent Sankur <br/>Electrical and Electronics Engineering @@ -32879,6 +42172,8 @@ </td><td>('3033284', 'Barbara Caputo', 'barbara caputo')<br/>('1749692', 'Vittorio Ferrari', 'vittorio ferrari')</td><td>jluo@idiap.ch <br/>bcaputo@idiap.ch <br/>ferrari@vision.ee.ethz.ch +</td></tr><tr><td>23ce6f404c504592767b8bec7d844d87b462de71</td><td>A Deep Face Identification Network Enhanced by Facial Attributes Prediction +<br/><b>West Virginia University</b></td><td>('34708406', 'Fariborz Taherkhani', 'fariborz taherkhani')<br/>('8147588', 'Nasser M. Nasrabadi', 'nasser m. nasrabadi')</td><td>ft0009@mix.wvu.edu, nasser.nasrabadi@mail.wvu.edu, Jeremy.Dawson@mail.wvu.edu </td></tr><tr><td>23fd653b094c7e4591a95506416a72aeb50a32b5</td><td>Emotion Recognition using Fuzzy Rule-based System <br/>International Journal of Computer Applications (0975 – 8887) <br/>Volume 93 – No.11, May 2014 @@ -33013,7 +42308,19 @@ <br/>formulated as <br/>(x, y) = A(x, y) × L(x, y) <br/>(1) -</td><td>('1688667', 'Chuan-Xian Ren', 'chuan-xian ren')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1726138', 'Dao-Qing Dai', 'dao-qing dai')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td></td></tr><tr><td>23e75f5ce7e73714b63f036d6247fa0172d97cb6</td><td>BioMed Central +</td><td>('1688667', 'Chuan-Xian Ren', 'chuan-xian ren')<br/>('1718623', 'Zhen Lei', 'zhen lei')<br/>('1726138', 'Dao-Qing Dai', 'dao-qing dai')<br/>('34679741', 'Stan Z. Li', 'stan z. li')</td><td></td></tr><tr><td>2322ec2f3571e0ddc593c4e2237a6a794c61251d</td><td>Jack, R. E. , Sun, W., Delis, I., Garrod, O. G. B. and Schyns, P. G. (2016) +<br/>Four not six: revealing culturally common facial expressions of +<br/>emotion.Journal of Experimental Psychology: General, 145(6), pp. 708- +<br/>730. (doi:10.1037/xge0000162) +<br/>This is the author’s final accepted version. +<br/>There may be differences between this version and the published version. +<br/>You are advised to consult the publisher’s version if you wish to cite from +<br/>it. +<br/>http://eprints.gla.ac.uk/116592/ +<br/> +<br/>Deposited on: 20 April 2016 +<br/><b>Enlighten Research publications by members of the University of Glasgow</b><br/>http://eprints.gla.ac.uk +</td><td></td><td></td></tr><tr><td>23e75f5ce7e73714b63f036d6247fa0172d97cb6</td><td>BioMed Central <br/>Research <br/>Facial expression (mood) recognition from facial images using <br/>committee neural networks @@ -33028,6 +42335,10 @@ <br/>This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), <br/>which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. </td><td>('39890387', 'Saket S Kulkarni', 'saket s kulkarni')<br/>('2484370', 'Narender P Reddy', 'narender p reddy')<br/>('32173165', 'SI Hariharan', 'si hariharan')</td><td>Email: Saket S Kulkarni - saketkulkarni@gmail.com; Narender P Reddy* - npreddy@uakron.edu; SI Hariharan - hari@uakron.edu +</td></tr><tr><td>23429ef60e7a9c0e2f4d81ed1b4e47cc2616522f</td><td>A Domain Based Approach to Social Relation Recognition +<br/><b>Max Planck Institute for Informatics, Saarland Informatics Campus</b><br/>Figure 1: We investigate the recognition of social relations in a domain-based approach. Our study is based on Bugental’s +<br/>social psychology theory [1] that partitions social life into 5 domains from which we derive 16 social relations. +</td><td>('32222907', 'Qianru Sun', 'qianru sun')<br/>('1697100', 'Bernt Schiele', 'bernt schiele')<br/>('1739548', 'Mario Fritz', 'mario fritz')</td><td>{qsun, schiele, mfritz}@mpi-inf.mpg.de </td></tr><tr><td>23aba7b878544004b5dfa64f649697d9f082b0cf</td><td>Locality-Constrained Discriminative Learning and Coding <br/>1Department of Electrical & Computer Engineering, <br/><b>College of Computer and Information Science</b><br/><b>Northeastern University, Boston, MA, USA</b></td><td>('7489165', 'Shuyang Wang', 'shuyang wang')<br/>('37771688', 'Yun Fu', 'yun fu')</td><td>{shuyangwang, yunfu}@ece.neu.edu @@ -33054,6 +42365,10 @@ <br/>the work immediately and investigate your claim. <br/>Downloaded from vbn.aau.dk on: October 11, 2016 <br/> </td><td>('7855312', 'Sergio Escalera', 'sergio escalera')</td><td>If you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access to +</td></tr><tr><td>2303d07d839e8b20f33d6e2ec78d1353cac256cf</td><td>Squeeze-and-Excitation on Spatial and Temporal +<br/>Deep Feature Space for Action Recognition +<br/><b>Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China</b><br/>Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing 100044, China +</td><td>('2896701', 'Gaoyun An', 'gaoyun an')<br/>('3027947', 'Wen Zhou', 'wen zhou')<br/>('47095962', 'Yuxuan Wu', 'yuxuan wu')<br/>('4464686', 'ZhenXing Zheng', 'zhenxing zheng')<br/>('46398737', 'Yongwen Liu', 'yongwen liu')</td><td>Email:{gyan, 16125155, 16120307, zhxzheng, 17120314}@bjtu.edu.cn </td></tr><tr><td>23d55061f7baf2ffa1c847d356d8f76d78ebc8c1</td><td>Solmaz et al. IPSJ Transactions on Computer Vision and <br/>Applications (2017) 9:22 <br/>DOI 10.1186/s41074-017-0033-4 @@ -33122,15 +42437,136 @@ <br/>layer-by-layer and normally higher layers represent higher-level concept ab- <br/>stractions. Both of the two network paths share the same architecture, e.g., <br/>the same number of convolutional filters and number of middle layers. This -</td><td>('35370244', 'Qiang Chen', 'qiang chen')<br/>('1753492', 'Junshi Huang', 'junshi huang')<br/>('2106286', 'Jian Dong', 'jian dong')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>23a8d02389805854cf41c9e5fa56c66ee4160ce3</td><td>Multimed Tools Appl +</td><td>('35370244', 'Qiang Chen', 'qiang chen')<br/>('1753492', 'Junshi Huang', 'junshi huang')<br/>('2106286', 'Jian Dong', 'jian dong')<br/>('1698982', 'Shuicheng Yan', 'shuicheng yan')</td><td></td></tr><tr><td>23dd8d17ce09c22d367e4d62c1ccf507bcbc64da</td><td>Deep Density Clustering of Unconstrained Faces +<br/>(Supplementary Material) +<br/><b>University of Maryland, College Park</b><br/>A. Mathematical Details +<br/>Let S = {i | 0 < αi < C}. We have the following results: +<br/>nV(cid:88) +<br/>nV(cid:88) +<br/>i=1 +<br/>c∗ = +<br/>w∗ = +<br/>αiΨθ(xi), +<br/>¯R∗ = (cid:107)Ψθ(xs) − c∗(cid:107)2 , +<br/>αiΨθ(xi), +<br/>ρ∗ = w∗T Ψθ(xs), +<br/>where s ∈ S. Substituting into (3) and (4), we obtain +<br/>hSVDD(x) = 2 · hOC-SVM(x) = 2 +<br/>αiK(xi, x) − ρ∗ +<br/>(cid:34) nV(cid:88) +<br/>i=1 +<br/>(1) +<br/>(2) +<br/>(5) +<br/>(6) +<br/>(cid:35) +<br/>(7) +<br/>A.2. Proof of Theorem 1 +<br/>Theorem 1. If 1/nV < ν ≤ 1 and c∗T Ψθ(xs) (cid:54)= 0 for +<br/>some support vector xs, hSVDD(x) defined in (3) is asymp- +<br/>totically a Parzen window density estimator in the feature +<br/>space with Epanechnikov kernel. +<br/>Proof. Given the condition, according to Lemma 1, +<br/>hSVDD(x) is equivalent to hOC-SVM(x) with ρ∗ (cid:54)= 0. From +<br/>the results in [10] and the fact that(cid:80) αi = 1, we obtain: +<br/>(cid:21) +<br/>(cid:20) +<br/>hOC-SVM(x) = +<br/>αi +<br/>1 − 1 +<br/>(cid:107)Ψθ(x) − Ψθ(xi)(cid:107)2 +<br/>(cid:18)(cid:107)Ψθ(x) − Ψθ(xi)(cid:107) +<br/>(cid:19) +<br/>− ρ∗ +<br/>− ρ∗ − 1, +<br/>αiKE +<br/>nV(cid:88) +<br/>nV(cid:88) +<br/>i=1 +<br/>i=1 +<br/>4 (1 − u2), |u| ≤ 1 is the Epanechnikov +<br/>where KE(u) = 3 +<br/>kernel. As a consequence of Proposition 4 in [10] and the +<br/>proof of Proposition 1 in [11], as nV → ∞, the fraction +<br/>of support vector is ν, and the fraction of points with 0 < +<br/>αi < 1/(ν · nV ) vanishes. Therefore, either αi = 0 or +<br/>αi = 1/(ν · nV ). We introduce the notation ¯S = {i | αi = +<br/>ξ(z) +<br/>i=1 +<br/>In this section, we first provide the two core mathe- +<br/>matical formulations and then present detailed proofs for +<br/>Lemma 1 and Theorem 1. +<br/>SVDD formulation: +<br/>(cid:88) +<br/>z∈V (x) +<br/>¯R + +<br/>ν · nV +<br/>min +<br/>c, ¯R, ξ +<br/>s.t. +<br/>(cid:107)Ψθ(z) − c(cid:107)2 ≤ ¯R + ξ(z), +<br/>ξ ≥ 0, ∀z ∈ V (x), +<br/>OC-SVM formulation: +<br/>(cid:88) +<br/>min +<br/>w, ρ, ξ +<br/>s.t. +<br/>(cid:107)w(cid:107)2 + +<br/>ν · nV +<br/>wT Ψθ(z) ≥ ρ − ξz, +<br/>z∈V (x) +<br/>ξz − ρ +<br/>ξz ≥ 0, ∀z ∈ V (x). +<br/>A.1. Proof of Lemma 1 +<br/>Lemma 1. If 1/nV < ν ≤ 1, the SVDD formulation in (1) +<br/>is equivalent to the OC-SVM formulation in (2) when the +<br/>evaluation functions for the two are given by +<br/>hSVDD(x) = ¯R∗ − (cid:107)Ψθ(x) − c∗(cid:107)2 , +<br/>hOC-SVM(x) = w∗T Ψθ(x) − ρ∗, +<br/>(3) +<br/>(4) +<br/>with the correspondence w∗ = c∗, and ρ∗ = c∗T Ψθ(xs), +<br/>where xs is a support vector in (1) that lies on the learned +<br/>enclosing sphere. +<br/>Proof. The condition corresponds to the case 1/nV ≤ C < +<br/>1 in [1] with C = 1/(ν · nV ). We introduce the kernel +<br/>function K(xi, xj) = Ψθ(xi)T Ψθ(xj). Since K(xi, xi) +<br/>is constant in our setting, the same dual formulation for (1) +<br/>and (2) can be written as: +<br/>(cid:88) +<br/>min +<br/>αiαjK(xi, xj) +<br/>s.t. +<br/>0 ≤ αi ≤ C, +<br/>ij +<br/>i=1 +<br/>nV(cid:88) +<br/>αi = 1. +</td><td>('3329881', 'Wei-An Lin', 'wei-an lin')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')</td><td>walin@umd.edu pullpull@cs.umd.edu carlos@cs.umd.edu rama@umiacs.umd.edu +</td></tr><tr><td>23a8d02389805854cf41c9e5fa56c66ee4160ce3</td><td>Multimed Tools Appl <br/>DOI 10.1007/s11042-013-1568-8 <br/>Influence of low resolution of images on reliability <br/>of face detection and recognition <br/>© The Author(s) 2013. This article is published with open access at SpringerLink.com -</td><td>('2553748', 'Tomasz Marciniak', 'tomasz marciniak')<br/>('2009993', 'Radoslaw Weychan', 'radoslaw weychan')<br/>('40397247', 'Adam Dabrowski', 'adam dabrowski')</td><td></td></tr><tr><td>4fd29e5f4b7186e349ba34ea30738af7860cf21f</td><td></td><td></td><td></td></tr><tr><td>4f0d9200647042e41dea71c35eb59e598e6018a7</td><td><b></b><br/>Experiments of Image Retrieval Using Weak Attributes +</td><td>('2553748', 'Tomasz Marciniak', 'tomasz marciniak')<br/>('2009993', 'Radoslaw Weychan', 'radoslaw weychan')<br/>('40397247', 'Adam Dabrowski', 'adam dabrowski')</td><td></td></tr><tr><td>23b37c2f803a2d4b701e2f39c5f623b2f3e14d8e</td><td>Available Online at www.ijcsmc.com +<br/>International Journal of Computer Science and Mobile Computing +<br/>A Monthly Journal of Computer Science and Information Technology +<br/>ISSN 2320–088X +<br/> IJCSMC, Vol. 2, Issue. 4, April 2013, pg.646 – 649 +<br/>RESEARCH ARTICLE +<br/>Modified Approaches on Face Recognition +<br/>By using Multisensory Image +<br/><b>Bharath University, India</b><br/><b>Bharath University, India</b></td><td></td><td></td></tr><tr><td>4f9e00aaf2736b79e415f5e7c8dfebda3043a97d</td><td>Machine Audition: +<br/>Principles, Algorithms +<br/>and Systems +<br/><b>University of Surrey, UK</b><br/>InformatIon scIence reference +<br/>Hershey • New York +</td><td>('46314841', 'WenWu Wang', 'wenwu wang')</td><td></td></tr><tr><td>4fd29e5f4b7186e349ba34ea30738af7860cf21f</td><td></td><td></td><td></td></tr><tr><td>4f0d9200647042e41dea71c35eb59e598e6018a7</td><td><b></b><br/>Experiments of Image Retrieval Using Weak Attributes <br/><b>Columbia University, New York, NY</b></td><td>('1815972', 'Felix X. Yu', 'felix x. yu')<br/>('1725599', 'Rongrong Ji', 'rongrong ji')<br/>('3138710', 'Ming-Hen Tsai', 'ming-hen tsai')<br/>('35984288', 'Guangnan Ye', 'guangnan ye')<br/>('9546964', 'Shih-Fu Chang', 'shih-fu chang')</td><td>yfyuxinnan, rrji, yegng@ee.columbia.edu <br/>xfminghen, sfchangg@cs.columbia.edu -</td></tr><tr><td>4faded442b506ad0f200a608a69c039e92eaff11</td><td><b>STANBUL TECHNICAL UNIVERSITY INSTITUTE OF SCIENCE AND TECHNOLOGY</b><br/>FACE RECOGNITION UNDER VARYING +</td></tr><tr><td>4f051022de100241e5a4ba8a7514db9167eabf6e</td><td>Face Parsing via a Fully-Convolutional Continuous +<br/>CRF Neural Network +</td><td>('48207414', 'Lei Zhou', 'lei zhou')<br/>('36300239', 'Zhi Liu', 'zhi liu')<br/>('1706670', 'Xiangjian He', 'xiangjian he')</td><td></td></tr><tr><td>4faded442b506ad0f200a608a69c039e92eaff11</td><td><b>STANBUL TECHNICAL UNIVERSITY INSTITUTE OF SCIENCE AND TECHNOLOGY</b><br/>FACE RECOGNITION UNDER VARYING <br/>ILLUMINATION <br/>Master Thesis by <br/>Department : Computer Engineering @@ -33188,11 +42624,30 @@ <br/><b>University of Groningen, The Netherlands</b></td><td>('3405120', 'Jos van de Wolfshaar', 'jos van de wolfshaar')</td><td></td></tr><tr><td>4fefd1bc8dc4e0ab37ee3324ddfa43ad9d6a04a7</td><td>Fashion Landmark Detection in the Wild <br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Key Lab of Comp. Vis. and Pat. Rec., Shenzhen Institutes of Advanced</b><br/>Technology, CAS, China </td><td>('3243969', 'Ziwei Liu', 'ziwei liu')<br/>('1979911', 'Sijie Yan', 'sijie yan')<br/>('1693209', 'Ping Luo', 'ping luo')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{lz013,siyan,pluo,xtang}@ie.cuhk.edu.hk, xgwang@ee.cuhk.edu.hk -</td></tr><tr><td>4f77a37753c03886ca9c9349723ec3bbfe4ee967</td><td>Localizing Facial Keypoints with Global Descriptor Search, +</td></tr><tr><td>4f4f920eb43399d8d05b42808e45b56bdd36a929</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 123 – No.4, August 2015 +<br/>A Novel Method for 3D Image Segmentation with Fusion +<br/>of Two Images using Color K-means Algorithm +<br/>Neelam Kushwah +<br/>Dept. of CSE +<br/>ITM Universe +<br/>Gwalior +<br/>Priusha Narwariya +<br/>Dept. of CSE +<br/>ITM Universe +<br/>Gwalior +<br/>two +</td><td></td><td></td></tr><tr><td>4f0b8f730273e9f11b2bfad2415485414b96299f</td><td>BDD100K: A Diverse Driving Video Database with +<br/>Scalable Annotation Tooling +<br/>1UC Berkeley +<br/><b>Georgia Institute of Technology</b><br/><b>Peking University</b><br/>4Uber AI Labs +</td><td>('1807197', 'Fisher Yu', 'fisher yu')<br/>('32324034', 'Fangchen Liu', 'fangchen liu')<br/>('8309711', 'Vashisht Madhavan', 'vashisht madhavan')<br/>('1753210', 'Trevor Darrell', 'trevor darrell')</td><td></td></tr><tr><td>4f77a37753c03886ca9c9349723ec3bbfe4ee967</td><td>Localizing Facial Keypoints with Global Descriptor Search, <br/>Neighbour Alignment and Locally Linear Models <br/>1 ´Ecole Polytechnique de Montr´eal, Universit´e de Montr´eal <br/><b>University of Toronto and Recognyz Systems Technologies</b><br/>also focused on emotion recognition in the wild [9]. </td><td>('1972076', 'Christopher Pal', 'christopher pal')<br/>('9422894', 'Sharon Moalem', 'sharon moalem')</td><td>md-kamrul.hasan@polymtl.ca, christohper.pal@polymtl.ca, sharon@recognyz.com +</td></tr><tr><td>4f7b92bd678772552b3c3edfc9a7c5c4a8c60a8e</td><td>Deep Density Clustering of Unconstrained Faces +<br/><b>University of Maryland, College Park</b></td><td>('3329881', 'Wei-An Lin', 'wei-an lin')<br/>('36407236', 'Jun-Cheng Chen', 'jun-cheng chen')</td><td>walin@umd.edu pullpull@cs.umd.edu carlos@cs.umd.edu rama@umiacs.umd.edu </td></tr><tr><td>4f36c14d1453fc9d6481b09c5a09e91d8d9ee47a</td><td>DU,CHELLAPPA: VIDEO-BASED FACE RECOGNITION <br/>Video-Based Face Recognition Using the <br/>Intra/Extra-Personal Difference Dictionary @@ -33327,10 +42782,22 @@ </td><td>('7530203', 'Sneha Thakur', 'sneha thakur')</td><td></td></tr><tr><td>8d4f12ed7b5a0eb3aa55c10154d9f1197a0d84f3</td><td>Cascaded Pose Regression <br/>Piotr Doll´ar <br/><b>California Institute of Technology</b></td><td>('2930640', 'Peter Welinder', 'peter welinder')<br/>('1690922', 'Pietro Perona', 'pietro perona')</td><td>{pdollar,welinder,perona}@caltech.edu -</td></tr><tr><td>8d2c0c9155a1ed49ba576ac0446ec67725468d87</td><td>A Study of Two Image Representations for Head Pose Estimation +</td></tr><tr><td>8de6deefb90fb9b3f7d451b9d8a1a3264b768482</td><td>Multibiometric Systems: Fusion Strategies and +<br/>Template Security +<br/>By +<br/>A Dissertation +<br/>Submitted to +<br/><b>Michigan State University</b><br/>in partial fulfillment of the requirements +<br/>for the degree of +<br/>Doctor of Philosophy +<br/>Department of Computer Science and Engineering +<br/>2008 +</td><td>('34633765', 'Karthik Nandakumar', 'karthik nandakumar')</td><td></td></tr><tr><td>8d2c0c9155a1ed49ba576ac0446ec67725468d87</td><td>A Study of Two Image Representations for Head Pose Estimation <br/>Dept. of Computer Science and Technology, <br/><b>Tsinghua University, Beijing, China</b></td><td>('1968464', 'Ligeng Dong', 'ligeng dong')<br/>('3265275', 'Linmi Tao', 'linmi tao')<br/>('1797002', 'Guangyou Xu', 'guangyou xu')</td><td>dongligeng99@mails.thu.edu.cn, <br/>{linmi, xgy-dcs}@tsinghua.edu.cn +</td></tr><tr><td>8d384e8c45a429f5c5f6628e8ba0d73c60a51a89</td><td>Temporal Dynamic Graph LSTM for Action-driven Video Object Detection +<br/><b>The Hong Kong University of Science and Technology 2 Carneige Mellon University</b></td><td>('38937910', 'Yuan Yuan', 'yuan yuan')</td><td>yyuanad@ust.hk, xiaodan1@cs.cmu.edu, xiaolonw@cs.cmu.edu, dyyeung@cse.ust.hk, abhinavg@cs.cmu.edu </td></tr><tr><td>8d0243b8b663ca0ab7cbe613e3b886a5d1c8c152</td><td>Development of Optical Computer Recognition (OCR) for Monitoring Stress and Emotions in Space <br/><b>Center for Computational Biomedicine Imaging and Modeling Center, Rutgers University, New Brunswick, NJ</b><br/><b>USA, 2Unit for Experimental Psychiatry, University of Pennsylvania School of Medicine</b><br/>Philadelphia, PA, USA <br/>INTRODUCTION. While in space, astronauts are required to perform mission-critical tasks on very expensive @@ -33383,7 +42850,12 @@ <br/>Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . <br/>Terry P. Orlando <br/>Chairman, Department Committee on Graduate Students -</td><td></td><td></td></tr><tr><td>8dbe79830713925affc48d0afa04ed567c54724b</td><td></td><td></td><td></td></tr><tr><td>8d1adf0ac74e901a94f05eca2f684528129a630a</td><td>Facial Expression Recognition Using Facial +</td><td></td><td></td></tr><tr><td>8dcc95debd07ebab1721c53fa50d846fef265022</td><td>MicroExpNet: An Extremely Small and Fast Model For Expression Recognition +<br/>From Frontal Face Images +<br/>˙Ilke C¸ u˘gu, Eren S¸ener, Emre Akbas¸ +<br/><b>Middle East Technical University</b><br/>06800 Ankara, Turkey +</td><td></td><td>{cugu.ilke, sener.eren}@metu.edu.tr, emre@ceng.metu.edu.tr +</td></tr><tr><td>8dbe79830713925affc48d0afa04ed567c54724b</td><td></td><td></td><td></td></tr><tr><td>8d1adf0ac74e901a94f05eca2f684528129a630a</td><td>Facial Expression Recognition Using Facial <br/>Movement Features </td><td></td><td></td></tr><tr><td>8d91f06af4ef65193f3943005922f25dbb483ee4</td><td>Facial Expression Classification Using Rotation <br/>Slepian-based Moment Invariants @@ -33492,7 +42964,15 @@ <br/>Finally, we visualized which features were the most <br/>important for classifying each emotion; the results can be <br/>seen in Figure 4. The figure shows the X and Y -</td><td>('39818775', 'Tom McLaughlin', 'tom mclaughlin')</td><td></td></tr><tr><td>8dce38840e6cf5ab3e0d1b26e401f8143d2a6bff</td><td>Towards large scale multimedia indexing: +</td><td>('39818775', 'Tom McLaughlin', 'tom mclaughlin')</td><td></td></tr><tr><td>8d5998cd984e7cce307da7d46f155f9db99c6590</td><td>ChaLearn Looking at People: +<br/>A Review of Events and Resources +<br/>1 Dept. Mathematics and Computer Science, UB, Spain, +<br/>2 Computer Vision Center, UAB, Barcelona, Spain, +<br/><b>EIMT, Open University of Catalonia, Barcelona, Spain</b><br/>4 ChaLearn, California, USA, 5 INAOE, Puebla, Mexico, +<br/>6 Universit´e Paris-Saclay, Paris, France, +<br/>http://chalearnlap.cvc.uab.es +</td><td>('7855312', 'Sergio Escalera', 'sergio escalera')<br/>('1742688', 'Hugo Jair Escalante', 'hugo jair escalante')<br/>('1743797', 'Isabelle Guyon', 'isabelle guyon')</td><td>sergio.escalera.guerrero@gmail.com +</td></tr><tr><td>8dce38840e6cf5ab3e0d1b26e401f8143d2a6bff</td><td>Towards large scale multimedia indexing: <br/>A case study on person discovery in broadcast news <br/><b>Idiap