diff options
Diffstat (limited to 'site/datasets/citations/tud_brussels.json')
| -rw-r--r-- | site/datasets/citations/tud_brussels.json | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/site/datasets/citations/tud_brussels.json b/site/datasets/citations/tud_brussels.json index 0960ab8e..d8f1546e 100644 --- a/site/datasets/citations/tud_brussels.json +++ b/site/datasets/citations/tud_brussels.json @@ -1 +1 @@ -{"id": "6ad5a38df8dd4cdddd74f31996ce096d41219f72", "paper": {"paperId": "6ad5a38df8dd4cdddd74f31996ce096d41219f72", "key": "tud_brussels", "title": "Multi-cue onboard pedestrian detection", "journal": "2009 IEEE Conference on Computer Vision and Pattern Recognition", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "https://www.mpi-inf.mpg.de/fileadmin/inf/d2/wojek/poster_cwojek_cvpr09.pdf", "report_link": "papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html", "citation_count": 217, "citations_geocoded": 40, "citations_unknown": 177, "citations_empty": 14, "citations_pdf": 131, "citations_doi": 86, "name": "TUD-Brussels"}, "address": null, "citations": [["Multi-stage Contextual Deep Learning for Pedestrian Detection", "", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", 2013], ["Ten Years of Pedestrian Detection, What Have We Learned?", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", 2014], ["Multiple People Tracking-by-Detection in a Multi-camera Environment", "", "Technical University Munich", "Technical University Munich", "TUM, 21, Arcisstra\u00dfe, Bezirksteil K\u00f6nigsplatz, Stadtbezirk 03 Maxvorstadt, M\u00fcnchen, Obb, Bayern, 80333, Deutschland", "48.14955455", "11.56775314", "edu", "", "2015"], ["Informed Haar-Like Features Improve Pedestrian Detection", "", "University of Bonn", "University of Bonn", "Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk K\u00f6ln, Nordrhein-Westfalen, 53113, Deutschland", "50.73381240", "7.10224650", "edu", "", 2014], ["Contextual Combination of Appearance and Motion for Intersection Videos with Vehicles and Pedestrians", "", "University of Nevada", "University of Nevada", "Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA", "39.54694490", "-119.81346566", "edu", "", 2014], ["Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters", "", "Tsinghua University", "Tsinghua University", "\u6e05\u534e\u5927\u5b66, 30, \u53cc\u6e05\u8def, \u4e94\u9053\u53e3, \u540e\u516b\u5bb6, \u6d77\u6dc0\u533a, 100084, \u4e2d\u56fd", "40.00229045", "116.32098908", "edu", "", "2017"], ["Fused DNN: A Deep Neural Network Fusion Approach to Fast and Robust Pedestrian Detection", "", "University of Maryland", "University of Maryland", "The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA", "39.28996850", "-76.62196103", "edu", "", "2017"], ["Pyramid Center-Symmetric Local Binary/Trinary Patterns for Effective Pedestrian Detection", "", "Australian National University", "Australian National University", "Canberra ACT 0200, Australia", "-35.27769990", "149.11852700", "edu", "", 2010], ["End-to-End People Detection in Crowded Scenes", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", 2016], ["Person Re-identification Meets Image Search", "", "University of Texas at San Antonio", "University of Texas at San Antonio", "UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA", "29.58333105", "-98.61944505", "edu", "", 2015], ["Isotropic Granularity-tunable gradients partition (IGGP) descriptors for human detection", "", "University of Oulu", "University of Oulu", "Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi", "65.05921570", "25.46632601", "edu", "", 2010], ["Efficient Online Spatio-Temporal Filtering for Video Event Detection", "", "University of Michigan", "University of Michigan", "University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA", "42.29421420", "-83.71003894", "edu", "", 2014], ["Multi-pedestrian detection in crowded scenes: A global view", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", 2012], ["Pedestrian Attribute Detection Using CNN", "", "Stanford University", "Stanford University", "Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA", "37.43131385", "-122.16936535", "edu", "", 2016], ["SPID: Surveillance Pedestrian Image Dataset and Performance Evaluation for Pedestrian Detection", "", "Shanghai Jiao Tong University", "Shanghai Jiao Tong University", "\u4e0a\u6d77\u4ea4\u901a\u5927\u5b66\uff08\u5f90\u6c47\u6821\u533a\uff09, \u6dee\u6d77\u897f\u8def, \u756a\u79ba\u5c0f\u533a, \u5e73\u9634\u6865, \u5f90\u6c47\u533a, \u4e0a\u6d77\u5e02, 200052, \u4e2d\u56fd", "31.20081505", "121.42840681", "edu", "", 2016], ["Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation", "", "Hefei University of Technology", "Hefei University of Technology", "\u5408\u80a5\u5de5\u4e1a\u5927\u5b66\uff08\u5c6f\u6eaa\u8def\u6821\u533a\uff09, 193\u53f7, \u5357\u4e00\u73af\u8def, \u822a\u8fd0\u5357\u6751, \u5305\u516c\u8857\u9053, \u5408\u80a5\u5e02\u533a, \u5408\u80a5\u5e02, \u5b89\u5fbd\u7701, 230009, \u4e2d\u56fd", "31.84691800", "117.29053367", "edu", "", 