Research Institute and EPFL, 2 LIMSI, CNRS, Univ. Paris-Sud, Universit Paris-Saclay</b><br/>3 CNRS, Irisa & Inria Rennes, 4 PUC de Minas Gerais, Belo Horizonte, <br/><b>Universitat Polit cnica de Catalunya, 6 University of Vigo, 7 LIUM, University of Maine</b></td><td>('39560344', 'Nam Le', 'nam le')<br/>('2578933', 'Hervé Bredin', 'hervé bredin')<br/>('2710421', 'Gabriel Sargent', 'gabriel sargent')<br/>('2613332', 'Miquel India', 'miquel india')<br/>('1794658', 'Paula Lopez-Otero', 'paula lopez-otero')<br/>('1802247', 'Claude Barras', 'claude barras')<br/>('1804407', 'Camille Guinaudeau', 'camille guinaudeau')<br/>('1708671', 'Guillaume Gravier', 'guillaume gravier')<br/>('23556030', 'Gabriel Barbosa da Fonseca', 'gabriel barbosa da fonseca')<br/>('32255257', 'Izabela Lyon Freire', 'izabela lyon freire')<br/>('37401316', 'Gerard Martí', 'gerard martí')<br/>('2585946', 'Josep Ramon Morros', 'josep ramon morros')<br/>('1726311', 'Javier Hernando', 'javier hernando')<br/>('2446815', 'Sylvain Meignier', 'sylvain meignier')<br/>('1719610', 'Jean-Marc Odobez', 'jean-marc odobez')</td><td>nle@idiap.ch,bredin@limsi.fr,gabriel.sargent@irisa.fr,miquel.india@tsc.upc.edu,plopez@gts.uvigo.es @@ -33572,7 +43052,9 @@ <br/>Some results are presented in Figure 1, Table 1 and 2. Figure 1 shows <br/>the improvement in both the affinity matrix and the subspace clustering us- <br/>ing S3C over SSC on a subset of face images of three subjects from the -</td><td>('9171002', 'Chun-Guang Li', 'chun-guang li')<br/>('1745721', 'René Vidal', 'rené vidal')</td><td></td></tr><tr><td>15affdcef4bb9d78b2d3de23c9459ee5b7a43fcb</td><td>Semi-Supervised Classification Using Linear +</td><td>('9171002', 'Chun-Guang Li', 'chun-guang li')<br/>('1745721', 'René Vidal', 'rené vidal')</td><td></td></tr><tr><td>15136c2f94fd29fc1cb6bedc8c1831b7002930a6</td><td>Deep Learning Architectures for Face +<br/>Recognition in Video Surveillance +</td><td>('2805645', 'Saman Bashbaghi', 'saman bashbaghi')<br/>('1697195', 'Eric Granger', 'eric granger')<br/>('1744351', 'Robert Sabourin', 'robert sabourin')<br/>('3046171', 'Mostafa Parchami', 'mostafa parchami')</td><td></td></tr><tr><td>15affdcef4bb9d78b2d3de23c9459ee5b7a43fcb</td><td>Semi-Supervised Classification Using Linear <br/>Neighborhood Propagation <br/><b>Tsinghua University, Beijing 100084, P.R.China</b><br/><b>The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong</b><br/>Semi-Supervised Classi(cid:12)cation <br/>A Toy Example @@ -33785,7 +43267,11 @@ <br/>(b) <br/>1.5 <br/>2.5 -</td><td>('34410258', 'Fei Wang', 'fei wang')<br/>('1688516', 'Jingdong Wang', 'jingdong wang')<br/>('1700883', 'Changshui Zhang', 'changshui zhang')<br/>('7969645', 'Helen C. Shen', 'helen c. shen')</td><td></td></tr><tr><td>159e792096756b1ec02ec7a980d5ef26b434ff78</td><td>Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence +</td><td>('34410258', 'Fei Wang', 'fei wang')<br/>('1688516', 'Jingdong Wang', 'jingdong wang')<br/>('1700883', 'Changshui Zhang', 'changshui zhang')<br/>('7969645', 'Helen C. Shen', 'helen c. shen')</td><td></td></tr><tr><td>15d653972d176963ef0ad2cc582d3b35ca542673</td><td>CSVideoNet: A Real-time End-to-end Learning Framework for +<br/>High-frame-rate Video Compressive Sensing +<br/>School of Computing, Informatics, and Decision Systems Engineering +<br/><b>Arizona State University, Tempe AZ</b></td><td>('47831601', 'Kai Xu', 'kai xu')<br/>('40615963', 'Fengbo Ren', 'fengbo ren')</td><td>{kaixu, renfengbo}@asu.edu +</td></tr><tr><td>159e792096756b1ec02ec7a980d5ef26b434ff78</td><td>Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence <br/>Signed Laplacian Embedding for Supervised Dimension Reduction <br/><b>Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University</b><br/><b>Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney</b></td><td>('1710691', 'Chen Gong', 'chen gong')<br/>('1692693', 'Dacheng Tao', 'dacheng tao')<br/>('39264954', 'Jie Yang', 'jie yang')<br/>('1847070', 'Keren Fu', 'keren fu')</td><td>{goodgongchen, jieyang, fkrsuper}@sjtu.edu.cn <br/>dacheng.tao@uts.edu.au @@ -33840,7 +43326,21 @@ </td><td>('7513255', 'Chi Xu', 'chi xu')<br/>('1689334', 'Yasushi Makihara', 'yasushi makihara')<br/>('12881056', 'Gakuto Ogi', 'gakuto ogi')<br/>('1737850', 'Xiang Li', 'xiang li')<br/>('1715071', 'Yasushi Yagi', 'yasushi yagi')<br/>('6120396', 'Jianfeng Lu', 'jianfeng lu')</td><td></td></tr><tr><td>151481703aa8352dc78e2577f0601782b8c41b34</td><td>Appearance Manifold of Facial Expression <br/><b>Queen Mary, University of London, London E1 4NS, UK</b><br/>Department of Computer Science </td><td>('10795229', 'Caifeng Shan', 'caifeng shan')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')<br/>('2803283', 'Peter W. McOwan', 'peter w. mcowan')</td><td>{cfshan,sgg,pmco}@dcs.qmul.ac.uk -</td></tr><tr><td>1565721ebdbd2518224f54388ed4f6b21ebd26f3</td><td>Face and Landmark Detection by Using Cascade of Classifiers +</td></tr><tr><td>15aa6c457678e25f6bc0e818e5fc39e42dd8e533</td><td></td><td></td><td></td></tr><tr><td>15cf1f17aeba62cd834116b770f173b0aa614bf4</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 77 – No.5, September 2013 +<br/>Facial Expression Recognition using Neural Network with +<br/>Regularized Back-propagation Algorithm +<br/>Research Scholar +<br/>Department of ECE, +<br/><b></b><br/>Phagwara, India +<br/>Assistant Professor +<br/>Department of ECE, +<br/><b></b><br/>Phagwara, India +<br/>Research Scholar +<br/>Department of ECE, +<br/><b>Gyan Ganga Institute of</b><br/>Technology & Sciences, +<br/>Jabalpur, India +</td><td>('35358999', 'Ashish Kumar Dogra', 'ashish kumar dogra')<br/>('50227570', 'Nikesh Bajaj', 'nikesh bajaj')</td><td></td></tr><tr><td>1565721ebdbd2518224f54388ed4f6b21ebd26f3</td><td>Face and Landmark Detection by Using Cascade of Classifiers <br/><b>Eskisehir Osmangazi University</b><br/>Eskisehir, Turkey <br/>Laboratoire Jean Kuntzmann <br/>Grenoble Cedex 9, France @@ -33905,6 +43405,12 @@ <br/>jhtao@nlpr.ia.ac.cn <br/>mhyang@nlpr.ia.ac.cn <br/>yli@nlpr.ia.ac.cn +</td></tr><tr><td>121503705689f46546cade78ff62963574b4750b</td><td>We don’t need no bounding-boxes: +<br/>Training object class detectors using only human verification +<br/><b>University of Edinburgh</b></td><td>('1749373', 'Dim P. Papadopoulos', 'dim p. papadopoulos')<br/>('1823362', 'Jasper R. R. Uijlings', 'jasper r. r. uijlings')<br/>('48716849', 'Frank Keller', 'frank keller')<br/>('1749692', 'Vittorio Ferrari', 'vittorio ferrari')</td><td>dim.papadopoulos@ed.ac.uk +<br/>jrr.uijlings@ed.ac.uk +<br/>keller@inf.ed.ac.uk +<br/>vferrari@inf.ed.ac.uk </td></tr><tr><td>125d82fee1b9fbcc616622b0977f3d06771fc152</td><td>Hierarchical Face Parsing via Deep Learning <br/><b>The Chinese University of Hong Kong</b><br/><b>The Chinese University of Hong Kong</b><br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b></td><td>('1693209', 'Ping Luo', 'ping luo')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>pluo.lhi@gmail.com <br/>xgwang@ee.cuhk.edu.hk @@ -33913,6 +43419,24 @@ <br/>from Multiple Histograms of Oriented Gradients <br/><b>Institute of Arti cial Intelligence and Cognitive Engineering (ALICE), University of Groningen</b><br/>Nijenborgh 9, Groningen, The Netherlands </td><td>('3351361', 'Mahir Faik Karaaba', 'mahir faik karaaba')<br/>('1728531', 'Olarik Surinta', 'olarik surinta')<br/>('1799278', 'Lambert Schomaker', 'lambert schomaker')</td><td>Email: {m.f.karaaba, o.surinta, l.r.b.schomaker, m.a.wiering}@rug.nl +</td></tr><tr><td>1275d6a800f8cf93c092603175fdad362b69c191</td><td>Deep Face Recognition: A Survey +<br/>School of Information and Communication Engineering, +<br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b><br/>still have an inevitable limitation on robustness against the +<br/>complex nonlinear facial appearance variations. +<br/>In general, traditional methods attempted to solve FR prob- +<br/>lem by one or two layer representation, such as filtering +<br/>responses or histogram of the feature codes. The research com- +<br/>munity studied intensively to separately improve the prepro- +<br/>cessing, local descriptors, and feature transformation, which +<br/>improve face recognition accuracy slowly. By the continuous +<br/>improvement of a decade, “shallow” methods only improve the +<br/>accuracy of the LFW benchmark to about 95% [26], which +<br/>indicates that “shallow” methods are insufficient to extract +<br/>stable identity feature against unconstrained facial variations. +<br/>Due to the technical insufficiency, facial recognition systems +<br/>were often reported with unstable performance or failures with +<br/>countless false alarms in real-world applications. +</td><td>('2285767', 'Mei Wang', 'mei wang')<br/>('1774956', 'Weihong Deng', 'weihong deng')</td><td>wm0245@126.com, whdeng@bupt.edu.cn </td></tr><tr><td>126535430845361cd7a3a6f317797fe6e53f5a3b</td><td>Robust Photometric Stereo via Low-Rank Matrix <br/>Completion and Recovery (cid:63) <br/><b>School of Optics and Electronics, Beijing Institute of Technology, Beijing</b><br/><b>Coordinated Science Lab, University of Illinois at Urbana-Champaign</b><br/><b>Key Laboratory of Machine Perception, Peking University, Beijing</b><br/>§Visual Computing Group, Microsoft Research Asia, Beijing @@ -33925,7 +43449,7 @@ <br/>TU M¨unchen <br/>April 5, 2007 </td><td>('2866162', 'Simon Kriegel', 'simon kriegel')</td><td>kriegel@mmer-systems.eu -</td></tr><tr><td>121fe33daf55758219e53249cf8bcb0eb2b4db4b</td><td>CHAKRABARTI et al.: EMPIRICAL CAMERA MODEL +</td></tr><tr><td>1287bfe73e381cc8042ac0cc27868ae086e1ce3b</td><td></td><td></td><td></td></tr><tr><td>121fe33daf55758219e53249cf8bcb0eb2b4db4b</td><td>CHAKRABARTI et al.: EMPIRICAL CAMERA MODEL <br/>An Empirical Camera Model <br/>for Internet Color Vision <br/>http://www.eecs.harvard.edu/~ayanc/ @@ -33937,7 +43461,9 @@ <br/>Cambridge, MA, USA 02139 <br/>2 Department of Computer Science <br/><b>Middlebury College</b><br/>Middlebury, VT, USA 05753 -</td><td>('38534744', 'Ayan Chakrabarti', 'ayan chakrabarti')<br/>('1709053', 'Daniel Scharstein', 'daniel scharstein')</td><td></td></tr><tr><td>120bcc9879d953de7b2ecfbcd301f72f3a96fb87</td><td>Report on the FG 2015 Video Person Recognition Evaluation +</td><td>('38534744', 'Ayan Chakrabarti', 'ayan chakrabarti')<br/>('1709053', 'Daniel Scharstein', 'daniel scharstein')</td><td></td></tr><tr><td>12408baf69419409d228d96c6f88b6bcde303505</td><td>Temporal Tessellation: A Unified Approach for Video Analysis +<br/><b>The Blavatnik School of Computer Science, Tel Aviv University, Israel</b><br/><b>Information Sciences Institute, USC, CA, USA</b><br/><b>The Open University of Israel, Israel</b><br/>4Facebook AI Research +</td><td>('48842639', 'Dotan Kaufman', 'dotan kaufman')<br/>('36813724', 'Gil Levi', 'gil levi')<br/>('1756099', 'Tal Hassner', 'tal hassner')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td></td></tr><tr><td>120bcc9879d953de7b2ecfbcd301f72f3a96fb87</td><td>Report on the FG 2015 Video Person Recognition Evaluation <br/>Zhenhua Feng <br/><b>Colorado State University</b><br/>Fort Collins, CO, USA <br/><b>University of Notre Dame</b><br/>Notre Dame, IN, USA @@ -33955,10 +43481,36 @@ <br/>Graduation research project, june 2012 <br/>Supervised by: Dr. Joost Broekens <br/><b></b></td><td></td><td>mail@barryborsboom.nl +</td></tr><tr><td>12095f9b35ee88272dd5abc2d942a4f55804b31e</td><td>DenseReg: Fully Convolutional Dense Shape Regression In-the-Wild +<br/>Rıza Alp G¨uler1 +<br/>1INRIA-CentraleSup´elec, France +<br/><b>Imperial College London, UK</b><br/>Stefanos Zafeiriou2 +<br/>3Amazon, Berlin, Germany +<br/><b>University College London, UK</b></td><td>('2814229', 'George Trigeorgis', 'george trigeorgis')<br/>('2788012', 'Epameinondas Antonakos', 'epameinondas antonakos')<br/>('2796644', 'Patrick Snape', 'patrick snape')<br/>('48111527', 'Iasonas Kokkinos', 'iasonas kokkinos')</td><td>riza.guler@inria.fr +<br/>2{g.trigeorgis, p.snape, s.zafeiriou}@imperial.ac.uk +<br/>antonak@amazon.com +<br/>i.kokkinos@cs.ucl.ac.uk </td></tr><tr><td>12cd96a419b1bd14cc40942b94d9c4dffe5094d2</td><td>29 <br/>Proceedings of the 5th Workshop on Vision and Language, pages 29–38, <br/>Berlin, Germany, August 12 2016. c(cid:13)2016 Association for Computational Linguistics -</td><td></td><td></td></tr><tr><td>12055b8f82d5411f9ad196b60698d76fbd07ac1e</td><td>1475 +</td><td></td><td></td></tr><tr><td>1275852f2e78ed9afd189e8b845fdb5393413614</td><td>A Transfer Learning based Feature-Weak-Relevant Method for +<br/>Image Clustering +<br/><b>Dalian Maritime University</b><br/>Dalian, China +</td><td>('3852923', 'Bo Dong', 'bo dong')<br/>('2860808', 'Xinnian Wang', 'xinnian wang')</td><td>{dukedong,wxn}@dlmu.edu.cn +</td></tr><tr><td>1297ee7a41aa4e8499c7ddb3b1fed783eba19056</td><td><b>University of Nebraska - Lincoln</b><br/>US Army Research +<br/>2015 +<br/>U.S. Department of Defense +<br/>Effects of emotional expressions on persuasion +<br/>Gale Lucas +<br/><b>University of Southern California</b><br/><b>University of Southern California</b><br/><b>University of Southern California</b><br/><b>University of Southern California</b><br/>Follow this and additional works at: http://digitalcommons.unl.edu/usarmyresearch +<br/>Wang, Yuqiong; Lucas, Gale; Khooshabeh, Peter; de Melo, Celso; and Gratch, Jonathan, "Effects of emotional expressions on +<br/>persuasion" (2015). US Army Research. 340. +<br/>http://digitalcommons.unl.edu/usarmyresearch/340 +</td><td>('49416640', 'Yuqiong Wang', 'yuqiong wang')<br/>('2635945', 'Peter Khooshabeh', 'peter khooshabeh')<br/>('1977901', 'Celso de Melo', 'celso de melo')<br/>('1730824', 'Jonathan Gratch', 'jonathan gratch')</td><td>DigitalCommons@University of Nebraska - Lincoln +<br/>University of Southern California, wangyuqiong@ymail.com +<br/>This Article is brought to you for free and open access by the U.S. Department of Defense at DigitalCommons@University of Nebraska - Lincoln. It has +<br/>been accepted for inclusion in US Army Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. +</td></tr><tr><td>12055b8f82d5411f9ad196b60698d76fbd07ac1e</td><td>1475 <br/>Multiview Facial Landmark Localization in RGB-D <br/>Images via Hierarchical Regression <br/>With Binary Patterns @@ -33977,14 +43529,52 @@ <br/>{javier.cruz,thomas.robin,michel.bierlaire}@epfl.ch <br/>gan@zurich.ibm.com <br/>barbara.cerretani@gmail.com +</td></tr><tr><td>120785f9b4952734818245cc305148676563a99b</td><td>Diagnostic automatique de l’état dépressif +<br/>S. Cholet +<br/>H. Paugam-Moisy +<br/>Laboratoire de Mathématiques Informatique et Applications (LAMIA - EA 4540) +<br/>Université des Antilles, Campus de Fouillole - Guadeloupe +<br/>Résumé +<br/>Les troubles psychosociaux sont un problème de santé pu- +<br/>blique majeur, pouvant avoir des conséquences graves sur +<br/>le court ou le long terme, tant sur le plan professionnel que +<br/>personnel ou familial. Le diagnostic de ces troubles doit +<br/>être établi par un professionnel. Toutefois, l’IA (l’Intelli- +<br/>gence Artificielle) peut apporter une contribution en four- +<br/>nissant au praticien une aide au diagnostic, et au patient +<br/>un suivi permanent rapide et peu coûteux. Nous proposons +<br/>une approche vers une méthode de diagnostic automatique +<br/>de l’état dépressif à partir d’observations du visage en +<br/>temps réel, au moyen d’une simple webcam. A partir de +<br/>vidéos du challenge AVEC’2014, nous avons entraîné un +<br/>classifieur neuronal à extraire des prototypes de visages +<br/>selon différentes valeurs du score de dépression de Beck +<br/>(BDI-II). +</td><td></td><td>Stephane.Cholet@univ-antilles.fr </td></tr><tr><td>12692fbe915e6bb1c80733519371bbb90ae07539</td><td>Object Bank: A High-Level Image Representation for Scene <br/>Classification & Semantic Feature Sparsification -<br/><b>Stanford University</b><br/><b>Carnegie Mellon University</b></td><td>('33642044', 'Li-Jia Li', 'li-jia li')<br/>('2888806', 'Hao Su', 'hao su')<br/>('1752601', 'Eric P. Xing', 'eric p. xing')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>12ccfc188de0b40c84d6a427999239c6a379cd66</td><td>Sparse Adversarial Perturbations for Videos +<br/><b>Stanford University</b><br/><b>Carnegie Mellon University</b></td><td>('33642044', 'Li-Jia Li', 'li-jia li')<br/>('2888806', 'Hao Su', 'hao su')<br/>('1752601', 'Eric P. Xing', 'eric p. xing')<br/>('3216322', 'Li Fei-Fei', 'li fei-fei')</td><td></td></tr><tr><td>1251deae1b4a722a2155d932bdfb6fe4ae28dd22</td><td>A Large-scale Attribute Dataset for Zero-shot Learning +<br/>1 National Engineering Laboratory for Video Technology, +<br/>Key Laboratory of Machine Perception (MoE), +<br/>Cooperative Medianet Innovation Center, Shanghai, +<br/><b>School of EECS, Peking University, Beijing, 100871, China</b><br/><b>School of Data Science, Fudan University</b><br/>3 Sinovation Ventures +</td><td>('49217762', 'Bo Zhao', 'bo zhao')<br/>('35782003', 'Yanwei Fu', 'yanwei fu')<br/>('1705512', 'Rui Liang', 'rui liang')<br/>('3165417', 'Jiahong Wu', 'jiahong wu')<br/>('47904050', 'Yonggang Wang', 'yonggang wang')<br/>('36637369', 'Yizhou Wang', 'yizhou wang')</td><td>bozhao, yizhou.wang@pku.edu.cn, yanweifu@fudan.edu.cn +<br/>liangrui, wujiahong, wangyonggang@chuangxin.com +</td></tr><tr><td>12ccfc188de0b40c84d6a427999239c6a379cd66</td><td>Sparse Adversarial Perturbations for Videos <br/>1 Tsinghua National Lab for Information Science and Technology <br/>1 State Key Lab of Intelligent Technology and Systems <br/><b>Tsinghua University</b><br/>1 Center for Bio-Inspired Computing Research </td><td>('2769710', 'Xingxing Wei', 'xingxing wei')<br/>('40062221', 'Jun Zhu', 'jun zhu')<br/>('37409747', 'Hang Su', 'hang su')</td><td>{xwei11, dcszj, suhangss}@mail.tsinghua.edu.cn -</td></tr><tr><td>12c713166c46ac87f452e0ae383d04fb44fe4eb2</td><td></td><td></td><td></td></tr><tr><td>1270044a3fa1a469ec2f4f3bd364754f58a1cb56</td><td>Video-Based Face Recognition Using Probabilistic Appearance Manifolds +</td></tr><tr><td>12c713166c46ac87f452e0ae383d04fb44fe4eb2</td><td></td><td></td><td></td></tr><tr><td>12ebeb2176a5043ad57bc5f3218e48a96254e3e9</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 120 – No.24, June 2015 +<br/>Traffic Road Sign Detection and Recognition for +<br/>Automotive Vehicles +<br/>Zakir Hyder +<br/>Department of Electrical Engineering and +<br/>Department of Electrical Engineering and +<br/><b>Computer Science North South University, Dhaka</b><br/><b>Computer Science North South University, Dhaka</b><br/>Bangladesh +<br/>Bangladesh +</td><td></td><td></td></tr><tr><td>1270044a3fa1a469ec2f4f3bd364754f58a1cb56</td><td>Video-Based Face Recognition Using Probabilistic Appearance Manifolds <br/>yComputer Science <br/>Urbana, IL 61801 <br/>zComputer Science & Engineering @@ -34211,7 +43801,9 @@ <br/>Xerox Research Centre Europe </td><td>('2295553', 'Diane Larlus', 'diane larlus')<br/>('1687524', 'Andrea Vedaldi', 'andrea vedaldi')</td><td>{david,andrea}@robots.ox.ac.uk <br/>diane.larlus@xrce.xerox.com -</td></tr><tr><td>8c6b9c9c26ead75ce549a57c4fd0a12b46142848</td><td>Facial expression recognition using shape and +</td></tr><tr><td>8ccde9d80706a59e606f6e6d48d4260b60ccc736</td><td>RotDCF: Decomposition of Convolutional Filters for +<br/>Rotation-Equivariant Deep Networks +<br/><b>Duke University</b><br/><b>Duke University</b></td><td>('1823644', 'Xiuyuan Cheng', 'xiuyuan cheng')<br/>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('1699339', 'Guillermo Sapiro', 'guillermo sapiro')</td><td></td></tr><tr><td>8c6b9c9c26ead75ce549a57c4fd0a12b46142848</td><td>Facial expression recognition using shape and <br/>texture information <br/>I. Kotsia1 and I. Pitas1 <br/><b>Aristotle University of Thessaloniki</b><br/>Department of Informatics @@ -34245,6 +43837,12 @@ <br/>as the di(cid:11)erence of Candide facial model grid node coordinates between the <br/>(cid:12)rst and the last frame of a video sequence [?]