2016], ["Efficient Boosted Weak Classifiers for Object Detection", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", 2013], ["Human Detection in Video over Large Viewpoint Changes", "", "OMRON Corporation, Kyoto, Japan", "Core Technology Center, OMRON Corporation, Kyoto, Japan", "Kyoto, Kyoto Prefecture, Japan", "35.01163630", "135.76802940", "company", "", 2010], ["CityPersons: A Diverse Dataset for Pedestrian Detection", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", "2017"], ["The Fastest Pedestrian Detector in the West", "", "University of California, San Diego", "University of California, San Diego", "UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA", "32.87935255", "-117.23110049", "edu", "", 2010], ["Scalable Person Re-identification: A Benchmark", "", "University of Texas at San Antonio", "University of Texas at San Antonio", "UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA", "29.58333105", "-98.61944505", "edu", "", 2015], ["UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "2015"], ["Single-Pedestrian Detection Aided by Multi-pedestrian Detection", "", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", 2013], ["Vehicle Detection Method Based on Edge Information and Local Transform Histogram", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", 2013], ["Quality-adaptive deep learning for pedestrian detection", "", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", 2017], ["Pedestrian Detection and Tracking Using HOG and Oriented-LBP Features", "", "Shenzhen Institutes of Advanced Technology", "Shenzhen Institutes of Advanced Technology", "\u4e2d\u56fd\u79d1\u5b66\u9662\u6df1\u5733\u5148\u8fdb\u6280\u672f\u7814\u7a76\u9662, 1068, \u79d1\u7814\u8def, \u6df1\u5733\u5927\u5b66\u57ce, \u4e09\u5751\u6751, \u5357\u5c71\u533a, \u6df1\u5733\u5e02, \u5e7f\u4e1c\u7701, 518000, \u4e2d\u56fd", "22.59805605", "113.98533784", "edu", "", 2011], ["Learning and Exploiting Camera Geometry for Computer Vision", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", "2016"], ["Robust Multi-resolution Pedestrian Detection in Traffic Scenes", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", 2013], ["Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters", "", "Carnegie Mellon University", "Carnegie Mellon University", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "2017"], ["A Diverse Dataset for Pedestrian Detection", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", ""], ["MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding", "", "Columbia University", "Columbia University", "Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA", "40.84198360", "-73.94368971", "edu", "", 2015], ["Pedestrian Detection Based on Sparse and Low-Rank Matrix Decomposition", "", "Jiangsu University", "Jiangsu University", "\u6c5f\u82cf\u5927\u5b66, 301, \u5b66\u5e9c\u8def, \u4eac\u53e3\u533a, \u8c61\u5c71\u8857\u9053, \u4eac\u53e3\u533a (Jingkou), \u9547\u6c5f\u5e02 / Zhenjiang, \u6c5f\u82cf\u7701, 212013, \u4e2d\u56fd", "32.20302965", "119.50968362", "edu", "", 2013], ["Fusion of Depth and Vision Information for Human Detection \u22c6", "", "Wayne State University", "Wayne State University", "Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA", "42.35775700", "-83.06286711", "edu", "", 2013], ["Spatial-Temporal Granularity-Tunable Gradients Partition (STGGP) Descriptors for Human Detection", "", "University of Oulu", "University of Oulu", "Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi", "65.05921570", "25.46632601", "edu", "", 2010], ["Integrating Perception and Cognition for AGI", "", "Carnegie Mellon University", "Carnegie Mellon University", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", 2011], ["Co-occurrence flow for pedestrian detection", "", "University of Cambridge", "University of Cambridge", "Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK", "52.17638955", "0.14308882", "edu", "", 2011], ["Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash", "", "Texas A&M University", "Texas A&M University", "Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA", "30.61083650", "-96.35212800", "edu", "", "2018"], ["Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice", "", "York University", "York University", "York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada", "43.77439110", "-79.50481085", "edu", "", "2018"], ["Viewpoint Adaptation for Person Detection", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", 2016], ["Pedestrian Detection with Semantic Regions of Interest", "", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences, UCAS, Yuquanlu, \u7389\u6cc9\u8def, \u7530\u6751, \u6d77\u6dc0\u533a, 100049, \u4e2d\u56fd", "39.90828040", "116.24585270", "edu", "", 2017]]}