. The decision made regarding </td><td></td><td>pitas@aiia.csd.auth.gr +</td></tr><tr><td>8ce9b7b52d05701d5ef4a573095db66ce60a7e1c</td><td>Structured Sparse Subspace Clustering: A Joint +<br/>Affinity Learning and Subspace Clustering +<br/>Framework +</td><td>('9171002', 'Chun-Guang Li', 'chun-guang li')<br/>('1878841', 'Chong You', 'chong you')</td><td></td></tr><tr><td>8cb6daba2cb1e208e809633133adfee0183b8dd2</td><td>Know Before You Do: Anticipating Maneuvers +<br/>via Learning Temporal Driving Models +<br/><b>Cornell University and Stanford University</b></td><td>('1726066', 'Ashesh Jain', 'ashesh jain')<br/>('3282281', 'Bharad Raghavan', 'bharad raghavan')<br/>('1681995', 'Ashutosh Saxena', 'ashutosh saxena')</td><td>{ashesh,hema,asaxena}@cs.cornell.edu {bharad,shanesoh}@stanford.edu </td></tr><tr><td>8c4ea76e67a2a99339a8c4decd877fe0aa2d8e82</td><td>Article <br/>Gated Convolutional Neural Network for Semantic <br/>Segmentation in High-Resolution Images @@ -34281,7 +43879,20 @@ </td><td>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')<br/>('7855312', 'Sergio Escalera', 'sergio escalera')</td><td></td></tr><tr><td>85041e48b51a2c498f22850ce7228df4e2263372</td><td>Subspace Regression: Predicting <br/>a Subspace from One Sample <br/><b>Robotics Institute, Carnegie Mellon University</b><br/>‡ Electrical & Controls Integration Lab, General Motors R&D -</td><td>('34299925', 'Minyoung Kim', 'minyoung kim')</td><td></td></tr><tr><td>857ad04fca2740b016f0066b152bd1fa1171483f</td><td>Sample Images can be Independently Restored from +</td><td>('34299925', 'Minyoung Kim', 'minyoung kim')</td><td></td></tr><tr><td>85fd2bda5eb3afe68a5a78c30297064aec1361f6</td><td>702003 PSSXXX10.1177/0956797617702003Carr et al.Are You Smiling, or Have I Seen You Before? +<br/>research-article2017 +<br/>Research Article +<br/>Are You Smiling, or Have I Seen You +<br/>Before? Familiarity Makes Faces Look +<br/>Happier +<br/>2017, Vol. 28(8) 1087 –1102 +<br/>© The Author(s) 2017 +<br/>Reprints and permissions: +<br/>sagepub.com/journalsPermissions.nav +<br/>DOI: 10.1177/0956797617702003 +<br/>https://doi.org/10.1177/0956797617702003 +<br/>www.psychologicalscience.org/PS +<br/><b>Columbia Business School, University of California, San Diego</b><br/><b>Behavioural Science Group, Warwick Business School, University of Warwick; and 4Faculty of Psychology</b><br/><b>SWPS University of Social Sciences and Humanities</b></td><td>('5907729', 'Evan W. Carr', 'evan w. carr')<br/>('3122131', 'Piotr Winkielman', 'piotr winkielman')</td><td></td></tr><tr><td>857ad04fca2740b016f0066b152bd1fa1171483f</td><td>Sample Images can be Independently Restored from <br/> Face Recognition Templates <br/><b>School of Information Technology and Engineering, University of Ottawa, Ontario, Canada</b><br/>are being piloted or implemented at airports, for <br/>government identification systems such as passports @@ -34334,7 +43945,15 @@ <br/>ADJUSTABLE CORE SIZE </td><td>('2424633', 'BILIAN CHEN', 'bilian chen')<br/>('1792785', 'ZHENING LI', 'zhening li')<br/>('1789588', 'SHUZHONG ZHANG', 'shuzhong zhang')</td><td></td></tr><tr><td>85188c77f3b2de3a45f7d4f709b6ea79e36bd0d9</td><td>Author manuscript, published in "Workshop on Faces in 'Real-Life' Images: Detection, Alignment, and Recognition, Marseille : <br/>France (2008)" -</td><td></td><td></td></tr><tr><td>8518b501425f2975ea6dcbf1e693d41e73d0b0af</td><td>Relative Hidden Markov Models for Evaluating Motion Skills +</td><td></td><td></td></tr><tr><td>858b51a8a8aa082732e9c7fbbd1ea9df9c76b013</td><td>Can Computer Vision Problems Benefit from +<br/>Structured Hierarchical Classification? +<br/>Sandor Szedmak2 +<br/><b>INTELSIG, Monte ore Institute, University of Li`ege, Belgium</b><br/><b>Intelligent and Interactive Systems, Institute of Computer Science, University of</b><br/>Innsbruck, Austria +</td><td>('3104165', 'Thomas Hoyoux', 'thomas hoyoux')<br/>('1772389', 'Justus H. Piater', 'justus h. piater')</td><td></td></tr><tr><td>856317f27248cdb20226eaae599e46de628fb696</td><td>A Method Based on Convex Cone Model for +<br/>Image-Set Classification with CNN Features +<br/><b>Graduate School of Systems and Information Engineering, University of Tsukuba</b><br/>1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8573, Japan +</td><td>('46230115', 'Naoya Sogi', 'naoya sogi')<br/>('2334316', 'Taku Nakayama', 'taku nakayama')<br/>('1770128', 'Kazuhiro Fukui', 'kazuhiro fukui')</td><td>Email: {sogi, nakayama}@cvlab.cs.tsukuba.ac.jp, kfukui@cs.tsukuba.ac.jp +</td></tr><tr><td>8518b501425f2975ea6dcbf1e693d41e73d0b0af</td><td>Relative Hidden Markov Models for Evaluating Motion Skills <br/>Computer Science and Engineering <br/>Arizona State Univerisity, Tempe, AZ 85281 </td><td>('1689161', 'Qiang Zhang', 'qiang zhang')<br/>('2913552', 'Baoxin Li', 'baoxin li')</td><td>qzhang53,baoxin.li@asu.edu @@ -34419,7 +44038,10 @@ <br/> Department of computer science <br/><b>Raipur institute of technology</b><br/> Raipur, India </td><td>('1977125', 'Vivek Verma', 'vivek verma')</td><td>E-mail: vivekverma.exe@gmail.com -</td></tr><tr><td>1d97735bb0f0434dde552a96e1844b064af08f62</td><td>Weber Binary Pattern and Weber Ternary Pattern +</td></tr><tr><td>1d776bfe627f1a051099997114ba04678c45f0f5</td><td>Deployment of Customized Deep Learning based +<br/>Video Analytics On Surveillance Cameras +<br/>AitoeLabs (www.aitoelabs.com) +</td><td>('46175439', 'Pratik Dubal', 'pratik dubal')<br/>('22549601', 'Rohan Mahadev', 'rohan mahadev')<br/>('9745898', 'Suraj Kothawade', 'suraj kothawade')<br/>('46208440', 'Kunal Dargan', 'kunal dargan')</td><td></td></tr><tr><td>1d97735bb0f0434dde552a96e1844b064af08f62</td><td>Weber Binary Pattern and Weber Ternary Pattern <br/>for Illumination-Robust Face Recognition <br/><b>Tsinghua University, China</b><br/>Shenzhen Key Laboratory of Information Science and Technology, Guangdong, China </td><td>('35160104', 'Zuodong Yang', 'zuodong yang')<br/>('2312541', 'Yinyan Jiang', 'yinyan jiang')<br/>('40398990', 'Yong Wu', 'yong wu')<br/>('2265693', 'Zongqing Lu', 'zongqing lu')<br/>('1718891', 'Weifeng Li', 'weifeng li')<br/>('2883861', 'Qingmin Liao', 'qingmin liao')</td><td>(cid:3) E-mail: yangzd13@mails.tsinghua.edu.cn @@ -34589,6 +44211,12 @@ </td></tr><tr><td>1de690714f143a8eb0d6be35d98390257a3f4a47</td><td>Face Detection Using Spectral Histograms and SVMs <br/><b>The Florida State University</b><br/>Tallahassee, FL 32306 </td><td>('3209925', 'Christopher A. Waring', 'christopher a. waring')<br/>('1800002', 'Xiuwen Liu', 'xiuwen liu')</td><td>chwaring@cs.fsu.edu liux@cs.fsu.edu +</td></tr><tr><td>1d7df3df839a6aa8f5392310d46b2a89080a3c25</td><td>Large-Margin Softmax Loss for Convolutional Neural Networks +<br/>Meng Yang4 +<br/><b>School of ECE, Peking University 2School of EIE, South China University of Technology</b><br/><b>Carnegie Mellon University 4College of CS and SE, Shenzhen University</b></td><td>('36326884', 'Weiyang Liu', 'weiyang liu')<br/>('2512949', 'Yandong Wen', 'yandong wen')<br/>('1751019', 'Zhiding Yu', 'zhiding yu')</td><td>WYLIU@PKU.EDU.CN +<br/>WEN.YANDONG@MAIL.SCUT.EDU.CN +<br/>YZHIDING@ANDREW.CMU.EDU +<br/>YANG.MENG@SZU.EDU.CN </td></tr><tr><td>1d6c09019149be2dc84b0c067595f782a5d17316</td><td>Encoding Video and Label Priors for Multi-label Video Classification <br/>on YouTube-8M dataset <br/><b>Seoul National University</b><br/><b>Seoul National University</b><br/><b>Seoul National University</b><br/>SK Telecom Video Tech. Lab @@ -34604,7 +44232,33 @@ <br/>INRIA & Laboratoire Jean <br/>Kuntzmann, <br/>655 avenue de l'Europe, Montbonnot 38330, France -</td><td>('2248421', 'Xiaoyang Tan', 'xiaoyang tan')<br/>('1756114', 'Bill Triggs', 'bill triggs')</td><td></td></tr><tr><td>71b376dbfa43a62d19ae614c87dd0b5f1312c966</td><td>The Temporal Connection Between Smiles and Blinks +</td><td>('2248421', 'Xiaoyang Tan', 'xiaoyang tan')<br/>('1756114', 'Bill Triggs', 'bill triggs')</td><td></td></tr><tr><td>1d729693a888a460ee855040f62bdde39ae273af</td><td>Photorealistic Face de-Identification by Aggregating +<br/>Donors’ Face Components +<br/>To cite this version: +<br/>gating Donors’ Face Components. Asian Conference on Computer Vision, Nov 2014, Singapore. +<br/>pp.1-16, 2014. <hal-01070658> +<br/>HAL Id: hal-01070658 +<br/>https://hal.archives-ouvertes.fr/hal-01070658 +<br/>Submitted on 2 Oct 2014 +<br/>HAL is a multi-disciplinary open access +<br/>archive for the deposit and dissemination of sci- +<br/>entific research documents, whether they are pub- +<br/>lished or not. The documents may come from +<br/>teaching and research institutions in France or +<br/><b>abroad, or from public or private research centers</b><br/>L’archive ouverte pluridisciplinaire HAL, est +<br/>destin´ee au d´epˆot et `a la diffusion de documents +<br/>scientifiques de niveau recherche, publi´es ou non, +<br/>´emanant des ´etablissements d’enseignement et de +<br/>recherche fran¸cais ou ´etrangers, des laboratoires +<br/>publics ou priv´es. +</td><td>('3095534', 'Saleh Mosaddegh', 'saleh mosaddegh')<br/>('3095534', 'Saleh Mosaddegh', 'saleh mosaddegh')</td><td></td></tr><tr><td>1d4c25f9f8f08f5a756d6f472778ab54a7e6129d</td><td>International Journal of Science and Research (IJSR) +<br/>ISSN (Online): 2319-7064 +<br/>Index Copernicus Value (2014): 6.14 | Impact Factor (2014): 4.438 +<br/>An Innovative Mean Approach for Plastic Surgery +<br/>Face Recognition +<br/>1 Student of M.E., Department of Electronics & Telecommunication Engineering, +<br/><b>P. R. Patil College of Engineering, Amravati Maharashtra India</b><br/>2 Assistant Professor, Department of Electronics & Telecommunication Engineering, +<br/><b>P. R. Patil College of Engineering, Amravati Maharashtra India</b></td><td>('2936550', 'Umesh W. Hore', 'umesh w. hore')</td><td></td></tr><tr><td>71b376dbfa43a62d19ae614c87dd0b5f1312c966</td><td>The Temporal Connection Between Smiles and Blinks </td><td>('2048839', 'Laura C. Trutoiu', 'laura c. trutoiu')<br/>('1788773', 'Jessica K. Hodgins', 'jessica k. hodgins')<br/>('1737918', 'Jeffrey F. Cohn', 'jeffrey f. cohn')</td><td></td></tr><tr><td>71b07c537a9e188b850192131bfe31ef206a39a0</td><td>Image and Vision Computing 47 (2016) 3–18 <br/>Contents lists available at ScienceDirect <br/>Image and Vision Computing @@ -34680,7 +44334,13 @@ <br/>of objects from a single input image <br/>1Computer Science and Engineering and Information Technology, Shiraz <br/><b>university, Shiraz, Iran</b><br/>November 17, 2017 -</td><td>('34649340', 'Shima Kamyab', 'shima kamyab')<br/>('2014752', 'Zohreh Azimifar', 'zohreh azimifar')</td><td></td></tr><tr><td>71f36c8e17a5c080fab31fce1ffea9551fc49e47</td><td>Predicting Failures of Vision Systems +</td><td>('34649340', 'Shima Kamyab', 'shima kamyab')<br/>('2014752', 'Zohreh Azimifar', 'zohreh azimifar')</td><td></td></tr><tr><td>7142ac9e4d5498037aeb0f459f278fd28dae8048</td><td>Semi-Supervised Learning for Optical Flow +<br/>with Generative Adversarial Networks +<br/><b>University of California, Merced</b><br/>2Virginia Tech +<br/>3Nvidia Research +</td><td>('2268189', 'Wei-Sheng Lai', 'wei-sheng lai')<br/>('3068086', 'Jia-Bin Huang', 'jia-bin huang')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td>1{wlai24|mhyang}@ucmerced.edu +<br/>2jbhuang@vt.edu +</td></tr><tr><td>71f36c8e17a5c080fab31fce1ffea9551fc49e47</td><td>Predicting Failures of Vision Systems <br/>1Virginia Tech <br/>2Univ. of Texas at Austin <br/>3Univ. of Washington @@ -34688,6 +44348,11 @@ <br/>2jiuling@utexas.edu <br/>3ali@cs.uw.edu <br/>4hebert@ri.cmu.edu +</td></tr><tr><td>7117ed0be436c0291bc6fb6ea6db18de74e2464a</td><td>Under review as a conference paper at ICLR 2017 +<br/>WARPED CONVOLUTIONS: EFFICIENT INVARIANCE TO +<br/>SPATIAL TRANSFORMATIONS +<br/>Visual Geometry Group +<br/><b>University of Oxford</b></td><td>('36478254', 'João F. Henriques', 'joão f. henriques')</td><td>{joao,vedaldi}@robots.ox.ac.uk </td></tr><tr><td>71e6a46b32a8163c9eda69e1badcee6348f1f56a</td><td>Visually Interpreting Names as Demographic Attributes <br/>by Exploiting Click-Through Data <br/><b>National Taiwan University, Taipei, Taiwan</b><br/><b>FX Palo Alto Laboratory, Inc., California, USA</b></td><td>('35081710', 'Yan-Ying Chen', 'yan-ying chen')<br/>('1692811', 'Yin-Hsi Kuo', 'yin-hsi kuo')<br/>('2580465', 'Chun-Che Wu', 'chun-che wu')<br/>('1716836', 'Winston H. Hsu', 'winston h. hsu')</td><td>{yanying,kuonini,kenwu0721}@gmail.com, whsu@ntu.edu.tw @@ -34706,14 +44371,29 @@ <br/>Department of Computer <br/>Science, <br/>Lahore, Pakistan -<br/><b>University of Gujrat, Pakistan</b><br/><b>University of Gujrat, Pakistan</b></td><td>('35637737', 'Muhammad Nabeel Asim', 'muhammad nabeel asim')<br/>('3245405', 'Abdur Rehman', 'abdur rehman')<br/>('1981732', 'Umar Shoaib', 'umar shoaib')</td><td></td></tr><tr><td>716d6c2eb8a0d8089baf2087ce9fcd668cd0d4c0</td><td>SMITH & DYER: 3D FACIAL LANDMARK ESTIMATION +<br/><b>University of Gujrat, Pakistan</b><br/><b>University of Gujrat, Pakistan</b></td><td>('35637737', 'Muhammad Nabeel Asim', 'muhammad nabeel asim')<br/>('3245405', 'Abdur Rehman', 'abdur rehman')<br/>('1981732', 'Umar Shoaib', 'umar shoaib')</td><td></td></tr><tr><td>714d487571ca0d676bad75c8fa622d6f50df953b</td><td>eBear: An Expressive Bear-Like Robot +</td><td>('49470290', 'Xiao Zhang', 'xiao zhang')<br/>('2314025', 'Ali Mollahosseini', 'ali mollahosseini')<br/>('29764067', 'Evan Boucher', 'evan boucher')<br/>('1783240', 'Richard M. Voyles', 'richard m. voyles')</td><td></td></tr><tr><td>716d6c2eb8a0d8089baf2087ce9fcd668cd0d4c0</td><td>SMITH & DYER: 3D FACIAL LANDMARK ESTIMATION <br/>Pose-Robust 3D Facial Landmark Estimation <br/>from a Single 2D Image <br/>http://www.cs.wisc.edu/~bmsmith <br/>http://www.cs.wisc.edu/~dyer <br/>Department of Computer Sciences <br/><b>University of Wisconsin-Madison</b><br/>Madison, WI USA -</td><td>('2721523', 'Brandon M. Smith', 'brandon m. smith')<br/>('1724754', 'Charles R. Dyer', 'charles r. dyer')</td><td></td></tr><tr><td>71e56f2aebeb3c4bb3687b104815e09bb4364102</td><td>Video Co-segmentation for Meaningful Action Extraction +</td><td>('2721523', 'Brandon M. Smith', 'brandon m. smith')<br/>('1724754', 'Charles R. Dyer', 'charles r. dyer')</td><td></td></tr><tr><td>7143518f847b0ec57a0ff80e0304c89d7e924d9a</td><td>Speeding-up Age Estimation in Intelligent +<br/>Demographics System via Network Optimization +<br/><b>School of Computer and Information, Hefei University of Technology, Hefei, China</b><br/><b>School of Computer Science and Engineering, Nanyang Technological University, Singapore</b></td><td>('49941674', 'Zhenzhen Hu', 'zhenzhen hu')<br/>('7739626', 'Peng Sun', 'peng sun')<br/>('40096128', 'Yonggang Wen', 'yonggang wen')</td><td>huzhen.ice@gmail.com, {sunp0003, ygwen}@ntu.edu.sg +</td></tr><tr><td>710011644006c18291ad512456b7580095d628a2</td><td>Learning Residual Images for Face Attribute Manipulation +<br/>Fujitsu Research & Development Center, Beijing, China. +</td><td>('48157627', 'Wei Shen', 'wei shen')<br/>('2113095', 'Rujie Liu', 'rujie liu')</td><td>{shenwei, rjliu}@cn.fujitsu.com +</td></tr><tr><td>713db3874b77212492d75fb100a345949f3d3235</td><td>Deep Semantic Face Deblurring +<br/><b>Beijing Institute of Technology</b><br/><b>University of California, Merced</b><br/>3Nvidia +<br/>4Google Cloud +<br/>https://sites.google.com/site/ziyishenmi/cvpr18_face_deblur +</td><td>('2182388', 'Ziyi Shen', 'ziyi shen')<br/>('2268189', 'Wei-Sheng Lai', 'wei-sheng lai')<br/>('39001620', 'Tingfa Xu', 'tingfa xu')<br/>('1690538', 'Jan Kautz', 'jan kautz')<br/>('1715634', 'Ming-Hsuan Yang', 'ming-hsuan yang')</td><td></td></tr><tr><td>715b69575dadd7804b4f8ccb419a3ad8b7b7ca89</td><td>1 +<br/>Testing separability and independence of perceptual +<br/>dimensions with general recognition theory: A tutorial and +<br/>new R package (grtools)1 +<br/><b>Florida International University</b><br/><b>University of California, Santa Barbara</b><br/><b>Florida International University</b><br/><b>University of California, Santa Barbara</b></td><td>('2850756', 'Fabian A. Soto', 'fabian a. soto')<br/>('33897174', 'Johnny Fonseca', 'johnny fonseca')<br/>('5854837', 'F. Gregory Ashby', 'f. gregory ashby')</td><td></td></tr><tr><td>71e56f2aebeb3c4bb3687b104815e09bb4364102</td><td>Video Co-segmentation for Meaningful Action Extraction <br/><b>National University of Singapore, Singapore</b><br/><b>National University of Singapore Research Institute, Suzhou, China</b></td><td>('3036190', 'Jiaming Guo', 'jiaming guo')<br/>('3119455', 'Zhuwen Li', 'zhuwen li')<br/>('1809333', 'Steven Zhiying Zhou', 'steven zhiying zhou')</td><td>{guo.jiaming, lizhuwen, eleclf, elezzy}@nus.edu.sg </td></tr><tr><td>711bb5f63139ee7a9b9aef21533f959671a7d80e</td><td><b>Helsinki University of Technology Laboratory of Computational Engineering Publications</b><br/>Teknillisen korkeakoulun Laskennallisen tekniikan laboratorion julkaisuja <br/>Espoo 2007 @@ -34737,9 +44417,26 @@ </td><td>('1732556', 'Terry Windeatt', 'terry windeatt')</td><td></td></tr><tr><td>76673de6d81bedd6b6be68953858c5f1aa467e61</td><td>Discovering a Lexicon of Parts and Attributes <br/><b>Toyota Technological Institute at Chicago</b><br/>Chicago, IL 60637, USA </td><td>('35208858', 'Subhransu Maji', 'subhransu maji')</td><td>smaji@ttic.edu +</td></tr><tr><td>76cd5e43df44e389483f23cb578a9015d1483d70</td><td>BORGHI ET AL.: FACE VERIFICATION FROM DEPTH +<br/>Face Verification from Depth using +<br/>Privileged Information +<br/>Department of Engineering +<br/>"Enzo Ferrari" +<br/><b>University of Modena and Reggio</b><br/>Emilia +<br/>Modena, Italy +</td><td>('12010968', 'Guido Borghi', 'guido borghi')<br/>('2035969', 'Stefano Pini', 'stefano pini')<br/>('32044032', 'Filippo Grazioli', 'filippo grazioli')<br/>('1723285', 'Roberto Vezzani', 'roberto vezzani')<br/>('1741922', 'Rita Cucchiara', 'rita cucchiara')</td><td>guido.borghi@unimore.it +<br/>stefano.pini@unimore.it +<br/>filippo.grazioli@unimore.it +<br/>roberto.vezzani@unimore.it +<br/>rita.cucchiara@unimore.it </td></tr><tr><td>7643861bb492bf303b25d0306462f8fb7dc29878</td><td>Speeding up 2D-Warping for Pose-Invariant Face Recognition <br/><b>Human Language Technology and Pattern Recognition Group, RWTH Aachen University, Germany</b></td><td>('1804963', 'Harald Hanselmann', 'harald hanselmann')<br/>('1685956', 'Hermann Ney', 'hermann ney')</td><td>surname@cs.rwth-aachen.de -</td></tr><tr><td>760a712f570f7a618d9385c0cee7e4d0d6a78ed2</td><td></td><td></td><td></td></tr><tr><td>76ce3d35d9370f0e2e27cfd29ea0941f1462895f</td><td>Hindawi Publishing Corporation +</td></tr><tr><td>760a712f570f7a618d9385c0cee7e4d0d6a78ed2</td><td></td><td></td><td></td></tr><tr><td>76b11c281ac47fe6d95e124673a408ee9eb568e3</td><td>International Journal of Latest Engineering and Management Research (IJLEMR) +<br/>ISSN: 2455-4847 +<br/>www.ijlemr.com || Volume 02 - Issue 03 || March 2017 || PP. 59-71 +<br/>REAL-TIME MULTI VIEW FACE DETECTION AND POSE +<br/>ESTIMATION +<br/><b>U. G STUDENTS, DEPT OF CSE, ALPHA COLLEGE OF ENGINEERING, CHENNAI</b><br/><b>ALPHA COLLEGE OF ENGINEERING, CHENNAI</b></td><td></td><td></td></tr><tr><td>76ce3d35d9370f0e2e27cfd29ea0941f1462895f</td><td>Hindawi Publishing Corporation <br/>e Scientific World Journal <br/>Volume 2014, Article ID 528080, 13 pages <br/>http://dx.doi.org/10.1155/2014/528080 @@ -34822,7 +44519,18 @@ <br/>”Doctor of