\ No newline at end of file +{"id": "6ad5a38df8dd4cdddd74f31996ce096d41219f72", "paper": {"paperId": "6ad5a38df8dd4cdddd74f31996ce096d41219f72", "key": "tud_brussels", "title": "Multi-cue onboard pedestrian detection", "journal": "2009 IEEE Conference on Computer Vision and Pattern Recognition", "address": "", "address_type": "", "lat": "", "lng": "", "pdf_link": "http://vision.lbl.gov/Conferences/cvpr/Papers/data/papers/1454.pdf", "report_link": "papers/6ad5a38df8dd4cdddd74f31996ce096d41219f72.html", "citation_count": 217, "citations_geocoded": 110, "citations_unknown": 107, "citations_empty": 14, "citations_pdf": 131, "citations_doi": 86, "name": "TUD-Brussels"}, "address": null, "citations": [["Multi-stage Contextual Deep Learning for Pedestrian Detection", "", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", "2013"], ["A Joint Integrated Probabilistic Data Association Filter for pedestrian tracking across blind regions using monocular camera and radar", "Institute of Industrial Information Technology, Karlsruhe Institute of Technology, 76187 Karlsruhe, Germany", "Karlsruhe Institute of Technology", "Karlsruhe Institute of Technology", "KIT, Leopoldshafener Allee, Linkenheim, Linkenheim-Hochstetten, Landkreis Karlsruhe, Regierungsbezirk Karlsruhe, Baden-W\u00fcrttemberg, 76351, Deutschland", "49.10184375", "8.43312560", "edu", "", "2012"], ["An HOG-CT human detector with histogram-based search", "State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou, China", "Zhejiang University", "Zhejiang University", "\u6d59\u6c5f\u5927\u5b66\u4e4b\u6c5f\u6821\u533a, \u4e4b\u6c5f\u8def, \u8f6c\u5858\u8857\u9053, \u897f\u6e56\u533a (Xihu), \u676d\u5dde\u5e02 Hangzhou, \u6d59\u6c5f\u7701, 310008, \u4e2d\u56fd", "30.19331415", "120.11930822", "edu", "", "2011"], ["Multi-cue pedestrian classification with partial occlusion handling", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2010"], ["Ten Years of Pedestrian Detection, What Have We Learned?", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", "2014"], ["Automatic generation of training samples and a learning method based on advanced MILBoost for human detection", "Chubu University, Japan", "Chubu University", "Chubu University", "\u4e2d\u90e8\u5927\u5b66, \u56fd\u905319\u53f7, \u6625\u65e5\u4e95\u5e02, \u611b\u77e5\u770c, \u4e2d\u90e8\u5730\u65b9, 487-8501, \u65e5\u672c", "35.27426550", "137.01327841", "edu", "", "2011"], ["Vision based victim detection from unmanned aerial vehicles", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2010"], ["Pedestrian detection via contour fragments", "Key Laboratory of Measurement and Control of Complex Systems of Engineering, Southeast University, Nanjing, China", "Southeast University", "Southeast University", "SEU, \u4f53\u80b2\u9986\u8def, \u65b0\u8857\u53e3, \u6708\u5b63\u56ed, \u7384\u6b66\u533a, \u5357\u4eac\u5e02, \u6c5f\u82cf\u7701, 210008, \u4e2d\u56fd", "32.05752790", "118.78682252", "edu", "", "2016"], ["Multiple People Tracking-by-Detection in a Multi-camera Environment", "", "Technical University Munich", "Technical University Munich", "TUM, 21, Arcisstra\u00dfe, Bezirksteil K\u00f6nigsplatz, Stadtbezirk 03 Maxvorstadt, M\u00fcnchen, Obb, Bayern, 80333, Deutschland", "48.14955455", "11.56775314", "edu", "", "2015"], ["Auto++: Detecting Cars Using Embedded Microphones in Real-Time", "WINLAB, Rutgers University", "Rutgers University", "Rutgers University", "Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA", "40.47913175", "-74.43168868", "edu", "", "2017"], ["A review on vision-based pedestrian detection in intelligent transportation systems", "State Key Laboratory of Management and Control for Complex Systems, Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "2012"], ["Informed Haar-Like Features Improve Pedestrian Detection", "", "University of Bonn", "University of Bonn", "Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk K\u00f6ln, Nordrhein-Westfalen, 53113, Deutschland", "50.73381240", "7.10224650", "edu", "", "2014"], ["Pedestrian Detection via Body Part Semantic and Contextual Information With DNN", "School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China", "University of Electronic Science and Technology of China", "University of Electronic Science and Technology of China", "Columbus, OH 43210, USA", "40.01419050", "-83.03091430", "edu", "", "2018"], ["Fast pedestrian detection using a modified WLD detector in salient region", "School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China", "Sun Yat-Sen University", "Sun Yat-Sen University", "\u4e2d\u5927, \u65b0\u6e2f\u897f\u8def, \u9f99\u8239\u6ed8, \u5eb7\u4e50, \u6d77\u73e0\u533a (Haizhu), \u5e7f\u5dde\u5e02, \u5e7f\u4e1c\u7701, 510105, \u4e2d\u56fd", "23.09461185", "113.28788994", "edu", "", "2011"], ["Efficient Stixel-based object recognition", "Environment Perception Group, Daimler AG Group Research & Advanced Engineering, 71059 Sindelfingen, Germany", "Environment Perception Group, Daimler AG", "Environment Perception Group, Daimler AG Group Research & Advanced Engineering, 71059 Sindelfingen, Germany", "Sindelfingen, Germany", "48.70745580", "9.00440530", "company", "", "2012"], ["Pedestrian detection based on improved HOG feature and robust adaptive boosting algorithm", "College of