Philosophy” <br/>by <br/><b>Submitted to the Senate of the Hebrew University</b><br/>August / 2013 -</td><td>('39161025', 'Alon Zweig', 'alon zweig')</td><td></td></tr><tr><td>76d939f73a327bf1087d91daa6a7824681d76ea1</td><td>A Thermal Facial Emotion Database +</td><td>('39161025', 'Alon Zweig', 'alon zweig')</td><td></td></tr><tr><td>764882e6779fbee29c3d87e00302befc52d2ea8d</td><td>Deep Approximately Orthogonal Nonnegative +<br/>Matrix Factorization for Clustering +<br/>School of Automation +<br/>School of Automation +<br/>School of Automation +<br/><b>Guangdong University of Technology</b><br/><b>Guangdong University of Technology</b><br/><b>Guangdong University of Technology</b><br/>Guangzhou, China +<br/>Guangzhou, China +<br/>Guangzhou, China +</td><td>('30185240', 'Yuning Qiu', 'yuning qiu')<br/>('1764724', 'Guoxu Zhou', 'guoxu zhou')<br/>('2454506', 'Kan Xie', 'kan xie')</td><td>yn.qiu@foxmail.com +<br/>guoxu.zhou@qq.com +<br/>kanxiegdut@gmail.com +</td></tr><tr><td>76d939f73a327bf1087d91daa6a7824681d76ea1</td><td>A Thermal Facial Emotion Database <br/>and Its Analysis <br/><b>Japan Advanced Institute of Science and Technology</b><br/>1-1 Asahidai, Nomi, Ishikawa, Japan <br/><b>University of Science, Ho Chi Minh city</b><br/>227 Nguyen Van Cu, Ho Chi Minh city, Vietnam @@ -34913,7 +44621,34 @@ <br/>EEE A&E SYSTEMS MAGAZINE VOL. 19, NO. 1 JANUARY 2004 PART 2: TUTORIALS-BAGGENSTOSS <br/>37 </td><td></td><td>RI, 02841, E-mail: (p.m.baggenstoss@ieee.arg). -</td></tr><tr><td>7636f94ddce79f3dea375c56fbdaaa0f4d9854aa</td><td>Appl. Math. Inf. Sci. 6 No. 2S pp. 403S-408S (2012) +</td></tr><tr><td>766728bac030b169fcbc2fbafe24c6e22a58ef3c</td><td>A survey of deep facial landmark detection +<br/>Yongzhe Yan1,2 +<br/>Thierry Chateau1 +<br/>1 Université Clermont Auvergne, France +<br/>2 Wisimage, France +<br/>3 Université de Lyon, CNRS, INSA Lyon, LIRIS, UMR5205, Lyon, France +<br/>Résumé +<br/>La détection de landmarks joue un rôle crucial dans de +<br/>nombreuses applications d’analyse du visage comme la +<br/>reconnaissance de l’identité, des expressions, l’animation +<br/>d’avatar, la reconstruction 3D du visage, ainsi que pour +<br/>les applications de réalité augmentée comme la pose de +<br/>masque ou de maquillage virtuel. L’avènement de l’ap- +<br/>prentissage profond a permis des progrès très importants +<br/>dans ce domaine, y compris sur les corpus non contraints +<br/>(in-the-wild). Nous présentons ici un état de l’art cen- +<br/>tré sur la détection 2D dans une image fixe, et les mé- +<br/>thodes spécifiques pour la vidéo. Nous présentons ensuite +<br/>les corpus existants pour ces trois tâches, ainsi que les mé- +<br/>triques d’évaluations associées. Nous exposons finalement +<br/>quelques résultats, ainsi que quelques pistes de recherche. +<br/>Mots Clef +<br/>Détection de landmark facial, Alignement de visage, Deep +<br/>learning +</td><td>('3015472', 'Xavier Naturel', 'xavier naturel')<br/>('50493659', 'Christophe Garcia', 'christophe garcia')<br/>('48601809', 'Christophe Blanc', 'christophe blanc')<br/>('1762557', 'Stefan Duffner', 'stefan duffner')</td><td>yongzhe.yan@etu.uca.fr +</td></tr><tr><td>7697295ee6fc817296bed816ac5cae97644c2d5b</td><td>Detecting and Recognizing Human-Object Interactions +<br/>Facebook AI Research (FAIR) +</td><td>('2082991', 'Georgia Gkioxari', 'georgia gkioxari')<br/>('39353098', 'Kaiming He', 'kaiming he')</td><td></td></tr><tr><td>7636f94ddce79f3dea375c56fbdaaa0f4d9854aa</td><td>Appl. Math. Inf. Sci. 6 No. 2S pp. 403S-408S (2012) <br/> An International Journal <br/>© 2012 NSP <br/>Applied Mathematics & Information Sciences @@ -34931,7 +44666,9 @@ </td><td>('2470198', 'Jiaolong Xu', 'jiaolong xu')</td><td></td></tr><tr><td>1ce3a91214c94ed05f15343490981ec7cc810016</td><td>Exploring Photobios <br/><b>University of Washington</b><br/>2Adobe Systems† <br/>3Google Inc. -</td><td>('2419955', 'Ira Kemelmacher-Shlizerman', 'ira kemelmacher-shlizerman')<br/>('2177801', 'Eli Shechtman', 'eli shechtman')<br/>('9748713', 'Rahul Garg', 'rahul garg')<br/>('1679223', 'Steven M. Seitz', 'steven m. seitz')</td><td></td></tr><tr><td>1c2724243b27a18a2302f12dea79d9a1d4460e35</td><td>Fisher+Kernel Criterion for Discriminant Analysis* +</td><td>('2419955', 'Ira Kemelmacher-Shlizerman', 'ira kemelmacher-shlizerman')<br/>('2177801', 'Eli Shechtman', 'eli shechtman')<br/>('9748713', 'Rahul Garg', 'rahul garg')<br/>('1679223', 'Steven M. Seitz', 'steven m. seitz')</td><td></td></tr><tr><td>1c9efb6c895917174ac6ccc3bae191152f90c625</td><td>Unifying Identification and Context Learning for Person Recognition +<br/><b>CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong</b></td><td>('39360892', 'Qingqiu Huang', 'qingqiu huang')<br/>('50446092', 'Yu Xiong', 'yu xiong')<br/>('1807606', 'Dahua Lin', 'dahua lin')</td><td>{hq016, xy017, dhlin}@ie.cuhk.edu.hk +</td></tr><tr><td>1c2724243b27a18a2302f12dea79d9a1d4460e35</td><td>Fisher+Kernel Criterion for Discriminant Analysis* <br/><b>National Laboratory on Machine Perception, Peking University, Beijing, P.R. China</b><br/><b>the Chinese University of Hong Kong, Shatin, Hong Kong</b><br/>3 MOE-Microsoft Key Laboratory of Multimedia Computing and Communication & Department of EEIS, <br/><b>University of Science and Technology of China, Hefei, Anhui, P. R. China</b><br/>4Microsoft Research Asia, Beijing, P.R. China <br/> @@ -34997,7 +44734,11 @@ <br/>11,130 <br/>17,345 <br/>16,721 -</td><td>('1996796', 'Zaeem Hussain', 'zaeem hussain')<br/>('2365530', 'Mingda Zhang', 'mingda zhang')<br/>('3186356', 'Xiaozhong Zhang', 'xiaozhong zhang')<br/>('9085797', 'Keren Ye', 'keren ye')<br/>('40540691', 'Christopher Thomas', 'christopher thomas')<br/>('6004292', 'Zuha Agha', 'zuha agha')<br/>('34493995', 'Nathan Ong', 'nathan ong')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td></td></tr><tr><td>1ce4587e27e2cf8ba5947d3be7a37b4d1317fbee</td><td>Deep fusion of visual signatures +</td><td>('1996796', 'Zaeem Hussain', 'zaeem hussain')<br/>('2365530', 'Mingda Zhang', 'mingda zhang')<br/>('3186356', 'Xiaozhong Zhang', 'xiaozhong zhang')<br/>('9085797', 'Keren Ye', 'keren ye')<br/>('40540691', 'Christopher Thomas', 'christopher thomas')<br/>('6004292', 'Zuha Agha', 'zuha agha')<br/>('34493995', 'Nathan Ong', 'nathan ong')<br/>('1770205', 'Adriana Kovashka', 'adriana kovashka')</td><td></td></tr><tr><td>1cfe3533759bf95be1fce8ce1d1aa2aeb5bfb4cc</td><td>Recognition of Facial Gestures based on Support +<br/>Vector Machines +<br/><b>Faculty of Informatics, University of Debrecen, Hungary</b><br/>H-4010 Debrecen P.O.Box 12. +</td><td>('47547897', 'Attila Fazekas', 'attila fazekas')</td><td>Attila.Fazekas@inf.unideb.hu +</td></tr><tr><td>1ce4587e27e2cf8ba5947d3be7a37b4d1317fbee</td><td>Deep fusion of visual signatures <br/>for client-server facial analysis <br/>Normandie Univ, UNICAEN, <br/>ENSICAEN, CNRS, GREYC @@ -35266,7 +45007,14 @@ <br/>song@iis.sinica.edu.tw </td></tr><tr><td>1c93b48abdd3ef1021599095a1a5ab5e0e020dd5</td><td>JOURNAL OF LATEX CLASS FILES, VOL. *, NO. *, JANUARY 2009 <br/>A Compositional and Dynamic Model for Face Aging -</td><td>('3133970', 'Song-Chun Zhu', 'song-chun zhu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td></td></tr><tr><td>1cbd3f96524ca2258fd2d5c504c7ea8da7fb1d16</td><td>Fusion of audio-visual features using hierarchical classifier systems for +</td><td>('3133970', 'Song-Chun Zhu', 'song-chun zhu')<br/>('1685914', 'Shiguang Shan', 'shiguang shan')<br/>('1710220', 'Xilin Chen', 'xilin chen')</td><td></td></tr><tr><td>1c41965c5e1f97b1504c1bdde8037b5e0417da5e</td><td>Interaction-aware Spatio-temporal Pyramid +<br/>Attention Networks for Action Classification +<br/><b>University of Chinese Academy of Sciences</b><br/>2 CAS Center for Excellence in Brain Science and Intelligence Technology, National +<br/><b>Laboratory of Pattern Recognition, Institute of Automation, CAS</b><br/>3 Meitu, 4 National Computer network Emergency Response technical +<br/>Team/Coordination Center of China +</td><td>('1807325', 'Yang Du', 'yang du')<br/>('2034987', 'Chunfeng Yuan', 'chunfeng yuan')<br/>('46708348', 'Bing Li', 'bing li')<br/>('40027215', 'Lili Zhao', 'lili zhao')<br/>('2082374', 'Yangxi Li', 'yangxi li')<br/>('40506509', 'Weiming Hu', 'weiming hu')</td><td>duyang2014@ia.ac.cn,{cfyuan,bli,wmhu}@nlpr.ia.ac.cn, +<br/>lili.zhao@meitu.com, liyangxi@outlook.com +</td></tr><tr><td>1cbd3f96524ca2258fd2d5c504c7ea8da7fb1d16</td><td>Fusion of audio-visual features using hierarchical classifier systems for <br/>the recognition of affective states and the state of depression <br/><b>Institute of Neural Information Processing, Ulm University, Ulm, Germany</b><br/>Keywords: <br/>Emotion Recognition, Multiple Classifier Systems, Affective Computing, Information Fusion @@ -35288,7 +45036,7 @@ <br/>Distribution Learning for Age Estimation <br/>Key Lab of Computer Network and Information Integration (Ministry of Education) <br/><b>School of Computer Science and Engineering, Southeast University, Nanjing 211189, China</b></td><td>('2442058', 'Xu Yang', 'xu yang')<br/>('1735299', 'Xin Geng', 'xin geng')<br/>('1725992', 'Deyu Zhou', 'deyu zhou')</td><td>{x.yang,xgeng,d.zhou}@seu.edu.cn -</td></tr><tr><td>82f8652c2059187b944ce65e87bacb6b765521f6</td><td>Discriminative Object Categorization with +</td></tr><tr><td>1c6e22516ceb5c97c3caf07a9bd5df357988ceda</td><td></td><td></td><td></td></tr><tr><td>82f8652c2059187b944ce65e87bacb6b765521f6</td><td>Discriminative Object Categorization with <br/>External Semantic Knowledge <br/>Dissertation Proposal <br/>by @@ -35297,12 +45045,18 @@ <br/>Prof. Kristen Grauman (Advisor) <br/>Prof. Fei Sha <br/>Prof. J. K. Aggarwal -</td><td>('35788904', 'Sung Ju Hwang', 'sung ju hwang')<br/>('1797655', 'Raymond Mooney', 'raymond mooney')<br/>('2302443', 'Pradeep Ravikumar', 'pradeep ravikumar')</td><td></td></tr><tr><td>82bef8481207de9970c4dc8b1d0e17dced706352</td><td></td><td></td><td></td></tr><tr><td>82d2af2ffa106160a183371946e466021876870d</td><td>A Novel Space-Time Representation on the Positive Semidefinite Cone +</td><td>('35788904', 'Sung Ju Hwang', 'sung ju hwang')<br/>('1797655', 'Raymond Mooney', 'raymond mooney')<br/>('2302443', 'Pradeep Ravikumar', 'pradeep ravikumar')</td><td></td></tr><tr><td>82bef8481207de9970c4dc8b1d0e17dced706352</td><td></td><td></td><td></td></tr><tr><td>825f56ff489cdd3bcc41e76426d0070754eab1a8</td><td>Making Convolutional Networks Recurrent for Visual Sequence Learning +<br/>NVIDIA +</td><td>('40058797', 'Xiaodong Yang', 'xiaodong yang')</td><td>{xiaodongy,pmolchanov,jkautz}@nvidia.com +</td></tr><tr><td>82d2af2ffa106160a183371946e466021876870d</td><td>A Novel Space-Time Representation on the Positive Semidefinite Cone <br/>for Facial Expression Recognition <br/>1IMT Lille Douai, Univ. Lille, CNRS, UMR 9189 – CRIStAL – <br/>Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France <br/>2Univ. Lille, CNRS, UMR 8524, Laboratoire Paul Painlev´e, F-59000 Lille, France. -</td><td>('37809060', 'Anis Kacem', 'anis kacem')<br/>('2909056', 'Mohamed Daoudi', 'mohamed daoudi')<br/>('2125606', 'Boulbaba Ben Amor', 'boulbaba ben amor')</td><td></td></tr><tr><td>82ccd62f70e669ec770daf11d9611cab0a13047e</td><td>Sparse Variation Pattern for Texture Classification +</td><td>('37809060', 'Anis Kacem', 'anis kacem')<br/>('2909056', 'Mohamed Daoudi', 'mohamed daoudi')<br/>('2125606', 'Boulbaba Ben Amor', 'boulbaba ben amor')</td><td></td></tr><tr><td>824d1db06e1c25f7681e46199fd02cb5fc343784</td><td>Representing Relative Visual Attributes +<br/>with a Reference-Point-Based Decision Model +<br/>Marc T. Law +<br/><b>University of Toronto</b><br/><b>Shanghai Jiao Tong University</b><br/><b>University of Michigan-Shanghai Jiao Tong University Joint Institute</b></td><td>('38481975', 'Paul Weng', 'paul weng')</td><td></td></tr><tr><td>82ccd62f70e669ec770daf11d9611cab0a13047e</td><td>Sparse Variation Pattern for Texture Classification <br/>Electrical Engineering Department <br/>Computer Science and Software Engineering <br/>Electrical Engineering Department @@ -35312,7 +45066,10 @@ </td><td>('2014145', 'Mohammad Tavakolian', 'mohammad tavakolian')<br/>('3046235', 'Farshid Hajati', 'farshid hajati')<br/>('1747500', 'Ajmal S. Mian', 'ajmal s. mian')<br/>('2997971', 'Soheila Gheisari', 'soheila gheisari')</td><td>m tavakolian,hajati@tafreshu.ac.ir <br/>ajmal.mian@uwa.edu.au <br/>gheisari.s@iauctb.ac.ir -</td></tr><tr><td>82c303cf4852ad18116a2eea31e2291325bc19c3</td><td>Journal of Image and Graphics, Volume 2, No.1, June, 2014 +</td></tr><tr><td>82eff71af91df2ca18aebb7f1153a7aed16ae7cc</td><td>MSU-AVIS dataset: +<br/>Fusing Face and Voice Modalities for Biometric +<br/>Recognition in Indoor Surveillance Videos +<br/><b>Michigan State University, USA</b><br/><b>Yarmouk University, Jordan</b></td><td>('39617163', 'Anurag Chowdhury', 'anurag chowdhury')<br/>('2447931', 'Yousef Atoum', 'yousef atoum')<br/>('1849929', 'Luan Tran', 'luan tran')<br/>('49543771', 'Xiaoming Liu', 'xiaoming liu')<br/>('1698707', 'Arun Ross', 'arun ross')</td><td></td></tr><tr><td>82c303cf4852ad18116a2eea31e2291325bc19c3</td><td>Journal of Image and Graphics, Volume 2, No.1, June, 2014 <br/>Fusion Based FastICA Method: Facial Expression <br/>Recognition <br/><b>Computer Science, Engineering and Mathematics School, Flinders University, Australia</b></td><td>('3105876', 'Humayra B. Ali', 'humayra b. ali')<br/>('1739260', 'David M W Powers', 'david m w powers')</td><td>Email: {ali0041, david.powers}@flinders.edu.au @@ -35322,7 +45079,26 @@ </td><td></td><td></td></tr><tr><td>82a4a35b2bae3e5c51f4d24ea5908c52973bd5be</td><td>Real-time emotion recognition for gaming using <br/>deep convolutional network features <br/>S´ebastien Ouellet -</td><td></td><td></td></tr><tr><td>82f4e8f053d20be64d9318529af9fadd2e3547ef</td><td>Technical Report: +</td><td></td><td></td></tr><tr><td>82a610a59c210ff77cfdde7fd10c98067bd142da</td><td>UC San Diego +<br/>UC San Diego Electronic Theses and Dissertations +<br/>Title +<br/>Human attention and intent analysis using robust visual cues in a Bayesian framework +<br/>Permalink +<br/>https://escholarship.org/uc/item/1cb8d7vw +<br/>Author +<br/>McCall, Joel Curtis +<br/>Publication Date +<br/>2006-01-01 +<br/>Peer reviewed|Thesis/dissertation +<br/>eScholarship.org +<br/>Powered by the California Digital Library +<br/><b>University of California</b></td><td></td><td></td></tr><tr><td>829f390b3f8ad5856e7ba5ae8568f10cee0c7e6a</td><td>International Journal of Computer Applications (0975 – 8887) +<br/>Volume 57– No.20, November 2012 +<br/>A Robust Rotation Invariant Multiview Face Detection in +<br/>Erratic Illumination Condition +<br/>G.Nirmala Priya +<br/>Associate Professor, Department of ECE +<br/><b>Sona College of Technology</b></td><td>('48201570', 'Salem', 'salem')</td><td></td></tr><tr><td>82f4e8f053d20be64d9318529af9fadd2e3547ef</td><td>Technical Report: <br/>Multibiometric Cryptosystems </td><td>('2743820', 'Abhishek Nagar', 'abhishek nagar')<br/>('34633765', 'Karthik Nandakumar', 'karthik nandakumar')<br/>('40437942', 'Anil K. Jain', 'anil k. jain')</td><td></td></tr><tr><td>82b43bc9213230af9db17322301cbdf81e2ce8cc</td><td>Attention-Set based Metric Learning for Video Face Recognition <br/>Center for Research on Intelligent Perception and Computing, @@ -35358,13 +45134,21 @@ <br/>Journal Computer Vision, Vol. 25, No. 1, pp. 23-48, 1997. <br/>10. <br/>Recognition using a State-Based Model of Spatially-Localized Facial -</td><td>('1689298', 'Ahmed', 'ahmed')<br/>('1689298', 'Ahmed', 'ahmed')<br/>('29977973', 'Angle', 'angle')<br/>('20765969', 'Bolle', 'bolle')<br/>('16848439', 'Bourel', 'bourel')</td><td></td></tr><tr><td>82e66c4832386cafcec16b92ac88088ffd1a1bc9</td><td>OpenFace: A general-purpose face recognition +</td><td>('1689298', 'Ahmed', 'ahmed')<br/>('1689298', 'Ahmed', 'ahmed')<br/>('29977973', 'Angle', 'angle')<br/>('20765969', 'Bolle', 'bolle')<br/>('16848439', 'Bourel', 'bourel')</td><td></td></tr><tr><td>82417d8ec8ac6406f2d55774a35af2a1b3f4b66e</td><td>Some faces are more equal than others: +<br/>Hierarchical organization for accurate and +<br/>efficient large-scale identity-based face retrieval +<br/>GREYC, CNRS UMR 6072, Universit´e de Caen Basse-Normandie, France1 +<br/>Technicolor, Rennes, France2 +</td><td>('48467774', 'Binod Bhattarai', 'binod bhattarai')<br/>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>82e66c4832386cafcec16b92ac88088ffd1a1bc9</td><td>OpenFace: A general-purpose face recognition <br/>library with mobile applications <br/>June 2016 <br/>CMU-CS-16-118 <br/>School of Computer Science <br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA 15213 -<br/><b>Poznan University of Technology</b></td><td>('1773498', 'Brandon Amos', 'brandon amos')<br/>('1747303', 'Mahadev Satyanarayanan', 'mahadev satyanarayanan')</td><td></td></tr><tr><td>826c66bd182b54fea3617192a242de1e4f16d020</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE +<br/><b>Poznan University of Technology</b></td><td>('1773498', 'Brandon Amos', 'brandon amos')<br/>('1747303', 'Mahadev Satyanarayanan', 'mahadev satyanarayanan')</td><td></td></tr><tr><td>82eb267b8e86be0b444e841b4b4ed4814b6f1942</td><td>Single Image 3D Interpreter Network +<br/><b>Massachusetts Institute of Technology</b><br/><b>Stanford University</b><br/>3Facebook AI Research +<br/>4Google Research +</td><td>('3045089', 'Jiajun Wu', 'jiajun wu')<br/>('3222730', 'Tianfan Xue', 'tianfan xue')<br/>('35198686', 'Joseph J. Lim', 'joseph j. lim')<br/>('39402399', 'Yuandong Tian', 'yuandong tian')<br/>('1763295', 'Joshua B. Tenenbaum', 'joshua b. tenenbaum')<br/>('1690178', 'Antonio Torralba', 'antonio torralba')<br/>('1768236', 'William T. Freeman', 'william t. freeman')</td><td></td></tr><tr><td>826c66bd182b54fea3617192a242de1e4f16d020</td><td>978-1-5090-4117-6/17/$31.00 ©2017 IEEE <br/>1602 <br/>ICASSP 2017 </td><td></td><td></td></tr><tr><td>499f1d647d938235e9186d968b7bb2ab20f2726d</td><td>Face Recognition via Archetype Hull Ranking @@ -35392,7 +45176,12 @@ <br/><b>University of Business Agriculture and Technology, Dhaka-1230, Bangladesh</b><br/> </td><td>('2832495', 'Md. Hafizur Rahman', 'md. hafizur rahman')<br/>('2226529', 'Suman Chowdhury', 'suman chowdhury')<br/>('36231591', 'Md. Abul Bashar', 'md. abul bashar')</td><td></td></tr><tr><td>49820ae612b3c0590a8a78a725f4f378cb605cd1</td><td>Evaluation of Smile Detection Methods with <br/>Images in Real-world Scenarios -<br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>('22550265', 'Zhoucong Cui', 'zhoucong cui')<br/>('1678529', 'Shuo Zhang', 'shuo zhang')<br/>('23224233', 'Jiani Hu', 'jiani hu')<br/>('1774956', 'Weihong Deng', 'weihong deng')</td><td></td></tr><tr><td>49dd4b359f8014e85ed7c106e7848049f852a304</td><td></td><td></td><td></td></tr><tr><td>49e85869fa2cbb31e2fd761951d0cdfa741d95f3</td><td>253 +<br/><b>Beijing University of Posts and Telecommunications, Beijing, China</b></td><td>('22550265', 'Zhoucong Cui', 'zhoucong cui')<br/>('1678529', 'Shuo Zhang', 'shuo zhang')<br/>('23224233', 'Jiani Hu', 'jiani hu')<br/>('1774956', 'Weihong Deng', 'weihong deng')</td><td></td></tr><tr><td>4972aadcce369a8c0029e6dc2f288dfd0241e144</td><td>Multi-target Unsupervised Domain Adaptation +<br/>without Exactly Shared Categories +</td><td>('2076460', 'Huanhuan Yu', 'huanhuan yu')<br/>('27096523', 'Menglei Hu', 'menglei hu')<br/>('1680768', 'Songcan Chen', 'songcan chen')</td><td></td></tr><tr><td>49dd4b359f8014e85ed7c106e7848049f852a304</td><td></td><td></td><td></td></tr><tr><td>49e975a4c60d99bcc42c921d73f8d89ec7130916</td><td>Human and computer recognition of facial expressions of emotion +<br/>J.M. Susskind