Information Science and Engineering, Hunan University, Changsha, China", "Hunan University", "Hunan University", "Yejin University for Employees, \u51b6\u91d1\u897f\u8def, \u548c\u5e73\u4e61, \u73e0\u6656\u533a, \u8861\u9633\u5e02 / Hengyang, \u6e56\u5357\u7701, \u4e2d\u56fd", "26.88111275", "112.62850666", "edu", "", "2011"], ["Pedestrian detection based on the privileged information", "School of Economics and Management, University of Chinese Academy Sciences, Beijing, China", "China", "China", "China", "35.86166000", "104.19539700", "edu", "", "2016"], ["People detection based on appearance and motion models", "Video Processing and Understanding Lab, Universidad Aut\u00f3noma de Madrid (Spain)", "Video Processing and Understanding Lab, Universidad Aut\u00f3noma de Madrid (Spain)", "Video Processing and Understanding Lab, Universidad Aut\u00f3noma de Madrid (Spain)", "Ciudad Universitaria de Cantoblanco, 28049 Madrid, Spain", "40.54669830", "-3.69436190", "edu", "", "2011"], ["Contextual Combination of Appearance and Motion for Intersection Videos with Vehicles and Pedestrians", "", "University of Nevada", "University of Nevada", "Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA", "39.54694490", "-119.81346566", "edu", "", "2014"], ["Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters", "", "China", "China", "China", "35.86166000", "104.19539700", "edu", "", "2017"], ["Fused DNN: A Deep Neural Network Fusion Approach to Fast and Robust Pedestrian Detection", "", "University of Maryland", "University of Maryland", "The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA", "39.28996850", "-76.62196103", "edu", "", "2017"], ["MKL-SVM-based human detection for autonomous navigation of a robot", "Research & Technology Center, North American Robot Bosch LLC, 2835 East Carson Street Suite 210, Pittsburgh, 15203, USA", "Research & Technology Center, North American Robot Bosch LLC, 2835 East Carson Street Suite 210, Pittsburgh, 15203, USA", "Research & Technology Center, North American Robot Bosch LLC, 2835 East Carson Street Suite 210, Pittsburgh, 15203, USA", "2555 Smallman St Suite 301, Pittsburgh, PA 15222, USA", "40.45533960", "-79.98017410", "edu", "", "2014"], ["Single-Pedestrian Detection Aided by Two-Pedestrian Detection", "", "Member", "Member", "1322 N Inglewood Ave, Coffeyville, KS 67337, USA", "37.05826350", "-95.67914910", "edu", "", "2015"], ["Pyramid Center-Symmetric Local Binary/Trinary Patterns for Effective Pedestrian Detection", "", "Australian National University", "Australian National University", "Canberra ACT 0200, Australia", "-35.27769990", "149.11852700", "edu", "", "2010"], ["End-to-End People Detection in Crowded Scenes", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", "2016"], ["Person Re-identification Meets Image Search.", "", "University of Texas at San Antonio", "University of Texas at San Antonio", "UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA", "29.58333105", "-98.61944505", "edu", "", "2015"], ["Isotropic Granularity-tunable gradients partition (IGGP) descriptors for human detection", "", "Finland", "Finland", "Finland", "61.92411000", "25.74815110", "edu", "", "2010"], ["Human detection using local shape and Non-Redundant binary patterns", "Advanced Multimedia Research Lab, ICT Research Institute, School of Computer Science and Software Engineering, University of Wollongong, Australia", "University of Wollongong", "University of Wollongong", "University of Wollongong, Admin Road, Keiraville, Wollongong, NSW, 2500, Australia", "-34.40505545", "150.87834655", "edu", "", "2010"], ["Early Detection of Sudden Pedestrian Crossing for Safe Driving During Summer Nights", "Computer Vision and Pattern Recognition Laboratory, Keimyung University, Daegu, South Korea", "Keimyung University", "Keimyung University, Daegu, Korea", "South Korea, Daegu, Dalseo-gu, Dalgubeol-daero, 1095", "35.85505250", "128.48712690", "edu", "", "2017"], ["Improving pedestrian detection", "Department of Electrical and Computer Engineering, University of Canterbury, Christchurch, New Zealand", "University of Canterbury", "University of Canterbury", "University of Canterbury, Uni-Cycle, Ilam, Christchurch, Christchurch City, Canterbury, 8040, New Zealand/Aotearoa", "-43.52405280", "172.58030625", "edu", "", "2016"], ["Efficient Online Spatio-Temporal Filtering for Video Event Detection", "", "University of Michigan", "University of Michigan", "University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA", "42.29421420", "-83.71003894", "edu", "", "2014"], ["Monocular 3D Scene Modeling and Inference: Understanding Multi-Object Traffic Scenes", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2010"], ["Multi-pedestrian detection in crowded scenes: A global view", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "2012"], ["Disparity Statistics for Pedestrian Detection: Combining Appearance, Motion and Stereo", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2010"], ["Pedestrian Attribute Detection