a, G. Littlewort b, M.S. Bartlett b, J. Movellan b, A.K. Anderson a,c,∗ +<br/><b>b Machine Perception Laboratory, Institute of Neural Computation, University of California, San Diego, United States</b><br/><b>c Rotman Research Institute, Baycrest Centre for Geriatric Care, Toronto, Ont. M6A 2E1, Canada</b><br/><b>University of Toronto, Canada</b><br/>Available online 12 June 2006 +</td><td></td><td></td></tr><tr><td>49e85869fa2cbb31e2fd761951d0cdfa741d95f3</td><td>253 <br/>Adaptive Manifold Learning </td><td>('2923061', 'Zhenyue Zhang', 'zhenyue zhang')<br/>('1697912', 'Jing Wang', 'jing wang')<br/>('1750350', 'Hongyuan Zha', 'hongyuan zha')</td><td></td></tr><tr><td>49659fb64b1d47fdd569e41a8a6da6aa76612903</td><td></td><td></td><td></td></tr><tr><td>490a217a4e9a30563f3a4442a7d04f0ea34442c8</td><td>International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI), Vol.2, No.4, August 2013 <br/>An SOM-based Automatic Facial Expression @@ -35453,7 +45242,11 @@ <br/>Jiangjing Lv1 <br/><b>Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences</b><br/><b>University of Chinese Academy of Sciences</b><br/><b>Institute of Automation, Chinese Academy of Sciences</b></td><td>('3492237', 'Xiaohu Shao', 'xiaohu shao')<br/>('1757173', 'Junliang Xing', 'junliang xing')<br/>('2095535', 'Cheng Cheng', 'cheng cheng')<br/>('39959302', 'Xi Zhou', 'xi zhou')</td><td>{lvjiangjing,shaoxiaohu,chengcheng,zhouxi}@cigit.ac.cn <br/>jlxing@nlpr.ia.ac.cn -</td></tr><tr><td>493ec9e567c5587c4cbeb5f08ca47408ca2d6571</td><td>You et al. Complex Adapt Syst Model (2016) 4:22 +</td></tr><tr><td>49df381ea2a1e7f4059346311f1f9f45dd997164</td><td>2018 +<br/>On the Use of Client-Specific Information for Face +<br/>Presentation Attack Detection Based on Anomaly +<br/>Detection +</td><td>('1690611', 'Shervin Rahimzadeh Arashloo', 'shervin rahimzadeh arashloo')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td></td></tr><tr><td>493ec9e567c5587c4cbeb5f08ca47408ca2d6571</td><td>You et al. Complex Adapt Syst Model (2016) 4:22 <br/>DOI 10.1186/s40294‑016‑0034‑7 <br/>RESEARCH <br/>Combining graph embedding @@ -35521,7 +45314,10 @@ <br/>Aleksandar Stani´c1 <br/>Helmut B¨olcskei1 <br/>1Dept. IT & EE, ETH Zurich, Switzerland -<br/><b>University of Vienna, Austria</b></td><td>('2076040', 'Thomas Wiatowski', 'thomas wiatowski')<br/>('2208878', 'Michael Tschannen', 'michael tschannen')<br/>('1690644', 'Philipp Grohs', 'philipp grohs')</td><td></td></tr><tr><td>40ee38d7ff2871761663d8634c3a4970ed1dc058</td><td>Three-Dimensional Face Recognition: A Fishersurface +<br/><b>University of Vienna, Austria</b></td><td>('2076040', 'Thomas Wiatowski', 'thomas wiatowski')<br/>('2208878', 'Michael Tschannen', 'michael tschannen')<br/>('1690644', 'Philipp Grohs', 'philipp grohs')</td><td></td></tr><tr><td>403a108dec92363fd1f465340bd54dbfe65af870</td><td>describing images with statistics of local non-binarized pixel patterns +<br/>Local Higher-Order Statistics (LHS) +<br/>aGREYC CNRS UMR 6072, Universit´e de Caen Basse-Normandie, France +<br/><b>bMax Planck Institute for Informatics, Germany</b></td><td>('2515597', 'Gaurav Sharma', 'gaurav sharma')</td><td></td></tr><tr><td>40ee38d7ff2871761663d8634c3a4970ed1dc058</td><td>Three-Dimensional Face Recognition: A Fishersurface <br/>Approach <br/><b>The University of York, United Kingdom</b></td><td>('2023950', 'Thomas Heseltine', 'thomas heseltine')<br/>('1737428', 'Nick Pears', 'nick pears')<br/>('2405628', 'Jim Austin', 'jim austin')</td><td></td></tr><tr><td>402f6db00251a15d1d92507887b17e1c50feebca</td><td>3D Facial Action Units Recognition for Emotional <br/>Expression @@ -35565,6 +45361,21 @@ <br/>2 Environment Perception, Group Research, Daimler AG, Ulm, Germany <br/>3 Intelligent Systems Lab, Faculty of Science, Univ. of Amsterdam, The Netherlands </td><td>('1765022', 'Markus Enzweiler', 'markus enzweiler')</td><td>{uni-heidelberg.enzweiler,dariu.gavrila}@daimler.com +</td></tr><tr><td>40dd2b9aace337467c6e1e269d0cb813442313d7</td><td>This thesis has been submitted in fulfilment of the requirements for a postgraduate degree +<br/><b>e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following</b><br/>terms and conditions of use: +<br/>This work is protected by copyright and other intellectual property rights, which are +<br/>retained by the thesis author, unless otherwise stated. +<br/>A copy can be downloaded for personal non-commercial research or study, without +<br/>prior permission or charge. +<br/>This thesis cannot be reproduced or quoted extensively from without first obtaining +<br/>permission in writing from the author. +<br/>The content must not be changed in any way or sold commercially in any format or +<br/>medium without the formal permission of the author. +<br/>When referring to this work, full bibliographic details including the author, title, +<br/>awarding institution and date of the thesis must be given. +</td><td></td><td></td></tr><tr><td>407de9da58871cae7a6ded2f3a6162b9dc371f38</td><td>TraMNet - Transition Matrix Network for +<br/>Efficient Action Tube Proposals +<br/><b>Oxford Brookes University, UK</b></td><td>('1931660', 'Gurkirt Singh', 'gurkirt singh')<br/>('49348905', 'Suman Saha', 'suman saha')<br/>('1754181', 'Fabio Cuzzolin', 'fabio cuzzolin')</td><td>gurkirt.singh-2015@brookes.ac.uk </td></tr><tr><td>405526dfc79de98f5bf3c97bf4aa9a287700f15d</td><td>MegaFace: A Million Faces for Recognition at Scale <br/>D. Miller <br/>E. Brossard @@ -35575,7 +45386,10 @@ <br/>tification rates, and (b) rank-10. Recognition rates drop once the number of distractors increases. We also present first <br/>large-scale human recognition results (up to 10K distractors). Interestingly, Google’s deep learning based FaceNet is more <br/>robust at scale than humans. See http://megaface.cs.washington.edu to participate in the challenge. -</td><td></td><td></td></tr><tr><td>40cd062438c280c76110e7a3a0b2cf5ef675052c</td><td></td><td></td><td></td></tr><tr><td>40a5b32e261dc5ccc1b5df5d5338b7d3fe10370d</td><td>Feedback-Controlled Sequential Lasso Screening +</td><td></td><td></td></tr><tr><td>40cd062438c280c76110e7a3a0b2cf5ef675052c</td><td></td><td></td><td></td></tr><tr><td>40b7e590dfd1cdfa1e0276e9ca592e02c1bd2b5b</td><td>Beyond Trade-off: Accelerate FCN-based Face Detector with Higher Accuracy +<br/><b>Beihang University, 2The Chinese University of Hong Kong, 3Sensetime Group Limited</b></td><td>('12920342', 'Guanglu Song', 'guanglu song')<br/>('1715752', 'Yu Liu', 'yu liu')<br/>('40452812', 'Ming Jiang', 'ming jiang')<br/>('33598672', 'Yujie Wang', 'yujie wang')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('2858789', 'Biao Leng', 'biao leng')</td><td>{guanglusong,jiangming1406,yujiewang,lengbiao}@buaa.edu.cn, +<br/>yuliu@ee.cuhk.edu.hk, yanjunjie@sensetime.com +</td></tr><tr><td>40a5b32e261dc5ccc1b5df5d5338b7d3fe10370d</td><td>Feedback-Controlled Sequential Lasso Screening <br/>Department of Electrical Engineering <br/><b>Princeton University</b></td><td>('1719525', 'Yun Wang', 'yun wang')<br/>('1734498', 'Xu Chen', 'xu chen')<br/>('1693135', 'Peter J. Ramadge', 'peter j. ramadge')</td><td></td></tr><tr><td>40a1935753cf91f29ffe25f6c9dde2dc49bf2a3a</td><td>80 </td><td></td><td></td></tr><tr><td>40a9f3d73c622cceee5e3d6ca8faa56ed6ebef60</td><td>AUTOMATIC LIP TRACKING AND ACTION UNITS CLASSIFICATION USING @@ -35593,7 +45407,12 @@ </td><td>('3210269', 'Hadi Seyedarabi', 'hadi seyedarabi')<br/>('2488201', 'Ali Aghagolzadeh', 'ali aghagolzadeh')</td><td>email: hadis@discover.uottawa.ca <br/>email: wslee@uottawa.ca <br/>email: aghagol@tabrizu.ac.ir -</td></tr><tr><td>40389b941a6901c190fb74e95dc170166fd7639d</td><td>Automatic Facial Expression Recognition +</td></tr><tr><td>40a34d4eea5e32dfbcef420ffe2ce7c1ee0f23cd</td><td>Bridging Heterogeneous Domains With Parallel Transport For Vision and +<br/>Multimedia Applications +<br/>Dept. of Video and Multimedia Technologies Research +<br/>AT&T Labs-Research +<br/>San Francisco, CA 94108 +</td><td>('33692583', 'Raghuraman Gopalan', 'raghuraman gopalan')</td><td></td></tr><tr><td>40389b941a6901c190fb74e95dc170166fd7639d</td><td>Automatic Facial Expression Recognition <br/>Emotient <br/>http://emotient.com <br/>February 12, 2014 @@ -35621,9 +45440,16 @@ <br/>detectors embedded in digital cameras [62]. Nonetheless, considerable progress has yet to be <br/>made: Methods for face detection and tracking (the first step of automated face analysis) <br/>work well for frontal views of adult Caucasian and Asian faces [50], but their performance -</td><td>('1775637', 'Jacob Whitehill', 'jacob whitehill')<br/>('40648952', 'Marian Stewart', 'marian stewart')<br/>('1741200', 'Javier R. Movellan', 'javier r. movellan')</td><td></td></tr><tr><td>40c8cffd5aac68f59324733416b6b2959cb668fd</td><td>Pooling Facial Segments to Face: The Shallow and Deep Ends +</td><td>('1775637', 'Jacob Whitehill', 'jacob whitehill')<br/>('40648952', 'Marian Stewart', 'marian stewart')<br/>('1741200', 'Javier R. Movellan', 'javier r. movellan')</td><td></td></tr><tr><td>40e1743332523b2ab5614bae5e10f7a7799161f4</td><td>Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural +<br/>Networks +<br/><b>Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH, UK</b><br/><b>School of IoT Engineering, Jiangnan University, Wuxi 214122, China</b></td><td>('2976854', 'Zhen-Hua Feng', 'zhen-hua feng')<br/>('1748684', 'Josef Kittler', 'josef kittler')</td><td>{z.feng, j.kittler, m.a.rana}@surrey.ac.uk, patrikhuber@gmail.com, wu xiaojun@jiangnan.edu.cn +</td></tr><tr><td>40c8cffd5aac68f59324733416b6b2959cb668fd</td><td>Pooling Facial Segments to Face: The Shallow and Deep Ends <br/>Department of Electrical and Computer Engineering and the Center for Automation Research, <br/><b>UMIACS, University of Maryland, College Park, MD</b></td><td>('3152615', 'Upal Mahbub', 'upal mahbub')<br/>('40599829', 'Sayantan Sarkar', 'sayantan sarkar')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td>{umahbub, ssarkar2, rama}@umiacs.umd.edu +</td></tr><tr><td>40273657e6919455373455bd9a5355bb46a7d614</td><td>Anonymizing k-Facial Attributes via Adversarial Perturbations +<br/>1 IIIT Delhi, New Delhi, India +<br/>2 Ministry of Electronics and Information Technology, New Delhi, India +</td><td>('24380882', 'Saheb Chhabra', 'saheb chhabra')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')<br/>('50046315', 'Gaurav Gupta', 'gaurav gupta')</td><td>{sahebc, rsingh, mayank@iiitd.ac.in}, gauravg@gov.in </td></tr><tr><td>40b10e330a5511a6a45f42c8b86da222504c717f</td><td>Implementing the Viola-Jones <br/>Face Detection Algorithm <br/>Kongens Lyngby 2008 @@ -35663,7 +45489,11 @@ <br/><b>University of Birmingham</b><br/>August 2012 </td><td>('2801456', 'Hamimah Ujir', 'hamimah ujir')</td><td></td></tr><tr><td>40217a8c60e0a7d1735d4f631171aa6ed146e719</td><td>Part-Pair Representation for Part Localization <br/><b>Columbia University</b></td><td>('2454675', 'Jiongxin Liu', 'jiongxin liu')<br/>('3173493', 'Yinxiao Li', 'yinxiao li')<br/>('1767767', 'Peter N. Belhumeur', 'peter n. belhumeur')</td><td>{liujx09, yli, belhumeur}@cs.columbia.edu -</td></tr><tr><td>2e20ed644e7d6e04dd7ab70084f1bf28f93f75e9</td><td></td><td></td><td></td></tr><tr><td>2eb37a3f362cffdcf5882a94a20a1212dfed25d9</td><td>4 +</td></tr><tr><td>2e20ed644e7d6e04dd7ab70084f1bf28f93f75e9</td><td></td><td></td><td></td></tr><tr><td>2e8e6b835e5a8f55f3b0bdd7a1ff765a0b7e1b87</td><td>International Journal of Computer Vision manuscript No. +<br/>(will be inserted by the editor) +<br/>Pointly-Supervised Action Localization +<br/>Received: date / Accepted: date +</td><td>('2606260', 'Pascal Mettes', 'pascal mettes')</td><td></td></tr><tr><td>2eb37a3f362cffdcf5882a94a20a1212dfed25d9</td><td>4 <br/>Local Feature Based Face Recognition <br/>R.I.T., Rajaramnagar and S.G.G.S. COE &T, Nanded <br/>India @@ -35708,7 +45538,7 @@ <br/>Henry Schneiderman (Chair) <br/>Alexei (Alyosha) Efros <br/><b>Robotics Institute</b><br/><b>Carnegie Mellon University</b><br/>Pittsburgh, Pennsylvania 15213 -<br/><b>c(cid:13) Carnegie Mellon University</b></td><td>('2989714', 'Jiang Ni', 'jiang ni')<br/>('1709305', 'Martial Hebert', 'martial hebert')<br/>('38998440', 'David Kriegman', 'david kriegman')</td><td></td></tr><tr><td>2e091b311ac48c18aaedbb5117e94213f1dbb529</td><td>Collaborative Facial Landmark Localization +<br/><b>c(cid:13) Carnegie Mellon University</b></td><td>('2989714', 'Jiang Ni', 'jiang ni')<br/>('1709305', 'Martial Hebert', 'martial hebert')<br/>('38998440', 'David Kriegman', 'david kriegman')</td><td></td></tr><tr><td>2e5cfa97f3ecc10ae8f54c1862433285281e6a7c</td><td></td><td></td><td></td></tr><tr><td>2e091b311ac48c18aaedbb5117e94213f1dbb529</td><td>Collaborative Facial Landmark Localization <br/>for Transferring Annotations Across Datasets <br/><b>University of Wisconsin Madison</b><br/>http://www.cs.wisc.edu/~lizhang/projects/collab-face-landmarks/ </td><td>('1893050', 'Brandon M. Smith', 'brandon m. smith')<br/>('40396555', 'Li Zhang', 'li zhang')</td><td></td></tr><tr><td>2e1415a814ae9abace5550e4893e13bd988c7ba1</td><td>International Journal of Engineering Trends and Technology (IJETT) – Volume 21 Number 3 – March 2015 @@ -35725,6 +45555,10 @@ </td><td>('1856025', 'Carl Vondrick', 'carl vondrick')<br/>('2367683', 'Hamed Pirsiavash', 'hamed pirsiavash')<br/>('1690178', 'Antonio Torralba', 'antonio torralba')</td><td>vondrick@mit.edu <br/>hpirsiav@umbc.edu <br/>torralba@mit.edu +</td></tr><tr><td>2e0d56794379c436b2d1be63e71a215dd67eb2ca</td><td>Improving precision and recall of face recognition in SIPP with combination of +<br/>modified mean search and LSH +<br/>Xihua.Li +</td><td></td><td>lixihua9@126.com </td></tr><tr><td>2ee8900bbde5d3c81b7ed4725710ed46cc7e91cd</td><td></td><td></td><td></td></tr><tr><td>2e475f1d496456831599ce86d8bbbdada8ee57ed</td><td>Groupsourcing: Team Competition Designs for <br/>Crowdsourcing <br/><b>L3S Research Center, Hannover, Germany</b></td><td>('2993225', 'Markus Rokicki', 'markus rokicki')<br/>('2553718', 'Sergej Zerr', 'sergej zerr')<br/>('1745880', 'Stefan Siersdorfer', 'stefan siersdorfer')</td><td>{rokicki,siersdorfer,zerr}@L3S.de @@ -35733,6 +45567,8 @@ <br/>Recognition <br/>face.com </td><td>('2188620', 'Yaniv Taigman', 'yaniv taigman')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td>{yaniv, wolf}@face.com +</td></tr><tr><td>2e231f1e7e641dd3619bec59e14d02e91360ac01</td><td>FUSION NETWORK FOR FACE-BASED AGE ESTIMATION +<br/><b>The University of Warwick, Coventry, UK</b><br/><b>School of Management, University of Bath, Bath, UK</b><br/><b>School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, Australia</b></td><td>('1750506', 'Haoyi Wang', 'haoyi wang')<br/>('40655450', 'Xingjie Wei', 'xingjie wei')<br/>('1901920', 'Victor Sanchez', 'victor sanchez')<br/>('1799504', 'Chang-Tsun Li', 'chang-tsun li')</td><td>{h.wang.16, vsanchez, C-T.Li}@warwick.ac.uk, x.wei@bath.ac.uk </td></tr><tr><td>2e6cfeba49d327de21ae3186532e56cadeb57c02</td><td>Real Time Eye Gaze Tracking with 3D Deformable Eye-Face Model <br/><b>Rensselaer Polytechnic Institute</b><br/>110 8th Street, Troy, NY, USA </td><td>('1771700', 'Kang Wang', 'kang wang')<br/>('1726583', 'Qiang Ji', 'qiang ji')</td><td>{wangk10, jiq}@rpi.edu @@ -35751,7 +45587,23 @@ <br/>A Study Amongst Pre-Elementary School Kids <br/><b>Carnegie Mellon University</b><br/>5000 Forbes Avenue, <br/>Pittsburgh, PA 15213 -</td><td>('29120285', 'Vivek Pai', 'vivek pai')<br/>('1760345', 'Raja Sooriamurthi', 'raja sooriamurthi')</td><td></td></tr><tr><td>2e19371a2d797ab9929b99c80d80f01a1fbf9479</td><td></td><td></td><td></td></tr><tr><td>2ebc35d196cd975e1ccbc8e98694f20d7f52faf3</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. +</td><td>('29120285', 'Vivek Pai', 'vivek pai')<br/>('1760345', 'Raja Sooriamurthi', 'raja sooriamurthi')</td><td></td></tr><tr><td>2e19371a2d797ab9929b99c80d80f01a1fbf9479</td><td></td><td></td><td></td></tr><tr><td>2ed4973984b254be5cba3129371506275fe8a8eb</td><td> +<br/>THE EFFECTS OF MOOD ON +<br/>EMOTION RECOGNITION AND +<br/>ITS RELATIONSHIP WITH THE +<br/>GLOBAL VS LOCAL +<br/>INFORMATION PROCESSING +<br/>STYLES +<br/>BASIC RESEARCH PROGRAM +<br/>WORKING PAPERS +<br/>SERIES: PSYCHOLOGY +<br/>WP BRP 60/PSY/2016 +<br/>This Working Paper is an output of a research project implemented at the National Research +<br/><b>University Higher School of Economics (HSE). Any opinions or claims contained in this</b><br/>Working Paper do not necessarily reflect the views of HSE +<br/> +</td><td>('15615673', 'Victoria Ovsyannikova', 'victoria ovsyannikova')</td><td></td></tr><tr><td>2e9c780ee8145f29bd1a000585dd99b14d1f5894</td><td>Simultaneous Adversarial Training - Learn from +<br/>Others’ Mistakes +<br/><b>Lite-On Singapore Pte. Ltd, 2Imperial College London</b></td><td>('9949538', 'Zukang Liao', 'zukang liao')</td><td></td></tr><tr><td>2ebc35d196cd975e1ccbc8e98694f20d7f52faf3</td><td>This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. <br/>IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE <br/>Towards Wide-angle Micro Vision Sensors </td><td>('2724462', 'Sanjeev J. Koppal', 'sanjeev j. koppal')<br/>('2407724', 'Ioannis Gkioulekas', 'ioannis gkioulekas')<br/>('2140759', 'Kenneth B. Crozier', 'kenneth b. crozier')</td><td></td></tr><tr><td>2e3d081c8f0e10f138314c4d2c11064a981c1327</td><td></td><td></td><td></td></tr><tr><td>2e86402b354516d0a8392f75430156d629ca6281</td><td></td><td></td><td></td></tr><tr><td>2ea78e128bec30fb1a623c55ad5d55bb99190bd2</td><td>Residual vs. Inception vs. Classical Networks for @@ -35819,7 +45671,17 @@ <br/>from Captioned Images of Cluttered Scenes ∗ <br/><b>University of Toronto</b><br/><b>Bielefeld University</b></td><td>('37894231', 'Michael Jamieson', 'michael jamieson')<br/>('1724954', 'Sven Wachsmuth', 'sven wachsmuth')</td><td>{jamieson, afsaneh, sven, suzanne}@cs.toronto.edu <br/>swachsmu@techfak.uni-bielefeld.de -</td></tr><tr><td>2e1b1969ded4d63b69a5ec854350c0f74dc4de36</td><td></td><td></td><td></td></tr><tr><td>2be0ab87dc8f4005c37c523f712dd033c0685827</td><td>RELAXED LOCAL TERNARY PATTERN FOR FACE RECOGNITION +</td></tr><tr><td>2e1b1969ded4d63b69a5ec854350c0f74dc4de36</td><td></td><td></td><td></td></tr><tr><td>2e832d5657bf9e5678fd45b118fc74db07dac9da</td><td>Running head: RECOGNITION OF FACIAL EXPRESSIONS OF EMOTION +<br/>1 +<br/>Recognition of Facial Expressions of Emotion: The Effects of Anxiety, Depression, and Fear of Negative +<br/>Evaluation +<br/>Rachel Merchak +<br/><b>Wittenberg University</b><br/><b>Rachel Merchak, Wittenberg University</b><br/>Author Note +<br/>This research was conducted in collaboration with Dr. Stephanie Little, Psychology Department, +<br/><b>Wittenberg University, and Dr. Michael Anes, Wittenberg University</b><br/>Correspondence concerning this article should be addressed to Rachel Merchak, 10063 Fox +<br/>Chase Drive, Loveland, OH 45140. +</td><td></td><td>E‐mail: merchakr@wittenberg.edu +</td></tr><tr><td>2be0ab87dc8f4005c37c523f712dd033c0685827</td><td>RELAXED LOCAL TERNARY PATTERN FOR FACE RECOGNITION <br/>BeingThere Centre <br/><b>Institute of Media Innovation</b><br/><b>Nanyang Technological University</b><br/>50 Nanyang Drive, Singapore 637553. <br/>School of Electrical & Electronics Engineering @@ -35873,7 +45735,8 @@ <br/>[7] and fusion of geometric and appearance features [8], [9], [10]. Nowadays, deep <br/>1249 </td><td>('9318822', 'MAHESH GOYANI', 'mahesh goyani')<br/>('11384332', 'NARENDRA PATEL', 'narendra patel')</td><td>E-mail: mgoyani@gmail.com, nmpatel@bvmengineerring.ac.in -</td></tr><tr><td>2b0ff4b82bac85c4f980c40b3dc4fde05d3cc23f</td><td>An Effective Approach for Facial Expression Recognition with Local Binary +</td></tr><tr><td>2bb53e66aa9417b6560e588b6235e7b8ebbc294c</td><td>SEMANTIC EMBEDDING SPACE FOR ZERO-SHOT ACTION RECOGNITION +<br/><b>School of EECS, Queen Mary University of London, London, UK</b></td><td>('47158489', 'Xun Xu', 'xun xu')<br/>('2073354', 'Shaogang Gong', 'shaogang gong')</td><td></td></tr><tr><td>2b0ff4b82bac85c4f980c40b3dc4fde05d3cc23f</td><td>An Effective Approach for Facial Expression Recognition with Local Binary <br/>Pattern and Support Vector Machine </td><td>('20656805', 'Thi Nhan', 'thi nhan')<br/>('9872793', 'Il Choi', 'il choi')</td><td>*1School of Media, Soongsil University, ctnhen@yahoo.com <br/>2School of Media, Soongsil University, an_tth@yahoo.com @@ -36078,6 +45941,9 @@ <br/>d1+d2≤d </td><td></td><td>e-mail: firstname.lastname@technicolor.com <br/>e-mail: firstname.lastname@univ-poitiers.fr +</td></tr><tr><td>2b869d5551b10f13bf6fcdb8d13f0aa4d1f59fc4</td><td>Ring loss: Convex Feature Normalization for Face Recognition +<br/>Department of Electrical and Computer Engineering +<br/><b>Carnegie Mellon University</b></td><td>('3049981', 'Yutong Zheng', 'yutong zheng')<br/>('2628116', 'Dipan K. Pal', 'dipan k. pal')<br/>('1794486', 'Marios Savvides', 'marios savvides')</td><td>{yutongzh, dipanp, marioss}@andrew.cmu.edu </td></tr><tr><td>2bae810500388dd595f4ebe992c36e1443b048d2</td><td>International Journal of Bioelectromagnetism <br/>Vol. 18, No. 1, pp. 13 - 18, 2016 <br/>www.ijbem.org @@ -36112,7 +45978,14 @@ <br/>Department of Electrical Engineering and Computer Science <br/><b>York University</b><br/>Toronto, Ontario <br/>Canada -</td><td>('1709096', 'Richard P. Wildes', 'richard p. wildes')</td><td></td></tr><tr><td>4793f11fbca4a7dba898b9fff68f70d868e2497c</td><td>Kinship Verification through Transfer Learning +</td><td>('1709096', 'Richard P. Wildes', 'richard p. wildes')</td><td></td></tr><tr><td>477236563c6a6c6db922045453b74d3f9535bfa1</td><td>International Journal of Science and Research (IJSR) +<br/>ISSN (Online): 2319-7064 +<br/>Index Copernicus Value (2013): 6.14 | Impact Factor (2014): 5.611 +<br/>Attribute Based Image Search Re-Ranking +<br/>Snehal S Patil1, Ajay Dani2 +<br/><b>Master of Computer Engg, Savitribai Phule Pune University, G. H. Raisoni Collage of Engg and Technology, Wagholi, Pune</b><br/><b>G. H .Raisoni Collage of Engg and Technology, Wagholi, Pune</b><br/>integrating +<br/>images by +</td><td></td><td></td></tr><tr><td>4793f11fbca4a7dba898b9fff68f70d868e2497c</td><td>Kinship Verification through Transfer Learning <br/>Siyu Xia∗ <br/>CSE, SUNY at Buffalo, USA <br/><b>and Southeast University, China</b><br/>CSE @@ -36238,7 +46111,11 @@ <br/>Real-Time Facial Expression Recognition App Development on <br/>Smart Phones <br/><b>Florida Institute Of Technology, Melbourne Fl</b><br/>USA -</td><td>('7155812', 'Humaid Alshamsi', 'humaid alshamsi')<br/>('7155812', 'Humaid Alshamsi', 'humaid alshamsi')</td><td></td></tr><tr><td>47e3029a3d4cf0a9b0e96252c3dc1f646e750b14</td><td>International Conference on Computer Systems and Technologies - CompSysTech’07 +</td><td>('7155812', 'Humaid Alshamsi', 'humaid alshamsi')<br/>('7155812', 'Humaid Alshamsi', 'humaid alshamsi')</td><td></td></tr><tr><td>47190d213caef85e8b9dd0d271dbadc29ed0a953</td><td>The Devil of Face Recognition is in the Noise +<br/>1 SenseTime Research +<br/><b>University of California San Diego</b><br/><b>Nanyang Technological University</b></td><td>('1682816', 'Fei Wang', 'fei wang')<br/>('3203648', 'Liren Chen', 'liren chen')<br/>('46651787', 'Cheng Li', 'cheng li')<br/>('1937119', 'Shiyao Huang', 'shiyao huang')<br/>('47557603', 'Yanjie Chen', 'yanjie chen')<br/>('49215552', 'Chen Qian', 'chen qian')<br/>('1717179', 'Chen Change Loy', 'chen change loy')</td><td>{wangfei, chengli, huangshiyao, chenyanjie, qianchen}@sensetime.com, +<br/>lic002@eng.ucsd.edu, ccloy@ieee.org +</td></tr><tr><td>47e3029a3d4cf0a9b0e96252c3dc1f646e750b14</td><td>International Conference on Computer Systems and Technologies - CompSysTech’07 <br/>Facial Expression Recognition in still pictures and videos using Active <br/>Appearance Models. A comparison approach. <br/>Drago(cid:1) Datcu @@ -36276,7 +46153,7 @@ <br/>Recognition Using PCA <br/>(M.Tech. Student) <br/>Computer Science & Engineering -<br/><b>Iftm University, Moradabad-244001 U.P</b></td><td>('9247488', 'Tara Prasad Singh', 'tara prasad singh')</td><td></td></tr><tr><td>477811ff147f99b21e3c28309abff1304106dbbe</td><td></td><td></td><td></td></tr><tr><td>473cbc5ec2609175041e1410bc6602b187d03b23</td><td>Semantic Audio-Visual Data Fusion for Automatic Emotion Recognition +<br/><b>Iftm University, Moradabad-244001 U.P</b></td><td>('9247488', 'Tara Prasad Singh', 'tara prasad singh')</td><td></td></tr><tr><td>477811ff147f99b21e3c28309abff1304106dbbe</td><td></td><td></td><td></td></tr><tr><td>47e14fdc6685f0b3800f709c32e005068dfc8d47</td><td></td><td></td><td></td></tr><tr><td>473cbc5ec2609175041e1410bc6602b187d03b23</td><td>Semantic Audio-Visual Data Fusion for Automatic Emotion Recognition <br/>Man-Machine Interaction Group <br/><b>Delft University of Technology</b><br/>2628 CD, Delft, <br/>The Netherlands @@ -36286,7 +46163,7 @@ <br/>point extraction, Active Appearance Models, Support Vector <br/>Machines. </td><td>('2866326', 'Dragos Datcu', 'dragos datcu')</td><td>E-mail: {D.Datcu ; L.J.M.Rothkrantz}@tudelft.nl -</td></tr><tr><td>78a4cabf0afc94da123e299df5b32550cd638939</td><td></td><td></td><td></td></tr><tr><td>78f08cc9f845dc112f892a67e279a8366663e26d</td><td>TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN +</td></tr><tr><td>782188821963304fb78791e01665590f0cd869e8</td><td></td><td></td><td></td></tr><tr><td>78a4cabf0afc94da123e299df5b32550cd638939</td><td></td><td></td><td></td></tr><tr><td>78f08cc9f845dc112f892a67e279a8366663e26d</td><td>TECHNISCHE UNIVERSIT ¨AT M ¨UNCHEN <br/>Lehrstuhl f¨ur Mensch-Maschine-Kommunikation <br/>Semi-Autonomous Data Enrichment and <br/>Optimisation for Intelligent Speech Analysis @@ -36383,7 +46260,7 @@ <br/><b>Tel Aviv University</b><br/>Tel Aviv, Israel </td><td>('2188620', 'Yaniv Taigman', 'yaniv taigman')<br/>('32447229', 'Ming Yang', 'ming yang')<br/>('1776343', 'Lior Wolf', 'lior wolf')</td><td>{yaniv, mingyang, ranzato}@fb.com <br/>wolf@cs.tau.ac.il -</td></tr><tr><td>78436256ff8f2e448b28e854ebec5e8d8306cf21</td><td>Measuring and Understanding Sensory Representations within +</td></tr><tr><td>78c1ad33772237bf138084220d1ffab800e1200d</td><td><b>State Key Laboratory of Software Development Environment, Beihang University, P.R.China</b><br/><b>University of Michigan, Ann Arbor</b></td><td>('48545182', 'Lei Huang', 'lei huang')<br/>('8342699', 'Jia Deng', 'jia deng')</td><td></td></tr><tr><td>78436256ff8f2e448b28e854ebec5e8d8306cf21</td><td>Measuring and Understanding Sensory Representations within <br/>Deep Networks Using a Numerical Optimization Framework <br/><b>Harvard University, Cambridge, MA</b><br/>USA <br/><b>Center for Brain Science, Harvard University, Cambridge, MA, USA</b><br/><b>Harvard University, Cambridge, MA, USA</b></td><td>('1739108', 'Chuan-Yung Tsai', 'chuan-yung tsai')<br/>('2042941', 'David D. Cox', 'david d. cox')</td><td>∗ E-mail: davidcox@fas.harvard.edu @@ -36401,6 +46278,22 @@ <br/> published February 28, 2015 </td><td>('37284667', 'Ju-Chin Chen', 'ju-chin chen')<br/>('36612683', 'Pei-Hsun Wu', 'pei-hsun wu')<br/>('3461535', 'Jenn-Jier James Lien', 'jenn-jier james lien')<br/>('37284667', 'Ju-Chin Chen', 'ju-chin chen')</td><td>[e-mail: jc.chen@cc.kuas.edu.tw] <br/>[e-mail: jjlien@csie.ncku.edu.tw] +</td></tr><tr><td>78598e7005f7c96d64cc47ff47e6f13ae52245b8</td><td>Hand2Face: Automatic Synthesis and Recognition of Hand Over Face Occlusions +<br/>Synthetic Reality Lab +<br/>Department of Computer Science +<br/><b>University of Central Florida</b><br/>Orlando, Florida +<br/>Synthetic Reality Lab +<br/>Department of Computer Science +<br/><b>University of Central Florida</b><br/>Orlando, Florida +<br/>Tadas Baltruˇsaitis +<br/><b>Language Technology Institute</b><br/>School of Computer Science +<br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA +<br/><b>Language Technology Institute</b><br/>School of Computer Science +<br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA +</td><td>('2974242', 'Behnaz Nojavanasghari', 'behnaz nojavanasghari')<br/>('32827434', 'Charles E. Hughes', 'charles e. hughes')<br/>('1767184', 'Louis-Philippe Morency', 'louis-philippe morency')</td><td>Email: behnaz@eecs.ucf.edu +<br/>Email: ceh@cs.ucf.edu +<br/>Email: tbaltrus@cs.cmu.edu +<br/>Email: morency@cs.cmu.edu </td></tr><tr><td>7862f646d640cbf9f88e5ba94a7d642e2a552ec9</td><td>Being John Malkovich <br/><b>University of Washington</b><br/>2 Adobe Systems <br/>3 Google Inc. @@ -36415,7 +46308,10 @@ <br/>Cees G. M. Snoek1 <br/>Received: 25 June 2016 / Accepted: 18 May 2017 <br/>© The Author(s) 2017. This article is an open access publication -</td><td>('40027484', 'Mihir Jain', 'mihir jain')<br/>('1681054', 'Hervé Jégou', 'hervé jégou')</td><td></td></tr><tr><td>78df7d3fdd5c32f037fb5cc2a7c104ac1743d74e</td><td>TEMPORAL PYRAMID POOLING CNN FOR ACTION RECOGNITION +</td><td>('40027484', 'Mihir Jain', 'mihir jain')<br/>('1681054', 'Hervé Jégou', 'hervé jégou')</td><td></td></tr><tr><td>78174c2be084e67f48f3e8ea5cb6c9968615a42c</td><td>Periocular Recognition Using CNN Features +<br/>Off-the-Shelf +<br/><b>School of Information Technology (ITE), Halmstad University, Box 823, 30118 Halmstad, Sweden</b></td><td>('51446244', 'Kevin Hernandez-Diaz', 'kevin hernandez-diaz')<br/>('2847751', 'Fernando Alonso-Fernandez', 'fernando alonso-fernandez')<br/>('5058247', 'Josef Bigun', 'josef bigun')</td><td>Email: kevin.hernandez-diaz@hh.se, feralo@hh.se, josef.bigun@hh.se +</td></tr><tr><td>78df7d3fdd5c32f037fb5cc2a7c104ac1743d74e</td><td>TEMPORAL PYRAMID POOLING CNN FOR ACTION RECOGNITION <br/>Temporal Pyramid Pooling Based Convolutional <br/>Neural Network for Action Recognition </td><td>('40378631', 'Peng Wang', 'peng wang')<br/>('2572430', 'Yuanzhouhan Cao', 'yuanzhouhan cao')<br/>('40529029', 'Chunhua Shen', 'chunhua shen')<br/>('2161037', 'Lingqiao Liu', 'lingqiao liu')<br/>('1724393', 'Heng Tao Shen', 'heng tao shen')</td><td></td></tr><tr><td>780557daaa39a445b24c41f637d5fc9b216a0621</td><td>Large Video Event Ontology Browsing, Search and @@ -36436,6 +46332,19 @@ </td><td>('25087736', 'Mahek Shah', 'mahek shah')</td><td></td></tr><tr><td>7808937b46acad36e43c30ae4e9f3fd57462853d</td><td>Describing People: A Poselet-Based Approach to Attribute Classification ∗ <br/>1EECS, U.C. Berkeley, Berkeley, CA 94720 <br/><b>Adobe Systems, Inc., 345 Park Ave, San Jose, CA</b></td><td>('35208858', 'Subhransu Maji', 'subhransu maji')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td>{lbourdev,smaji,malik}@eecs.berkeley.edu +</td></tr><tr><td>8b2c090d9007e147b8c660f9282f357336358061</td><td><b>Lake Forest College</b><br/><b>Lake Forest College Publications</b><br/>Senior Theses +<br/>4-23-2018 +<br/>Student Publications +<br/>Emotion Classification based on Expressions and +<br/>Body Language using Convolutional Neural +<br/>Networks +<br/>Follow this and additional works at: https://publications.lakeforest.edu/seniortheses +<br/>Part of the Neuroscience and Neurobiology Commons +<br/>Recommended Citation +<br/>Tanveer, Aasimah S., "Emotion Classification based on Expressions and Body Language using Convolutional Neural Networks" +<br/>(2018). Senior Theses. +<br/><b>This Thesis is brought to you for free and open access by the Student Publications at Lake Forest College Publications. It has been accepted for</b><br/><b>inclusion in Senior Theses by an authorized administrator of Lake Forest College Publications. For more information, please contact</b></td><td></td><td>Lake Forest College, tanveeras@lakeforest.edu +<br/>levinson@lakeforest.edu. </td></tr><tr><td>8ba67f45fbb1ce47a90df38f21834db37c840079</td><td>People Search and Activity Mining in Large-Scale <br/>Community-Contributed Photos <br/><b>National Taiwan University, Taipei, Taiwan</b><br/>Winston H. Hsu, Hong-Yuan Mark Liao @@ -36447,6 +46356,26 @@ <br/>hemanta.sapkota@student.uts.edu.au <br/>daniel.j.rosser@gmail.com <br/>yusuf.pisan@gamesstudio.org +</td></tr><tr><td>8bed7ff2f75d956652320270eaf331e1f73efb35</td><td>Emotion Recognition in the Wild using +<br/>Deep Neural Networks and Bayesian Classifiers +<br/>Elena Ba(cid:138)ini S¨onmez +<br/><b>University of Calabria - DeMACS</b><br/>Via Pietro Bucci +<br/>Rende (CS), Italy +<br/><b>Plymouth University - CRNS</b><br/>Portland Square PL4 8AA +<br/>Plymouth, United Kingdom +<br/>ac.uk +<br/><b>Istanbul Bilgi University - DCE</b><br/>Eski Silahtaraa Elektrik Santral Kazm +<br/>Karabekir Cad. No: 2/13 34060 Eyp +<br/>Istanbul, Turkey +<br/><b>University of Calabria - DeMACS</b><br/>Via Pietro Bucci +<br/>Rende (CS), Italy +<br/><b>Plymouth University - CRNS</b><br/>Portland Square PL4 8AA +<br/>Plymouth, United Kingdom +</td><td>('32751441', 'Luca Surace', 'luca surace')<br/>('3366919', 'Massimiliano Patacchiola', 'massimiliano patacchiola')<br/>('3205804', 'William Spataro', 'william spataro')<br/>('1692929', 'Angelo Cangelosi', 'angelo cangelosi')</td><td>lucasurace11@gmail.com +<br/>massimiliano.patacchiola@plymouth. +<br/>ebsonmez@bilgi.edu.tr +<br/>william.spataro@unical.it +<br/>angelo.cangelosi@plymouth.ac.uk </td></tr><tr><td>8b7191a2b8ab3ba97423b979da6ffc39cb53f46b</td><td>Search Pruning in Video Surveillance Systems: Efficiency-Reliability Tradeoff <br/>EURECOM <br/>Sophia Antipolis, France @@ -36464,10 +46393,25 @@ </td><td>('17872416', 'Qiantong Xu', 'qiantong xu')<br/>('13318784', 'Ke Yan', 'ke yan')<br/>('1705972', 'Yonghong Tian', 'yonghong tian')</td><td>{xuqiantong, keyan, yhtian}@pku.edu.cn </td></tr><tr><td>8bfada57140aa1aa22a575e960c2a71140083293</td><td>Can we match Ultraviolet Face Images against their Visible <br/>Counterparts? -<br/><b>aMILab, LCSEE, West Virginia University, Morgantown, West Virginia, USA</b></td><td>('33240042', 'Neeru Narang', 'neeru narang')<br/>('1731727', 'Thirimachos Bourlai', 'thirimachos bourlai')<br/>('1678573', 'Lawrence A. Hornak', 'lawrence a. hornak')<br/>('11898042', 'Paul D. Coverdell', 'paul d. coverdell')</td><td></td></tr><tr><td>8b8728edc536020bc4871dc66b26a191f6658f7c</td><td></td><td></td><td></td></tr><tr><td>8bbbdff11e88327816cad3c565f4ab1bb3ee20db</td><td>Automatic Semantic Face Recognition +<br/><b>aMILab, LCSEE, West Virginia University, Morgantown, West Virginia, USA</b></td><td>('33240042', 'Neeru Narang', 'neeru narang')<br/>('1731727', 'Thirimachos Bourlai', 'thirimachos bourlai')<br/>('1678573', 'Lawrence A. Hornak', 'lawrence a. hornak')<br/>('11898042', 'Paul D. Coverdell', 'paul d. coverdell')</td><td></td></tr><tr><td>8b8728edc536020bc4871dc66b26a191f6658f7c</td><td></td><td></td><td></td></tr><tr><td>8befcd91c24038e5c26df0238d26e2311b21719a</td><td>A Joint Sequence Fusion Model for Video +<br/>Question Answering and Retrieval +<br/>Department of Computer Science and Engineering, +<br/><b>Seoul National University, Seoul, Korea</b><br/>http://vision.snu.ac.kr/projects/jsfusion/ +</td><td>('7877122', 'Youngjae Yu', 'youngjae yu')<br/>('2175130', 'Jongseok Kim', 'jongseok kim')</td><td>{yj.yu,js.kim}@vision.snu.ac.kr, gunhee@snu.ac.kr +</td></tr><tr><td>8bbbdff11e88327816cad3c565f4ab1bb3ee20db</td><td>Automatic Semantic Face Recognition <br/><b>University of Southampton</b><br/>Southampton, United Kingdom </td><td>('19249411', 'Nawaf Yousef Almudhahka', 'nawaf yousef almudhahka')<br/>('1727698', 'Mark S. Nixon', 'mark s. nixon')<br/>('31534955', 'Jonathon S. Hare', 'jonathon s. hare')</td><td>{nya1g14,msn,jsh2}@ecs.soton.ac.uk -</td></tr><tr><td>8b10383ef569ea0029a2c4a60cc2d8c87391b4db</td><td>ZHOU,MILLERANDZHANG:AGECLASSIFICATIONUSINGRADONTRANSFORM... +</td></tr><tr><td>8bdf6f03bde08c424c214188b35be8b2dec7cdea</td><td>Exploiting Unintended Feature Leakage in Collaborative Learning∗ +<br/>UCL +<br/><b>Cornell University</b><br/><b>UCL and Alan Turing Institute</b><br/>Cornell Tech +</td><td>('2008164', 'Luca Melis', 'luca melis')<br/>('3469125', 'Congzheng Song', 'congzheng song')<br/>('1728207', 'Emiliano De Cristofaro', 'emiliano de cristofaro')<br/>('1723945', 'Vitaly Shmatikov', 'vitaly shmatikov')</td><td>luca.melis.14@alumni.ucl.ac.uk +<br/>cs2296@cornell.edu +<br/>e.decristofaro@ucl.ac.uk +<br/>shmat@cs.cornell.edu +</td></tr><tr><td>8b744786137cf6be766778344d9f13abf4ec0683</td><td>978-1-4799-9988-0/16/$31.00 ©2016 IEEE +<br/>2697 +<br/>ICASSP 2016 +</td><td></td><td></td></tr><tr><td>8b10383ef569ea0029a2c4a60cc2d8c87391b4db</td><td>ZHOU,MILLERANDZHANG:AGECLASSIFICATIONUSINGRADONTRANSFORM... <br/>Age classification using Radon transform <br/>and entropy based scaling SVM <br/>Paul Miller1 @@ -36483,6 +46427,17 @@ <br/><b>Nanjing University, China</b><br/>2 Minieye, Youjia Innovation LLC, China </td><td>('1808816', 'Jianxin Wu', 'jianxin wu')<br/>('2226422', 'Bin-Bin Gao', 'bin-bin gao')<br/>('15527784', 'Guoqing Liu', 'guoqing liu')</td><td>∗ wujx2001@nju.edu.cn, gaobb@lamda.nju.edu.cn <br/>guoqing@minieye.cc +</td></tr><tr><td>8b61fdc47b5eeae6bc0a52523f519eaeaadbc8c8</td><td>HU, LIU, LI, LIU: TEMPORAL PERCEPTIVE NETWORK FOR ACTION RECOGNITION +<br/>Temporal Perceptive Network for +<br/>Skeleton-Based Action Recognition +<br/><b>Institute of Computer Science and</b><br/>Technology +<br/><b>Peking University</b><br/>Beijing, China +<br/>Sijie Song +</td><td>('9956463', 'Yueyu Hu', 'yueyu hu')<br/>('49046516', 'Chunhui Liu', 'chunhui liu')<br/>('3128506', 'Yanghao Li', 'yanghao li')<br/>('41127426', 'Jiaying Liu', 'jiaying liu')</td><td>huyy@pku.edu.cn +<br/>liuchunhui@pku.edu.cn +<br/>lyttonhao@pku.edu.cn +<br/>ssj940920@pku.edu.cn +<br/>liujiaying@pku.edu.cn </td></tr><tr><td>8b19efa16a9e73125ab973429eb769d0ad5a8208</td><td>SCAR: Dynamic adaptation for person detection and <br/>persistence analysis in unconstrained videos <br/>Department of Computer Science @@ -36605,6 +46560,16 @@ </td><td>('2309364', 'Oscar Koller', 'oscar koller')<br/>('1695195', 'Richard Bowden', 'richard bowden')</td><td>{n.camgoz, s.hadfield}@surrey.ac.uk <br/>koller@cs.rwth-aachen.de <br/>r.bowden@surrey.ac.uk +</td></tr><tr><td>8b38124ff02a9cf8ad00de5521a7f8a9fa4d7259</td><td>Real-time 3D Face Fitting and Texture Fusion +<br/>on In-the-wild Videos +<br/>Centre for Vision, Speech and Signal Processing +<br/>Image Understanding and Interactive Robotics +<br/><b>University of Surrey</b><br/>Guildford, GU2 7XH, United Kingdom +<br/>Contact: http://www.patrikhuber.ch +<br/><b>Reutlingen University</b><br/>D-72762 Reutlingen, Germany +</td><td>('39976184', 'Patrik Huber', 'patrik huber')<br/>('49759031', 'William Christmas', 'william christmas')<br/>('1748684', 'Josef Kittler', 'josef kittler')<br/>('49330989', 'Philipp Kopp', 'philipp kopp')</td><td></td></tr><tr><td>134f1cee8408cca648d8b4ca44b38b0a7023af71</td><td>Partially Shared Multi-Task Convolutional Neural Network with Local +<br/>Constraint for Face Attribute Learning +<br/><b>College of Information Science and Electronic Engineering</b><br/><b>Zhejiang University, China</b></td><td>('41021477', 'Jiajiong Cao', 'jiajiong cao')<br/>('2367491', 'Yingming Li', 'yingming li')<br/>('1720488', 'Zhongfei Zhang', 'zhongfei zhang')</td><td>{jiajiong, yingming, zhongfei}@zju.edu.cn </td></tr><tr><td>13719bbb4bb8bbe0cbcdad009243a926d93be433</td><td>Deep LDA-Pruned Nets for Efficient Facial Gender Classification <br/><b>McGill University</b><br/><b>University Street, Montral, QC H3A 0E9, Canada</b></td><td>('1992537', 'Qing Tian', 'qing tian')<br/>('1699104', 'Tal Arbel', 'tal