using CNN", "", "Stanford University", "Stanford University", "Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA", "37.43131385", "-122.16936535", "edu", "", "2016"], ["Scene-Specific Pedestrian Detection for Static Video Surveillance", "the Chinese University of Hong Kong, Hong Kong", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", "2013"], ["Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art", "", "Max Planck Institute for Intelligent Systems", "Max Planck Institute for Intelligent Systems", "Heisenbergstra\u00dfe 3, 70569 Stuttgart, Germany", "48.74689390", "9.08051410", "edu", "", "2017"], ["${\\rm C}^{4}$: A Real-Time Object Detection Framework", "iRobot Corporation, Bedford, MA, USA", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "2013"], ["Optimal spatio-temporal path discovery for video event detection", "School of EEE, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "2011"], ["SPID: Surveillance Pedestrian Image Dataset and Performance Evaluation for Pedestrian Detection", "", "Shanghai, China", "Shanghai, China", "Shanghai, China", "31.23039040", "121.47370210", "edu", "", "2016"], ["Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation", "", "Hefei University of Technology", "Hefei University of Technology", "\u5408\u80a5\u5de5\u4e1a\u5927\u5b66\uff08\u5c6f\u6eaa\u8def\u6821\u533a\uff09, 193\u53f7, \u5357\u4e00\u73af\u8def, \u822a\u8fd0\u5357\u6751, \u5305\u516c\u8857\u9053, \u5408\u80a5\u5e02\u533a, \u5408\u80a5\u5e02, \u5b89\u5fbd\u7701, 230009, \u4e2d\u56fd", "31.84691800", "117.29053367", "edu", "", "2016"], ["New features and insights for pedestrian detection", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2010"], ["Detection of Sudden Pedestrian Crossings for Driving Assistance Systems", "School of Electrical Information Engineering, Beihang University, Beijing, China", "Beihang University", "Beihang University", "\u5317\u4eac\u822a\u7a7a\u822a\u5929\u5927\u5b66, 37, \u5b66\u9662\u8def, \u4e94\u9053\u53e3, \u540e\u516b\u5bb6, \u6d77\u6dc0\u533a, 100083, \u4e2d\u56fd", "39.98083330", "116.34101249", "edu", "", "2012"], ["Efficient Boosted Weak Classifiers for Object Detection", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "2013"], ["Steerable second order intensity features for pedestrian detection", "School of Computer Engineering, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "2015"], ["Efficient object detection and segmentation with a cascaded Hough Forest ISM", "UMIC Research Centre, RWTH Aachen University, Germany", "RWTH Aachen University", "RWTH Aachen University", "RWTH Aachen, Mies-van-der-Rohe-Stra\u00dfe, K\u00f6nigsh\u00fcgel, Aachen-Mitte, Aachen, St\u00e4dteregion Aachen, Regierungsbezirk K\u00f6ln, Nordrhein-Westfalen, 52074, Deutschland", "50.77917030", "6.06728733", "edu", "", "2011"], ["Pedestrian detection using HOG, LUV and optical flow as features with AdaBoost as classifier", "Department of Computer Science, COMSATS Institute of Information Technology, Islamabad, Pakistan", "COMSATS Institute of Information Technology, Lahore", "COMSATS Institute of Information Technology", "COMSATS Institute of Information Technology, Ali Akbar Road, Dawood Residency, \u0628\u062d\u0631\u06cc\u06c1 \u0679\u0627\u0624\u0646\u202c\u200e, Lahore District, \u067e\u0646\u062c\u0627\u0628, 54700, \u200f\u067e\u0627\u06a9\u0633\u062a\u0627\u0646\u200e", "31.40063320", "74.21372960", "edu", "", "2016"], ["Human detection in video over large viewpoint changes", "", "OMRON Corporation, Kyoto, Japan", "Core Technology Center, OMRON Corporation, Kyoto, Japan", "Kyoto, Kyoto Prefecture, Japan", "35.01163630", "135.76802940", "company", "", "2010"], ["Pedestrian Detection by Feature Selected Self-Similarity Features", "National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, China", "University of Electronic Science and Technology of China", "University of Electronic Science and Technology of China", "Columbus, OH 43210, USA", "40.01419050", "-83.03091430", "edu", "", "2018"], ["CityPersons: A Diverse Dataset for Pedestrian Detection", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", "2017"], ["Estimation of Pedestrian Pose and Orientation Using on-Board Camera with Histograms of Oriented Gradients Features", "Institute of Industrial Science, The University of Tokyo, Meguro-ku, Japan", "Institute of Industrial Science", "Institute of Industrial Science", "\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240\uff1b\u897f\u4e8b\u696d\u6240, \u5b66\u5712\u897f\u5927\u901a\u308a, Onogawa housing complex, \u3064\u304f\u3070\u5e02, \u8328\u57ce\u770c, \u95a2\u6771\u5730\u65b9, 305-0051, \u65e5\u672c", "36.05238585", "140.11852361", "edu", "", "2016"], ["The Fastest Pedestrian Detector in the West", "", "University of California, San Diego", "University of California, San Diego", "UCSD, 9500, Gilman Drive, Sixth College, University City, San Diego, San Diego County, California, 92093, USA", "32.87935255", "-117.23110049", "edu", "", "2010"], ["A semiautomatic method