arbel')<br/>('1713608', 'James J. Clark', 'james j. clark')</td><td>{qtian,arbel,clark}@cim.mcgill.ca </td></tr><tr><td>134db6ca13f808a848321d3998e4fe4cdc52fbc2</td><td>IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 36, NO. 2, APRIL 2006 @@ -36688,7 +46653,13 @@ <br/>Processing,” Perth, Australia, November 1999. Acknowledgement also due to Mr. Der-Chen Pan at the Na- <br/><b>tional Taipei University for his help in performing simulations. The author would like to thank Mr. Ming</b><br/>Shon Chen at Ulead System Inc., Taipei, Taiwan, for his early work and assistance in this research. <br/>1033 -</td><td>('39548632', 'Daw-Tung Lin', 'daw-tung lin')</td><td></td></tr><tr><td>1394ca71fc52db972366602a6643dc3e65ee8726</td><td>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/308407783 +</td><td>('39548632', 'Daw-Tung Lin', 'daw-tung lin')</td><td></td></tr><tr><td>13604bbdb6f04a71dea4bd093794e46730b0a488</td><td>Robust Loss Functions under Label Noise for +<br/>Deep Neural Networks +<br/>Microsoft, Bangalore +<br/><b>Indian Institute of Science, Bangalore</b><br/><b>Indian Institute of Science, Bangalore</b></td><td>('3201314', 'Aritra Ghosh', 'aritra ghosh')<br/>('47602083', 'Himanshu Kumar', 'himanshu kumar')<br/>('1711348', 'P. S. Sastry', 'p. s. sastry')</td><td>arghosh@microsoft.com +<br/>himanshukr@ee.iisc.ernet.in +<br/>sastry@ee.iisc.ernet.in +</td></tr><tr><td>1394ca71fc52db972366602a6643dc3e65ee8726</td><td>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/308407783 <br/>EmoReact: A Multimodal Approach and Dataset <br/>for Recognizing Emotional Responses in Children <br/>Conference Paper · November 2016 @@ -36802,7 +46773,10 @@ <br/>Peer reviewed|Thesis/dissertation <br/>eScholarship.org <br/>Powered by the California Digital Library -<br/><b>University of California</b></td><td></td><td></td></tr><tr><td>13f6ab2f245b4a871720b95045c41a4204626814</td><td>RESEARCH ARTICLE +<br/><b>University of California</b></td><td></td><td></td></tr><tr><td>13aef395f426ca8bd93640c9c3f848398b189874</td><td>Image Preprocessing and Complete 2DPCA with Feature +<br/>Extraction for Gender Recognition +<br/>NSF REU 2017: Statistical Learning and Data Mining +<br/><b>University of North Carolina Wilmington</b></td><td></td><td></td></tr><tr><td>13f6ab2f245b4a871720b95045c41a4204626814</td><td>RESEARCH ARTICLE <br/>Cortex commands the performance of <br/>skilled movement <br/><b>Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United</b><br/>States @@ -36822,7 +46796,11 @@ <br/>Learning to Locate Informative Features for Visual Identification <br/>Received: 18 August 2005 / Accepted: 11 September 2007 / Published online: 9 November 2007 <br/>© Springer Science+Business Media, LLC 2007 -</td><td>('3236352', 'Andras Ferencz', 'andras ferencz')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td></td></tr><tr><td>7f57e9939560562727344c1c987416285ef76cda</td><td>Accessorize to a Crime: Real and Stealthy Attacks on +</td><td>('3236352', 'Andras Ferencz', 'andras ferencz')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td></td></tr><tr><td>1316296fae6485c1510f00b1b57fb171b9320ac2</td><td>FaceID-GAN: Learning a Symmetry Three-Player GAN +<br/>for Identity-Preserving Face Synthesis +<br/><b>CUHK - SenseTime Joint Lab, The Chinese University of Hong Kong</b><br/>2SenseTime Research +<br/><b>Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences</b></td><td>('8035201', 'Yujun Shen', 'yujun shen')<br/>('47571885', 'Ping Luo', 'ping luo')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>{sy116, pluo, xtang}@ie.cuhk.edu.hk, yanjunjie@sensetime.com, xgwang@ee.cuhk.edu.hk +</td></tr><tr><td>7f57e9939560562727344c1c987416285ef76cda</td><td>Accessorize to a Crime: Real and Stealthy Attacks on <br/>State-of-the-Art Face Recognition <br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA, USA <br/><b>Carnegie Mellon University</b><br/>Pittsburgh, PA, USA @@ -36837,7 +46815,96 @@ <br/>A Generalized Perspective <br/><b>Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China</b><br/><b>University of Chinese Academy of Sciences, Beijing, 100049, China</b><br/>3Key Laboratory of Optical-Electronics Information Processing <br/>November 20, 2017 -</td><td>('1803285', 'Tianci Liu', 'tianci liu')<br/>('2172914', 'Zelin Shi', 'zelin shi')<br/>('2556853', 'Yunpeng Liu', 'yunpeng liu')</td><td></td></tr><tr><td>7fce5769a7d9c69248178989a99d1231daa4fce9</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, +</td><td>('1803285', 'Tianci Liu', 'tianci liu')<br/>('2172914', 'Zelin Shi', 'zelin shi')<br/>('2556853', 'Yunpeng Liu', 'yunpeng liu')</td><td></td></tr><tr><td>7f511a6a2b38a26f077a5aec4baf5dffc981d881</td><td>LOW-LATENCY HUMAN ACTION RECOGNITION WITH WEIGHTED MULTI-REGION +<br/>CONVOLUTIONAL NEURAL NETWORK +<br/><b>cid:63)University of Science and Technology of China, Hefei, Anhui, China</b><br/>†HERE Technologies, Chicago, Illinois, USA +</td><td>('49417387', 'Yunfeng Wang', 'yunfeng wang')<br/>('38272296', 'Wengang Zhou', 'wengang zhou')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('49897466', 'Xiaotian Zhu', 'xiaotian zhu')<br/>('7179232', 'Houqiang Li', 'houqiang li')</td><td></td></tr><tr><td>7f21a7441c6ded38008c1fd0b91bdd54425d3f80</td><td>Real Time System for Facial Analysis +<br/><b>Tampere University of Technology, Finland</b><br/>I. +<br/>INTRODUCTION +<br/>Most signal or image processing algorithms should be +<br/>designed with real-time execution in mind. Most use cases +<br/>compute on an embedded platform while receiving streaming +<br/>data as a constant data flow. In machine learning, however, the +<br/>real time deployment and streaming data processing are less +<br/>often a design criterion. Instead, the bulk of machine learning is +<br/>executed offline on the cloud without any real time restrictions. +<br/>However, the real time use is rapidly becoming more important +<br/>as deep learning systems are appearing into, for example, +<br/>autonomous vehicles and working machines. +<br/>In this work, we describe the functionality of our demo +<br/>system integrating a number of common real time machine +<br/>learning systems together. The demo system consists of a +<br/>screen, webcam and a computer, and it estimates the age, +<br/>gender and facial expression of all faces seen by the webcam. +<br/>A picture of the system in use is shown in Figure 1. There is +<br/>also a Youtube video at https://youtu.be/Kfe5hKNwrCU and +<br/>the code is freely available at https://github.com/mahehu/TUT- +<br/>live-age-estimator. +<br/>Apart from serving as an illustrative example of modern +<br/>human level machine learning for the general public, the +<br/>system also highlights several aspects that are common in real +<br/>time machine learning systems. First, the subtasks needed to +<br/>achieve the three recognition results represent a wide variety of +<br/>machine learning problems: (1) object detection is used to find +<br/>the faces, (2) age estimation represents a regression problem +<br/>with a real-valued target output (3) gender prediction is a +<br/>binary classification problem, and (4) facial expression +<br/>prediction is a multi-class classification problem. Moreover, all +<br/>these tasks should operate in unison, such that each task will +<br/>receive enough resources from a limited pool. +<br/>In the remainder of this paper, we first describe the system +<br/>level multithreaded architecture for real time processing in +<br/>Section II. This is followed by detailed discussion individual +<br/>components of the system in Section III. Next, we report +<br/>experimental results on the accuracy of each individual +<br/>recognition component in Section IV, and finally, discuss the +<br/>benefits of demonstrating the potential of modern machine +<br/>learning to both general public and experts in the field. +<br/>II. SYSTEM LEVEL FUNCTIONALITY +<br/>The challenge in real-time operation is that there are +<br/>numerous components in the system, and each uses different +<br/>amount of execution time. The system should be designed +<br/>such that the operation appears smooth, which means that the +<br/>most visible tasks should be fast and have the priority in +<br/>scheduling. +<br/>Figure 1. Demo system recognizes the age, gender and facial +<br/>expression in real time. +<br/>The system is running in threads, as illustrated in Figure 2. +<br/>The whole system is controlled by the upper level controller +<br/>and visualization thread, which owns and starts the sub- +<br/>threads dedicated for individual tasks. The main thread holds +<br/>all data and executes the visualization loop showing the +<br/>recognition results to the user at 25 frames per second. +<br/>The recognition process starts from the grabber thread, +<br/>which is connected to a webcam. The thread requests video +<br/>frames from camera for feeding them into a FIFO buffer +<br/>located inside the controller thread. At grab time, each frame is +<br/>wrapped inside a class object, which holds the necessary meta +<br/>data related to each frame. More specifically, each frame is +<br/>linked with a timestamp and a flag indicating whether the face +<br/>detection has already been executed and +<br/>locations +<br/>(bounding boxes) of all found faces in the scene. +<br/>the +<br/>The actual face analysis consists of two parts: face +<br/>detection and face analysis. The detection is executed in the +<br/>detection thread, which operates asynchronously, requesting +<br/>new non-processed frames from the controller thread. After +<br/>face detection, the locations of found faces are sent to the +<br/>controller thread, which then matches each new face with all +<br/>face objects from the previous frames using straightforward +<br/>centroid tracking. Tracking allows us to average the estimates +<br/>for each face over a number of recent frames. +<br/>The detection thread operates on the average faster than the +<br/>frame rate, but sometimes there are delays due to high load on +<br/>the other threads. Therefore, the controller thread holds a +<br/>buffer of the most recent frames, in order to increase the +<br/>flexibility of processing time. +<br/>The recognition thread is responsible for assessing the age, +<br/>gender and facial expression of each face crop found from the +<br/>image. The thread operates also in an asynchronous mode, +<br/>requesting new non-processed (but face-detected) frames from +</td><td>('51232696', 'Janne Tommola', 'janne tommola')<br/>('51149972', 'Pedram Ghazi', 'pedram ghazi')<br/>('51131997', 'Bishwo Adhikari', 'bishwo adhikari')<br/>('1847889', 'Heikki Huttunen', 'heikki huttunen')</td><td></td></tr><tr><td>7fce5769a7d9c69248178989a99d1231daa4fce9</td><td>(IJACSA) International Journal of Advanced Computer Science and Applications, <br/>Vol. 7, No. 5, 2016 <br/>Towards Face Recognition Using Eigenface <br/>Department of Computer Engineering @@ -36849,6 +46916,9 @@ <br/>and Microphones in E-Learning <br/><b>Welten Institute, Research Centre for Learning, Teaching and Technology, Faculty of</b><br/><b>Psychology and Educational Sciences, Open University of the Netherlands, Valkenburgerweg</b><br/>177, 6419 AT Heerlen, The Netherlands </td><td>('2565070', 'Kiavash Bahreini', 'kiavash bahreini')<br/>('1717772', 'Rob Nadolski', 'rob nadolski')<br/>('3235367', 'Wim Westera', 'wim westera')</td><td>{kiavash.bahreini, rob.nadolski, wim.westera}@ou.nl +</td></tr><tr><td>7fb5006b6522436ece5bedf509e79bdb7b79c9a7</td><td>Multi-Task Convolutional Neural Network for Face Recognition +<br/>Department of Computer Science and Engineering +<br/><b>Michigan State University, East Lansing MI</b></td><td>('2399004', 'Xi Yin', 'xi yin')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td>{yinxi1,liuxm}@msu.edu </td></tr><tr><td>7f533bd8f32525e2934a66a5b57d9143d7a89ee1</td><td>Audio-Visual Identity Grounding for Enabling Cross Media Search <br/>Paper ID 22 </td><td>('1950685', 'Kevin Brady', 'kevin brady')</td><td></td></tr><tr><td>7f44f8a5fd48b2d70cc2f344b4d1e7095f4f1fe5</td><td>Int J Comput Vis (2016) 119:60–75 @@ -36856,7 +46926,18 @@ <br/>Sparse Output Coding for Scalable Visual Recognition <br/>Received: 15 May 2013 / Accepted: 16 June 2015 / Published online: 26 June 2015 <br/>© Springer Science+Business Media New York 2015 -</td><td>('1729034', 'Bin Zhao', 'bin zhao')</td><td></td></tr><tr><td>7f6061c83dc36633911e4d726a497cdc1f31e58a</td><td>YouTube-8M: A Large-Scale Video Classification +</td><td>('1729034', 'Bin Zhao', 'bin zhao')</td><td></td></tr><tr><td>7f4bc8883c3b9872408cc391bcd294017848d0cf</td><td> +<br/> +<br/>Computer +<br/>Sciences +<br/>Department +<br/>The Multimodal Focused Attribute Model: A Nonparametric +<br/>Bayesian Approach to Simultaneous Object Classification and +<br/>Attribute Discovery +<br/>Technical Report #1697 +<br/>January 2012 +<br/> +</td><td>('6256616', 'Jake Rosin', 'jake rosin')<br/>('1724754', 'Charles R. Dyer', 'charles r. dyer')<br/>('1832364', 'Xiaojin Zhu', 'xiaojin zhu')</td><td></td></tr><tr><td>7f6061c83dc36633911e4d726a497cdc1f31e58a</td><td>YouTube-8M: A Large-Scale Video Classification <br/>Benchmark <br/>Paul Natsev <br/>Google Research @@ -36875,6 +46956,8 @@ <br/><b>University of Michigan</b><br/>Ann Arbor, MI 48105, USA </td><td>('3084614', 'Xinchen Yan', 'xinchen yan')<br/>('34316743', 'Junsong Yuan', 'junsong yuan')<br/>('2574445', 'Hui Liang', 'hui liang')</td><td>skywalkeryxc@gmail.com <br/>jsyuan@ntu.edu.sg, hliang1@e.ntu.edu.sg +</td></tr><tr><td>7f445191fa0475ff0113577d95502a96dc702ef9</td><td>Towards an Unequivocal Representation of Actions +<br/><b>University of Bristol</b><br/><b>University of Bristol</b><br/><b>University of Bristol</b></td><td>('2052236', 'Michael Wray', 'michael wray')<br/>('3420479', 'Davide Moltisanti', 'davide moltisanti')<br/>('1728459', 'Dima Damen', 'dima damen')</td><td>firstname.surname@bristol.ac.uk </td></tr><tr><td>7f82f8a416170e259b217186c9e38a9b05cb3eb4</td><td>Multi-Attribute Robust Component Analysis for Facial UV Maps <br/><b>Imperial College London, London, UK</b><br/><b>Middlesex University London, London, UK</b><br/><b>Goldsmiths, University of London, London, UK</b></td><td>('24278037', 'Stylianos Moschoglou', 'stylianos moschoglou')<br/>('31243357', 'Evangelos Ververas', 'evangelos ververas')<br/>('1780393', 'Yannis Panagakis', 'yannis panagakis')<br/>('1776444', 'Stefanos Zafeiriou', 'stefanos zafeiriou')</td><td>{s.moschoglou, e.ververas16, i.panagakis, s.zafeiriou}@imperial.ac.uk, m.nicolaou@gold.ac.uk </td></tr><tr><td>7f36dd9ead29649ed389306790faf3b390dc0aa2</td><td>MOVEMENT DIFFERENCES BETWEEN DELIBERATE @@ -36884,7 +46967,9 @@ <br/>Features with Soft Facial Attributes <br/>L. Zhang, P. Dou, I.A. Kakadiaris <br/>Computational Biomedicine Lab, 4849 Calhoun Rd, Rm 373, Houston, TX 77204 -</td><td></td><td></td></tr><tr><td>7f6599e674a33ed64549cd512ad75bdbd28c7f6c</td><td>Kernel Alignment Inspired +</td><td></td><td></td></tr><tr><td>7fab17ef7e25626643f1d55257a3e13348e435bd</td><td>Age Progression/Regression by Conditional Adversarial Autoencoder +<br/><b>The University of Tennessee, Knoxville, TN, USA</b></td><td>('1786391', 'Zhifei Zhang', 'zhifei zhang')<br/>('46970616', 'Yang Song', 'yang song')<br/>('1698645', 'Hairong Qi', 'hairong qi')</td><td>{zzhang61, ysong18, hqi}@utk.edu +</td></tr><tr><td>7f6599e674a33ed64549cd512ad75bdbd28c7f6c</td><td>Kernel Alignment Inspired <br/>Linear Discriminant Analysis <br/>Department of Computer Science and Engineering, <br/><b>University of Texas at Arlington, TX, USA</b></td><td>('1747268', 'Shuai Zheng', 'shuai zheng')</td><td>zhengs123@gmail.com, chqding@uta.edu @@ -37035,7 +47120,8 @@ <br/> ea whi <br/>de deve </td><td></td><td>weg@c. .ed -</td></tr><tr><td>7ae0212d6bf8a067b468f2a78054c64ea6a577ce</td><td>Human Face Processing Techniques +</td></tr><tr><td>7a81967598c2c0b3b3771c1af943efb1defd4482</td><td>Do We Need More Training Data? +</td><td>('32542103', 'Xiangxin Zhu', 'xiangxin zhu')</td><td></td></tr><tr><td>7ae0212d6bf8a067b468f2a78054c64ea6a577ce</td><td>Human Face Processing Techniques <br/>With Application To <br/>Large Scale Video Indexing <br/>DOCTOR OF @@ -37058,7 +47144,10 @@ </td><td></td><td>e-mail: [raul, marley]@ele.puc -rio.br, tuler@inf.puc-rio.br, [diogo, sam]@tecgraf.puc-rio.br </td></tr><tr><td>7ad77b6e727795a12fdacd1f328f4f904471233f</td><td>Supervised Local Descriptor Learning <br/>for Human Action Recognition -</td><td>('34798935', 'Xiantong Zhen', 'xiantong zhen')<br/>('40255667', 'Feng Zheng', 'feng zheng')<br/>('40799321', 'Ling Shao', 'ling shao')<br/>('1720247', 'Xianbin Cao', 'xianbin cao')<br/>('40147776', 'Dan Xu', 'dan xu')</td><td></td></tr><tr><td>7a7f2403e3cc7207e76475e8f27a501c21320a44</td><td>Emotion Recognition from Multi-Modal Information +</td><td>('34798935', 'Xiantong Zhen', 'xiantong zhen')<br/>('40255667', 'Feng Zheng', 'feng zheng')<br/>('40799321', 'Ling Shao', 'ling shao')<br/>('1720247', 'Xianbin Cao', 'xianbin cao')<br/>('40147776', 'Dan Xu', 'dan xu')</td><td></td></tr><tr><td>7a3d46f32f680144fd2ba261681b43b86b702b85</td><td>Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute +<br/>Classification +<br/><b>School of Information Science and Engineering, Xiamen University, Xiamen 361005, China</b><br/><b>bSchool of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China</b><br/>aFujian Key Laboratory of Sensing and Computing for Smart City, +<br/><b>cSchool of Computer Science, The University of Adelaide, Adelaide, SA 5005, Australia</b></td><td>('41034942', 'Ni Zhuang', 'ni zhuang')<br/>('40461734', 'Yan Yan', 'yan yan')<br/>('47336404', 'Si Chen', 'si chen')<br/>('37414077', 'Hanzi Wang', 'hanzi wang')<br/>('1780381', 'Chunhua Shen', 'chunhua shen')</td><td></td></tr><tr><td>7a97de9460d679efa5a5b4c6f0b0a5ef68b56b3b</td><td></td><td></td><td></td></tr><tr><td>7a7f2403e3cc7207e76475e8f27a501c21320a44</td><td>Emotion Recognition from Multi-Modal Information <br/>Department of Computer Science and Information Engineering, <br/><b>National Cheng Kung University, Tainan, Taiwan, R.O.C</b></td><td>('1681512', 'Chung-Hsien Wu', 'chung-hsien wu')<br/>('1709777', 'Jen-Chun Lin', 'jen-chun lin')<br/>('1691390', 'Wen-Li Wei', 'wen-li wei')<br/>('2891156', 'Kuan-Chun Cheng', 'kuan-chun cheng')</td><td>E-mail: chunghsienwu@gmail.com, jenchunlin@gmail.com, lilijinjin@gmail.com, davidcheng817@gmail.com </td></tr><tr><td>7aafeb9aab48fb2c34bed4b86755ac71e3f00338</td><td>Article @@ -37086,7 +47175,13 @@ </td><td>('1736182', 'Yu Zhu', 'yu zhu')<br/>('1698571', 'Yan Li', 'yan li')<br/>('2501850', 'Guowang Mu', 'guowang mu')<br/>('1822413', 'Guodong Guo', 'guodong guo')</td><td>yzhu4@mix.wvu.edu, yan.li@vipl.ict.ac.cn, guowang.mu@mail.wvu.edu , <br/>Guodong.Guo@mail.wvu.edu (corresponding author) </td></tr><tr><td>7ad7897740e701eae455457ea74ac10f8b307bed</td><td>Random Subspace Two-dimensional LDA for Face Recognition* -</td><td>('29980351', 'Garrett Bingham', 'garrett bingham')</td><td></td></tr><tr><td>7a1ce696e260899688cb705f243adf73c679f0d9</td><td>Predicting Missing Demographic Information in +</td><td>('29980351', 'Garrett Bingham', 'garrett bingham')</td><td></td></tr><tr><td>7ac9aaafe4d74542832c273acf9d631cb8ea6193</td><td>Deep Micro-Dictionary Learning and Coding Network +<br/><b>University of Trento, Trento, Italy</b><br/>2Department of Electrical Engineering, Hong Kong Polytechnic Unversity, Hong Kong, China +<br/>3Lingxi Artificial Interlligence Co., Ltd, Shen Zhen, China +<br/>4Computer Vision Laboratory, ´Ecole Polytechnique F´ed´erale de Lausanne, Lausanne, Switzerland +<br/><b>University of Oxford, Oxford, UK</b><br/><b>Texas State University, San Marcos, USA</b></td><td>('46666325', 'Hao Tang', 'hao tang')<br/>('49567679', 'Heng Wei', 'heng wei')<br/>('38505394', 'Wei Xiao', 'wei xiao')<br/>('47824598', 'Wei Wang', 'wei wang')<br/>('40147776', 'Dan Xu', 'dan xu')<br/>('1703601', 'Nicu Sebe', 'nicu sebe')</td><td>{hao.tang, niculae.sebe}@unitn.it, 15102924d@connect.polyu.hk, xiaoweithu@163.com +<br/>wei.wang@epfl.ch, danxu@robots.ox.ac.uk, y y34@txstate.edu +</td></tr><tr><td>7a1ce696e260899688cb705f243adf73c679f0d9</td><td>Predicting Missing Demographic Information in <br/>Biometric Records using Label Propagation <br/>Techniques <br/>Department of Computer Science and Engineering @@ -37095,6 +47190,23 @@ <br/><b>Michigan State University</b><br/>East Lansing, Michigan 48824 </td><td>('3153117', 'Thomas Swearingen', 'thomas swearingen')<br/>('1698707', 'Arun Ross', 'arun ross')</td><td>Email: swearin3@msu.edu <br/>Email: rossarun@msu.edu +</td></tr><tr><td>7a7b1352d97913ba7b5d9318d4c3d0d53d6fb697</td><td>Attend and Rectify: a Gated Attention +<br/>Mechanism for Fine-Grained Recovery +<br/>†Computer Vision Center and Universitat Aut`onoma de Barcelona (UAB), +<br/>Campus UAB, 08193 Bellaterra, Catalonia Spain +<br/>‡Visual Tagging Services, Parc de Recerca, Campus UAB +</td><td>('1739551', 'Josep M. Gonfaus', 'josep m. gonfaus')<br/>('7153363', 'Guillem Cucurull', 'guillem cucurull')<br/>('1696387', 'F. Xavier Roca', 'f. xavier roca')</td><td></td></tr><tr><td>7aa062c6c90dba866273f5edd413075b90077b51</td><td>I.J. Information Technology and Computer Science, 2017, 5, 40-51 +<br/>Published Online May 2017 in MECS (http://www.mecs-press.org/) +<br/>DOI: 10.5815/ijitcs.2017.05.06 +<br/>Minimizing Separability: A Comparative Analysis +<br/>of Illumination Compensation Techniques in Face +<br/>Recognition +<br/><b>Baze University, Abuja, Nigeria</b></td><td>('7392398', 'Chollette C. Olisah', 'chollette c. olisah')</td><td>E-mail: chollette.olisah@bazeuniversity.edu.ng +</td></tr><tr><td>7a131fafa7058fb75fdca32d0529bc7cb50429bd</td><td>Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and +<br/>Identity Preserving Frontal View Synthesis +<br/>1National Laboratory of Pattern Recognition, CASIA +<br/>2Center for Research on Intelligent Perception and Computing, CASIA +<br/><b>University of Chinese Academy of Sciences, Beijing, China</b></td><td>('48241673', 'Rui Huang', 'rui huang')<br/>('50202300', 'Shu Zhang', 'shu zhang')<br/>('50290162', 'Tianyu Li', 'tianyu li')<br/>('1705643', 'Ran He', 'ran he')</td><td>huangrui@cmu.edu, tianyu.lizard@gmail.com, {shu.zhang, rhe}@nlpr.ia.ac.cn </td></tr><tr><td>1451e7b11e66c86104f9391b80d9fb422fb11c01</td><td>IET Signal Processing <br/>Research Article <br/>Image privacy protection with secure JPEG @@ -37253,7 +47365,17 @@ <br/>of multiple classes. However, its classification performance was not sufficient for <br/>many applications in practice, because class subspaces are generated indepen- <br/>dently of each other [1]. There is no reason to assume a priori that each class -</td><td>('1770128', 'Kazuhiro Fukui', 'kazuhiro fukui')</td><td></td></tr><tr><td>146a7ecc7e34b85276dd0275c337eff6ba6ef8c0</td><td>This is a pre-print of the original paper submitted for review in FG 2017. +</td><td>('1770128', 'Kazuhiro Fukui', 'kazuhiro fukui')</td><td></td></tr><tr><td>1442319de86d171ce9595b20866ec865003e66fc</td><td>Vision-Based Fall Detection with Convolutional +<br/>Neural Networks +<br/><b>DeustoTech - University of Deusto</b><br/>Avenida de las Universidades, 24 - 48007, Bilbao, Spain +<br/>2 Dept. of Computer Science and Artificial Intelligence, Basque +<br/><b>Country University, San Sebastian, Spain</b><br/>P. Manuel Lardizabal, 1 - 20018, San Sebastian, Spain +<br/>3 Ikerbasque, Basque Foundation for Science, Bilbao, Spain +<br/>Maria Diaz de Haro, 3 - 48013 Bilbao, Spain +<br/>4 Donostia International Physics Center (DIPC), San Sebastian, Spain +<br/>P. Manuel Lardizabal, 4 - 20018, San Sebastian, Spain +</td><td>('2481918', 'Gorka Azkune', 'gorka azkune')<br/>('3147227', 'Ignacio Arganda-Carreras', 'ignacio arganda-carreras')</td><td>{adrian.nunez@deusto.es, gorka.azkune@deusto.es, ignacio.arganda@ehu.es} +</td></tr><tr><td>146a7ecc7e34b85276dd0275c337eff6ba6ef8c0</td><td>This is a pre-print of the original paper submitted for review in FG 2017. <br/>AFFACT - Alignment Free Facial Attribute Classification Technique <br/>Vision and Security Technology (VAST) Lab, <br/><b>University of Colorado Colorado Springs</b><br/>∗ authors with equal contribution @@ -37576,7 +47698,16 @@ </td></tr><tr><td>14a5feadd4209d21fa308e7a942967ea7c13b7b6</td><td>978-1-4673-0046-9/12/$26.00 ©2012 IEEE <br/>1025 <br/>ICASSP 2012 -</td><td></td><td></td></tr><tr><td>8ec82da82416bb8da8cdf2140c740e1574eaf84f</td><td>CHUNG AND ZISSERMAN: BMVC AUTHOR GUIDELINES +</td><td></td><td></td></tr><tr><td>14fee990a372bcc4cb6dc024ab7fc4ecf09dba2b</td><td>Modeling Spatio-Temporal Human Track Structure for Action +<br/>Localization +</td><td>('2926143', 'Anton Osokin', 'anton osokin')</td><td></td></tr><tr><td>14ee4948be56caeb30aa3b94968ce663e7496ce4</td><td>Jang, Y; Gunes, H; Patras, I +<br/>© Copyright 2018 IEEE +<br/>For additional information about this publication click this link. +<br/>http://qmro.qmul.ac.uk/xmlui/handle/123456789/36405 +<br/>Information about this research object was correct at the time of download; we occasionally +<br/>make corrections to records, please therefore check the published record when citing. For +</td><td></td><td>more information contact scholarlycommunications@qmul.ac.uk +</td></tr><tr><td>8ec82da82416bb8da8cdf2140c740e1574eaf84f</td><td>CHUNG AND ZISSERMAN: BMVC AUTHOR GUIDELINES <br/>Lip Reading in Profile <br/>http://www.robots.ox.ac.uk/~joon <br/>http://www.robots.ox.ac.uk/~az @@ -37623,7 +47754,19 @@ <br/>[11]. This could indicate that image manipulations tend to equalize face recognition abilities, and <br/>we investigate whether this is the case with the manipulations and face recognition algorithms we <br/>test. -</td><td>('1897270', 'Cathy Chen', 'cathy chen')</td><td></td></tr><tr><td>8e94ed0d7606408a0833e69c3185d6dcbe22bbbe</td><td>© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE +</td><td>('1897270', 'Cathy Chen', 'cathy chen')</td><td></td></tr><tr><td>8e3d0b401dec8818cd0245c540c6bc032f169a1d</td><td>McGan: Mean and Covariance Feature Matching GAN +</td><td>('2211263', 'Youssef Mroueh', 'youssef mroueh')</td><td></td></tr><tr><td>8e3c97e420e0112c043929087d6456d8ab61e95c</td><td>SAFDARNEJAD et al.: ROBUST GLOBAL MOTION COMPENSATION +<br/>Robust Global Motion Compensation in +<br/>Presence of Predominant Foreground +<br/>https://www.msu.edu/~safdarne/ +<br/>http://www.cse.msu.edu/~liuxm/ +<br/>http://www.egr.msu.edu/ndel/profile/lalita-udpa +<br/><b>Michigan State University</b><br/>East Lansing +<br/>Michigan, USA +</td><td>('2941187', 'Seyed Morteza Safdarnejad', 'seyed morteza safdarnejad')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')<br/>('1938832', 'Lalita Udpa', 'lalita udpa')</td><td></td></tr><tr><td>8e0ab1b08964393e4f9f42ca037220fe98aad7ac</td><td>UV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face +<br/>Recognition +<br/><b>Imperial College London</b></td><td>('3234063', 'Jiankang Deng', 'jiankang deng')<br/>('1902288', 'Shiyang Cheng', 'shiyang cheng')<br/>('4091869', 'Niannan Xue', 'niannan xue')<br/>('47943220', 'Yuxiang Zhou', 'yuxiang zhou')</td><td>j.deng16, shiyang.cheng11,n.xue15,yuxiang.zhou10,s.zafeiriou@imperial.ac.uk +</td></tr><tr><td>8e94ed0d7606408a0833e69c3185d6dcbe22bbbe</td><td>© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE <br/>must be obtained for all other uses, in any current or future media, including <br/>reprinting/republishing this material for advertising or promotional purposes, <br/>creating new collective works, for resale or redistribution to servers or lists, or @@ -37643,7 +47786,7 @@ <br/>Multimedia Communications Department <br/>BP 193, 06904 Sophia Antipolis Cedex, France </td><td>('1723883', 'Florent Perronnin', 'florent perronnin')<br/>('1709849', 'Jean-Luc Dugelay', 'jean-luc dugelay')</td><td>fflorent.perronnin, jean-luc.dugelayg@eurecom.fr -</td></tr><tr><td>8e0ad1ccddc7ec73916eddd2b7bbc0019d8a7958</td><td>Segment-based SVMs for +</td></tr><tr><td>8ed32c8fad924736ebc6d99c5c319312ba1fa80b</td><td></td><td></td><td></td></tr><tr><td>8e0ad1ccddc7ec73916eddd2b7bbc0019d8a7958</td><td>Segment-based SVMs for <br/>Time Series Analysis <br/>CMU-RI-TR-12-1 <br/>Submitted in partial fulfillment of the @@ -37684,7 +47827,13 @@ <br/>am 18.09.2008 angenommen. </td><td></td><td></td></tr><tr><td>8ed051be31309a71b75e584bc812b71a0344a019</td><td>Class-based feature matching across unrestricted <br/>transformations -</td><td>('1938475', 'Evgeniy Bart', 'evgeniy bart')<br/>('1743045', 'Shimon Ullman', 'shimon ullman')</td><td></td></tr><tr><td>8ee5b1c9fb0bded3578113c738060290403ed472</td><td>Extending Explicit Shape Regression with +</td><td>('1938475', 'Evgeniy Bart', 'evgeniy bart')<br/>('1743045', 'Shimon Ullman', 'shimon ullman')</td><td></td></tr><tr><td>8e36100cb144685c26e46ad034c524b830b8b2f2</td><td>Modeling Facial Geometry using Compositional VAEs +<br/>1 ´Ecole Polytechnique F´ed´erale de Lausanne +<br/>2Facebook Reality Labs, Pittsburgh +</td><td>('33846296', 'Chenglei Wu', 'chenglei wu')<br/>('14373499', 'Jason Saragih', 'jason saragih')<br/>('1717736', 'Pascal Fua', 'pascal fua')<br/>('1774867', 'Yaser Sheikh', 'yaser sheikh')</td><td>{firstname.lastname}@epfl.ch, {firstname.lastname}@fb.com +</td></tr><tr><td>8ed33184fccde677ec8413ae06f28ea9f2ca70f3</td><td>Multimodal Visual Concept Learning with Weakly Supervised Techniques +<br/><b>School of E.C.E., National Technical University of Athens, Greece</b></td><td>('7311172', 'Giorgos Bouritsas', 'giorgos bouritsas')<br/>('2539459', 'Petros Koutras', 'petros koutras')<br/>('2641229', 'Athanasia Zlatintsi', 'athanasia zlatintsi')<br/>('1750686', 'Petros Maragos', 'petros maragos')</td><td>gbouritsas@gmail.com, {pkoutras, nzlat, maragos}@cs.ntua.gr +</td></tr><tr><td>8ee5b1c9fb0bded3578113c738060290403ed472</td><td>Extending Explicit Shape Regression with <br/>Mixed Feature Channels and Pose Priors <br/><b>Karlsruhe Institute of</b><br/>Technology (KIT) <br/>Karlsruhe, Germany @@ -37697,7 +47846,13 @@ </td><td>('39610204', 'Matthias Richter', 'matthias richter')<br/>('1697965', 'Hua Gao', 'hua gao')</td><td>matthias.richter@kit.edu <br/>hua.gao@epfl.ch <br/>ekenel@itu.edu.tr -</td></tr><tr><td>8efda5708bbcf658d4f567e3866e3549fe045bbb</td><td>Pre-trained Deep Convolutional Neural Networks +</td></tr><tr><td>8e0becfc5fe3ecdd2ac93fabe34634827b21ef2b</td><td>International Journal of Computer Vision manuscript No. +<br/>(will be inserted by the editor) +<br/>Learning from Longitudinal Face Demonstration - +<br/>Where Tractable Deep Modeling Meets Inverse Reinforcement Learning +<br/>Savvides · Tien D. Bui +<br/>Received: date / Accepted: date +</td><td>('1876581', 'Chi Nhan Duong', 'chi nhan duong')</td><td></td></tr><tr><td>8efda5708bbcf658d4f567e3866e3549fe045bbb</td><td>Pre-trained Deep Convolutional Neural Networks <br/>for Face Recognition <br/>Siebert Looije <br/>S2209276 @@ -37708,7 +47863,17 @@ <br/>Dr. M.A. (Marco) Wiering <br/>K. (Klaas) Dijkstra, MSc. <br/><b>ALICE Institute</b><br/><b>University of Groningen</b><br/>Nijenborgh 9, 9747 AG, Groningen, The Netherlands -<br/><b>facultyofmathematicsandnaturalsciencesarti cialintelligence22-09-2016|1ATitleA.UthorRijksuniversiteitGroningenSomeFaculty</b></td><td></td><td></td></tr><tr><td>225fb9181545f8750061c7693661b62d715dc542</td><td></td><td></td><td></td></tr><tr><td>22043cbd2b70cb8195d8d0500460ddc00ddb1a62</td><td>Separability-Oriented Subclass Discriminant +<br/><b>facultyofmathematicsandnaturalsciencesarti cialintelligence22-09-2016|1ATitleA.UthorRijksuniversiteitGroningenSomeFaculty</b></td><td></td><td></td></tr><tr><td>2227f978f084ebb18cb594c0cfaf124b0df6bf95</td><td>Pillar Networks for action recognition +<br/>B Sengupta +<br/>Cortexica Vision Systems Limited +<br/><b>Imperial College London</b><br/>London, UK +<br/>Y Qian +<br/>Cortexica Vision Systems Limited +<br/>30 Stamford Street SE1 9LQ +<br/>London, UK +</td><td></td><td>b.sengupta@imperial.ac.uk +<br/>yu.qian@cortexica.com +</td></tr><tr><td>225fb9181545f8750061c7693661b62d715dc542</td><td></td><td></td><td></td></tr><tr><td>22043cbd2b70cb8195d8d0500460ddc00ddb1a62</td><td>Separability-Oriented Subclass Discriminant <br/>Analysis </td><td>('2986129', 'Huan Wan', 'huan wan')<br/>('27838939', 'Hui Wang', 'hui wang')<br/>('35009947', 'Gongde Guo', 'gongde guo')<br/>('10803956', 'Xin Wei', 'xin wei')</td><td></td></tr><tr><td>22137ce9c01a8fdebf92ef35407a5a5d18730dde</td><td></td><td></td><td></td></tr><tr><td>22e2066acfb795ac4db3f97d2ac176d6ca41836c</td><td>Coarse-to-Fine Auto-Encoder Networks (CFAN) <br/>for Real-Time Face Alignment @@ -37769,9 +47934,19 @@ </td></tr><tr><td>22e678d3e915218a7c09af0d1602e73080658bb7</td><td>Adventures in Archiving and Using Three Years of Webcam Images <br/>Department of Computer Science and Engineering <br/><b>Washington University, St. Louis, MO, USA</b></td><td>('1990750', 'Nathan Jacobs', 'nathan jacobs')<br/>('39795519', 'Walker Burgin', 'walker burgin')<br/>('1761429', 'Robert Pless', 'robert pless')</td><td>{jacobsn,wsb1,rzs1,dyr1,pless}@cse.wustl.edu -</td></tr><tr><td>227b18fab568472bf14f9665cedfb95ed33e5fce</td><td>Compositional Dictionaries for Domain Adaptive +</td></tr><tr><td>2201f187a7483982c2e8e2585ad9907c5e66671d</td><td>Joint Face Alignment and 3D Face Reconstruction +<br/><b>College of Computer Science, Sichuan University, Chengdu, China</b><br/>2 Department of Computer Science and Engineering +<br/><b>Michigan State University, East Lansing, MI, U.S.A</b></td><td>('50207647', 'Feng Liu', 'feng liu')<br/>('39422721', 'Dan Zeng', 'dan zeng')<br/>('7345195', 'Qijun Zhao', 'qijun zhao')<br/>('1759169', 'Xiaoming Liu', 'xiaoming liu')</td><td></td></tr><tr><td>227b18fab568472bf14f9665cedfb95ed33e5fce</td><td>Compositional Dictionaries for Domain Adaptive <br/>Face Recognition -</td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>2241eda10b76efd84f3c05bdd836619b4a3df97e</td><td>One-to-many face recognition with bilinear CNNs +</td><td>('2077648', 'Qiang Qiu', 'qiang qiu')<br/>('9215658', 'Rama Chellappa', 'rama chellappa')</td><td></td></tr><tr><td>227b1a09b942eaf130d1d84cdcabf98921780a22</td><td>Yang et al. EURASIP Journal on Advances in Signal Processing (2018) 2018:51 +<br/>https://doi.org/10.1186/s13634-018-0572-6 +<br/>EURASIP Journal on Advances +<br/>in Signal Processing +<br/>R ES EAR CH +<br/>Multi-feature shape regression for face +<br/>alignment +<br/>Open Access +</td><td>('3413708', 'Wei-jong Yang', 'wei-jong yang')<br/>('49070426', 'Yi-Chen Chen', 'yi-chen chen')<br/>('1789917', 'Pau-Choo Chung', 'pau-choo chung')<br/>('1749263', 'Jar-Ferr Yang', 'jar-ferr yang')</td><td></td></tr><tr><td>2241eda10b76efd84f3c05bdd836619b4a3df97e</td><td>One-to-many face recognition with bilinear CNNs <br/>Aruni RoyChowdhury <br/><b>University of Massachusetts, Amherst</b><br/>Erik Learned-Miller </td><td>('2144284', 'Tsung-Yu Lin', 'tsung-yu lin')<br/>('35208858', 'Subhransu Maji', 'subhransu maji')</td><td>{arunirc,tsungyulin,smaji,elm}@cs.umass.edu @@ -37823,6 +47998,13 @@ </td><td>('2986395', 'Panna Felsen', 'panna felsen')<br/>('33932184', 'Pulkit Agrawal', 'pulkit agrawal')<br/>('1689212', 'Jitendra Malik', 'jitendra malik')</td><td>panna@berkeley.edu <br/>pulkitag@berkeley.edu <br/>malik@berkeley.edu +</td></tr><tr><td>25ff865460c2b5481fa4161749d5da8501010aa0</td><td>Seeing What Is Not There: +<br/>Learning Context to Determine Where Objects Are Missing +<br/>Department of Computer Science +<br/><b>University of Maryland</b><br/>Figure 1: When curb ramps (green rectangle) are missing from a segment of sidewalks in an intersection (orange rectangle), +<br/>people with mobility impairments are unable to cross the street. We propose an approach to determine where objects are +<br/>missing by learning a context model so that it can be combined with object detection results. +</td><td>('39516880', 'Jin Sun', 'jin sun')<br/>('34734622', 'David W. Jacobs', 'david w. jacobs')</td><td>{jinsun,djacobs}@cs.umd.edu </td></tr><tr><td>25d514d26ecbc147becf4117512523412e1f060b</td><td>Annotated Crowd Video Face Database <br/>IIIT-Delhi, India </td><td>('2952437', 'Tejas I. Dhamecha', 'tejas i. dhamecha')<br/>('2578160', 'Priyanka Verma', 'priyanka verma')<br/>('3239512', 'Mahek Shah', 'mahek shah')<br/>('39129417', 'Richa Singh', 'richa singh')<br/>('2338122', 'Mayank Vatsa', 'mayank vatsa')</td><td>{tejasd,priyanka13100,mahek13106,rsingh,mayank}@iiitd.ac.in @@ -37871,7 +48053,16 @@ <br/>yi.gao@stonybrookmedicine.edu </td></tr><tr><td>25d3e122fec578a14226dc7c007fb1f05ddf97f7</td><td>The First Facial Expression Recognition and Analysis Challenge </td><td>('1795528', 'Michel F. Valstar', 'michel f. valstar')<br/>('39532631', 'Bihan Jiang', 'bihan jiang')<br/>('1875347', 'Marc Mehu', 'marc mehu')<br/>('1694605', 'Maja Pantic', 'maja pantic')</td><td></td></tr><tr><td>2597b0dccdf3d89eaffd32e202570b1fbbedd1d6</td><td>Towards predicting the likeability of fashion images -</td><td>('2569065', 'Jinghua Wang', 'jinghua wang')<br/>('2613790', 'Abrar Abdul Nabi', 'abrar abdul nabi')<br/>('22804340', 'Gang Wang', 'gang wang')<br/>('2737180', 'Chengde Wan', 'chengde wan')<br/>('2475944', 'Tian-Tsong Ng', 'tian-tsong ng')</td><td></td></tr><tr><td>25c108a56e4cb757b62911639a40e9caf07f1b4f</td><td>Recurrent Scale Approximation for Object Detection in CNN +</td><td>('2569065', 'Jinghua Wang', 'jinghua wang')<br/>('2613790', 'Abrar Abdul Nabi', 'abrar abdul nabi')<br/>('22804340', 'Gang Wang', 'gang wang')<br/>('2737180', 'Chengde Wan', 'chengde wan')<br/>('2475944', 'Tian-Tsong Ng', 'tian-tsong ng')</td><td></td></tr><tr><td>2588acc7a730d864f84d4e1a050070ff873b03d5</td><td>Article +<br/>Action Recognition by an Attention-Aware Temporal +<br/>Weighted Convolutional Neural Network +<br/><b>Institute of Arti cial Intelligence and Robotics, Xi an Jiaotong University, Xi an 710049, China</b><br/>Received: 27 April 2018; Accepted: 19 June 2018; Published: 21 June 2018 +</td><td>('40367806', 'Le Wang', 'le wang')<br/>('14800230', 'Jinliang Zang', 'jinliang zang')<br/>('46324995', 'Qilin Zhang', 'qilin zhang')<br/>('1786361', 'Zhenxing Niu', 'zhenxing niu')<br/>('1745420', 'Gang Hua', 'gang hua')<br/>('1715389', 'Nanning Zheng', 'nanning zheng')</td><td>zjl19920904@stu.xjtu.edu.cn (J.Z.); nnzheng@xjtu.edu.cn (N.Z.) +<br/>2 HERE Technologies, Chicago, IL 60606, USA; qilin.zhang@here.com +<br/>3 Alibaba Group, Hangzhou 311121, China; zhenxing.nzx@alibaba-inc.com +<br/>4 Microsoft Research, Redmond, WA 98052, USA; ganghua@microsoft.com +<br/>* Correspondence: lewang@xjtu.edu.cn; Tel.: +86-29-8266-8672 +</td></tr><tr><td>25982e2bef817ebde7be5bb80b22a9864b979fb0</td><td></td><td></td><td></td></tr><tr><td>25c108a56e4cb757b62911639a40e9caf07f1b4f</td><td>Recurrent Scale Approximation for Object Detection in CNN <br/><b>Multimedia Laboratory at The Chinese University of Hong Kong</b><br/>1SenseTime Group Limited </td><td>('1715752', 'Yu Liu', 'yu liu')<br/>('1929886', 'Hongyang Li', 'hongyang li')<br/>('1721677', 'Junjie Yan', 'junjie yan')<br/>('22181490', 'Fangyin Wei', 'fangyin wei')<br/>('31843833', 'Xiaogang Wang', 'xiaogang wang')<br/>('1741901', 'Xiaoou Tang', 'xiaoou tang')</td><td>liuyuisanai@gmail.com,{yangli,xgwang}@ee.cuhk.edu.hk, <br/>{yanjunjie,weifangyin}@sensetime.com, xtang@ie.cuhk.edu.hk |