for pedestrian ground truth generation in thermal infrared on-board videos", "School of Software Engineering, South China University of Technology, Guangzhou, China", "South China University of Technology", "South China University of Technology", "\u534e\u5357\u7406\u5de5\u5927\u5b66, \u5927\u5b66\u57ce\u4e2d\u73af\u4e1c\u8def, \u5e7f\u5dde\u5927\u5b66\u57ce, \u65b0\u9020, \u756a\u79ba\u533a (Panyu), \u5e7f\u5dde\u5e02, \u5e7f\u4e1c\u7701, 510006, \u4e2d\u56fd", "23.05020420", "113.39880323", "edu", "", "2015"], ["A study on occluded pedestrian detection based on block-based features and ensemble classifier", "School of Automation, Northwestern Polytechnical University, Xi'an, Shaanxi 710072, China", "Northwestern Polytechnical University", "Northwestern Polytechnical University", "\u897f\u5317\u5de5\u4e1a\u5927\u5b66 \u53cb\u8c0a\u6821\u533a, 127\u53f7, \u53cb\u8c0a\u897f\u8def, \u957f\u5b89\u8def, \u7891\u6797\u533a (Beilin), \u897f\u5b89\u5e02, \u9655\u897f\u7701, 710072, \u4e2d\u56fd", "34.24691520", "108.91061982", "edu", "", "2015"], ["Object class detection: A survey", "University of Alberta, Canada", "University of Alberta", "University of Alberta", "University of Alberta, 87 Avenue NW, University of Alberta, Edmonton, Alberta, T6G, Canada", "53.52385720", "-113.52282665", "edu", "", "2013"], ["Scalable Person Re-identification: A Benchmark", "", "University of Texas at San Antonio", "University of Texas at San Antonio", "UTSA, Paseo Principal, San Antonio, Bexar County, Texas, 78249-1620, USA", "29.58333105", "-98.61944505", "edu", "", "2015"], ["Dynamic management of a partial reconfigurable hardware architecture for pedestrian detection in regions of interest", "LE2I Laboratory. Univ. Bourgogne Franche Comté, F21000, Dijon, France", "LE2I Laboratory. Univ. Bourgogne Franche Comté, F21000, Dijon, France", "LE2I Laboratory. Univ. Bourgogne Franche Comté, F21000, Dijon, France", "UFR Sciences et Techniques, all\u00e9e Alain Savary, 21000 Dijon, France", "47.31256900", "5.07361200", "edu", "", "2017"], ["Approximation of feature pyramids in the DCT domain and its application to pedestrian detection", "Department of Electrical and Computer Engineering, Concordia University, Montreal, Quebec, Canada H3G 1M8", "Concordia University", "Concordia University", "Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA", "45.57022705", "-122.63709346", "edu", "", "2016"], ["UA-DETRAC: A New Benchmark and Protocol for Multi-Object Detection and Tracking", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "2015"], ["Visual People Detection \u2013 Different Models , Comparison and Discussion", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "2009"], ["Variant SemiBoost for Improving Human Detection in Application Scenes", "School of Computer Science and Engineering, South China University of Technology, Guangzhou, China", "South China University of Technology", "South China University of Technology", "\u534e\u5357\u7406\u5de5\u5927\u5b66, \u5927\u5b66\u57ce\u4e2d\u73af\u4e1c\u8def, \u5e7f\u5dde\u5927\u5b66\u57ce, \u65b0\u9020, \u756a\u79ba\u533a (Panyu), \u5e7f\u5dde\u5e02, \u5e7f\u4e1c\u7701, 510006, \u4e2d\u56fd", "23.05020420", "113.39880323", "edu", "", "2018"], ["Fast moving pedestrian detection based on motion segmentation and new motion features", "Institute of Computer Science III, University of Bonn, Bonn, Germany", "University of Bonn", "University of Bonn", "Rheinische Friedrich-Wilhelms-Universit\u00e4t Bonn, Arkadenhof, Bonn-Zentrum, Stadtbezirk Bonn, Bonn, Regierungsbezirk K\u00f6ln, Nordrhein-Westfalen, 53113, Deutschland", "50.73381240", "7.10224650", "edu", "", "2015"], ["Single-Pedestrian Detection Aided by Multi-pedestrian Detection", "", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", "2013"], ["Vehicle Detection Method Based on Edge Information and Local Transform Histogram", "", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "2013"], ["Quality-adaptive deep learning for pedestrian detection", "", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "2017"], ["Pedestrian detection and tracking using HOG and oriented-LBP features", "", "Shenzhen Institutes of Advanced Technology", "Shenzhen Institutes of Advanced Technology", "\u4e2d\u56fd\u79d1\u5b66\u9662\u6df1\u5733\u5148\u8fdb\u6280\u672f\u7814\u7a76\u9662, 1068, \u79d1\u7814\u8def, \u6df1\u5733\u5927\u5b66\u57ce, \u4e09\u5751\u6751, \u5357\u5c71\u533a, \u6df1\u5733\u5e02, \u5e7f\u4e1c\u7701, 518000, \u4e2d\u56fd", "22.59805605", "113.98533784", "edu", "", "2011"], ["Adapting an object detector by considering the worst case: A conservative approach", "Electrical and Computer Engineering Dept., University of Missouri, Columbia, MO, USA", "University of Missouri", "University of Missouri", "L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA", "38.92676100", "-92.29193783", "edu", "", "2011"], ["Partial Occlusion Handling in Pedestrian Detection With a Deep Model", "Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", "2016"], ["Learning and Exploiting Camera Geometry for Computer Vision", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", "2016"], ["Robust Multi-resolution Pedestrian Detection in Traffic Scenes", "", "Chinese Academy of Sciences", "Chinese Academy of Sciences", "\u4e2d\u56fd\u79d1\u5b66\u9662\u5fc3\u7406\u7814\u7a76\u6240, 16, \u6797\u8403\u8def, \u671d\u9633\u533a / Chaoyang, \u5317\u4eac\u5e02, 100101, \u4e2d\u56fd", "40.00447950", "116.37023800", "edu", "", "2013"], ["Local Co-Occurrence Selection via Partial Least Squares for Pedestrian Detection", "University at Buffalo, The State University of New York, Buffalo, NY, USA", "State University of New York, Buffalo", "University at Buffalo, The State University of New York, Buffalo, NY, USA", "Buffalo, NY 14260, USA", "43.00080930", "-78.78896970", "edu", "", "2017"], ["Survey of Pedestrian Detection for Advanced Driver Assistance Systems", "", "Member", "Member", "1322 N Inglewood Ave, Coffeyville, KS 67337, USA", "37.05826350", "-95.67914910", "edu", "", "2010"], ["Visualization of object image database by using logistic discriminant analysis", "National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568, Japan", "National Institute of Advanced Industrial Science and Technology", "National Institute of Advanced Industrial Science and Technology", "\u7523\u696d\u6280\u8853\u7dcf\u5408\u7814\u7a76\u6240\uff1b\u897f\u4e8b\u696d\u6240, \u5b66\u5712\u897f\u5927\u901a\u308a, Onogawa housing complex, \u3064\u304f\u3070\u5e02, \u8328\u57ce\u770c, \u95a2\u6771\u5730\u65b9, 305-0051, \u65e5\u672c", "36.05238585", "140.11852361", "edu", "", "2016"], ["Pedestrian detection with geometric context from a single image", "Beijing University of Posts and Telecommunications, Beijing, China", "Beijing University of Posts and Telecommunications", "Beijing University of Posts and Telecommunications", "\u5317\u4eac\u90ae\u7535\u5927\u5b66, \u897f\u571f\u57ce\u8def, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100082, \u4e2d\u56fd", "39.96014880", "116.35193921", "edu", "", "2011"], ["People perception from RGB-D cameras for mobile robots", "School of Electrical and Automation Engineering, Shanghai University, Shanghai, 200072 China", "Shanghai University", "Shanghai University", "\u4e0a\u6d77\u5927\u5b66, \u9526\u79cb\u8def, \u5927\u573a\u9547, \u5b9d\u5c71\u533a (Baoshan), \u4e0a\u6d77\u5e02, 201906, \u4e2d\u56fd", "31.32235655", "121.38400941", "edu", "", "2015"], ["Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters", "", "Carnegie Mellon University", "Carnegie Mellon University", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "2017"], ["Multi-part-detector for human detection", "School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China", "China", "China", "China", "35.86166000", "104.19539700", "edu", "", "2013"], ["Out of sight: a toolkit for tracking occluded human joint positions", "University of St Andrews, St Andrews, UK", "University of St Andrews", "University of St Andrews", "University of St Andrews, North Street, Albany Park Student accommodation, Carngour, St Andrews, Fife, Scotland, KY16 9AJ, UK", "56.34119840", "-2.79309380", "edu", "", "2016"], ["Fast Pedestrian Detection Based on the Selective Window Differential Filter", "School of Electronic and Informatics Engineering, Jiangsu University, Zhenjiang, China", "Jiangsu University", "Jiangsu University", "\u6c5f\u82cf\u5927\u5b66, 301, \u5b66\u5e9c\u8def, \u4eac\u53e3\u533a, \u8c61\u5c71\u8857\u9053, \u4eac\u53e3\u533a (Jingkou), \u9547\u6c5f\u5e02 / Zhenjiang, \u6c5f\u82cf\u7701, 212013, \u4e2d\u56fd", "32.20302965", "119.50968362", "edu", "", "2017"], ["On experimenting with pedestrian classification using neural network", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram - 695581, India", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram - 695581, India", "TDC, Network Systems and Technologies (NeST) Technopark, Thiruvananthapuram - 695581, India", "Park Centre, Technopark Campus, Thiruvananthapuram, Kerala 695581, India", "8.55809670", "76.88156050", "edu", "", "2011"], ["Synthesizing a Scene-Specific Pedestrian Detector and Pose Estimator for Static Video Surveillance", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Volvo Construction Equipment, G\u00f6thenburg, Sweden", "Gropeg\u00e5rdsgatan 11, 417 15 G\u00f6teborg, Sweden", "57.71720040", "11.92185580", "edu", "", "2018"], ["Leveraging RGB-D Data: Adaptive fusion and domain adaptation for object detection", "", "University of Freiburg", "Social Robotics Lab, University of Freiburg, Germany", "Fahnenbergplatz, 79085 Freiburg im Breisgau, Germany", "47.99354410", "7.84594960", "edu", "", "2012"], ["A Diverse Dataset for Pedestrian Detection", "", "Max Planck Institute for Informatics", "Max Planck Institute for Informatics", "MPII, E1 4, Campus, Universit\u00e4t, Sankt Johann, Bezirk Mitte, Saarbr\u00fccken, Regionalverband Saarbr\u00fccken, Saarland, 66123, Deutschland", "49.25795660", "7.04577417", "edu", "", ""], ["Exploiting Target Data to Learn Deep Convolutional Networks for Scene-Adapted Human Detection", "VIVA Research Laboratory, School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada", "University of Ottawa", "University of Ottawa", "University of Ottawa, 1, Stewart Street, Byward Market, Lowertown, Rideau-Vanier, Ottawa, Ontario, K1N 6N5, Canada", "45.42580475", "-75.68740118", "edu", "", "2018"], ["Integrating Orientation Cue With EOH-OLBP-Based Multilevel Features for Human Detection", "Research and Development Department, AnKe Smart City Technology Company Ltd., Shenzhen, China", "China", "China", "China", "35.86166000", "104.19539700", "edu", "", "2013"], ["Is pedestrian detection robust for surveillance?", "Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "2015"], ["MuseumVisitors: A dataset for pedestrian and group detection, gaze estimation and behavior understanding", "", "Columbia University", "Columbia University", "Columbia University Medical Center, 630, West 168th Street, Washington Heights, Manhattan, Manhattan Community Board 12, New York County, NYC, New York, 10031, USA", "40.84198360", "-73.94368971", "edu", "", "2015"], ["Pedestrian Detection in Video Images via Error Correcting Output Code Classification of Manifold Subclasses", "College of Engineering, Graduate University of Chinese Academy of Sciences, Beijing, China", "Graduate University of Chinese Academy of Sciences", "College of Engineering, Graduate University of Chinese Academy of Sciences, Beijing, China", "China, Beijing, Haidian, Zhongguancun South 1st Alley, \u4e2d\u5173\u6751\u5357\u4e00\u6761", "39.98177000", "116.33008600", "edu", "", "2012"], ["A discriminative deep model for pedestrian detection with occlusion handling", "Department of Electronic Engineering, The Chinese University of Hong Kong", "Chinese University of Hong Kong", "The Chinese University of Hong Kong", "\u4e2d\u5927 CUHK, NA\u68af New Asia Stairs, \u99ac\u6599\u6c34 Ma Liu Shui, \u4e5d\u809a\u6751 Kau To Village, \u6c99\u7530\u5340 Sha Tin District, \u65b0\u754c New Territories, HK, DD193 1191, \u4e2d\u56fd", "22.42031295", "114.20788644", "edu", "", "2012"], ["Pedestrian Detection: An Evaluation of the State of the Art", "MPI Informatics, Saabrucken", "Caltech, Pasadena", "Caltech, Pasadena", "1200 E California Blvd, Pasadena, CA 91125, USA", "34.13765760", "-118.12526900", "edu", "", "2012"], ["Virtual and Real World Adaptation for Pedestrian Detection", "", "Member", "Member", "1322 N Inglewood Ave, Coffeyville, KS 67337, USA", "37.05826350", "-95.67914910", "edu", "", "2013"], ["Vision-based pedestrian monitoring at intersections including behavior & crossing count", "Electrical and Computer Engineering Department, University of Nevada, Las Vegas, 89154, USA", "University of Nevada", "University of Nevada", "Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA", "39.54694490", "-119.81346566", "edu", "", "2016"], ["Gradient Response Maps for Real-Time Detection of Textureless Objects", "Technische Universitat Muenchen, Garching bie Muenchen", "Technische Universitat Muenchen, Garching bie Muenchen", "Technische Universitat Muenchen, Garching bie Muenchen", "Boltzmannstra\u00dfe 15, 85748 Garching bei M\u00fcnchen, Germany", "48.26480530", "11.66886010", "edu", "", "2012"], ["Pedestrian Detection Based on Sparse and Low-Rank Matrix Decomposition", "", "China", "China", "China", "35.86166000", "104.19539700", "edu", "", "2014"], ["Pedestrian detection in digital videos using committee of motion feature extractors", "Universidade de Pernambuco(UPE), Recife, Brazil, Instituto Federal de Pernambuco (IFPE), Palmares, Brazil", "Laboratorio de Comunicaciones e ICYTE y Departamento Informática, Facultad de Ingeniería, Universidad Nacional de Mar del Plata (UNMDP), Mar del Plata, Argentina", "Laboratorio de Comunicaciones e ICYTE y Departamento Informática, Facultad de Ingeniería, Universidad Nacional de Mar del Plata (UNMDP), Mar del Plata, Argentina", "De\u00e1n Funes 3350, B7602AYL Mar del Plata, Buenos Aires, Argentina", "-38.00537090", "-57.57090000", "edu", "", "2017"], ["Fusion of Depth and Vision Information for Human Detection \u22c6", "", "Wayne State University", "Wayne State University", "Parking Structure 3, East Warren Avenue, New Center, Detroit, Wayne County, Michigan, 48236, USA", "42.35775700", "-83.06286711", "edu", "", "2013"], ["Spatial-Temporal Granularity-Tunable Gradients Partition (STGGP) Descriptors for Human Detection", "", "University of Oulu", "University of Oulu", "Oulun yliopisto, Biologintie, Linnanmaa, Oulu, Oulun seutukunta, Pohjois-Pohjanmaa, Pohjois-Suomen aluehallintovirasto, Pohjois-Suomi, Manner-Suomi, 90540, Suomi", "65.05921570", "25.46632601", "edu", "", "2010"], ["Context-aware pedestrian detection especially for small-sized instances with Deconvolution Integrated Faster RCNN (DIF R-CNN)", "Division of Electronical Engineering, Hanyang University, Ansan, Republic of Korea", "Hanyang University", "Hanyang University", "\ud55c\uc591\ub300, 206, \uc655\uc2ed\ub9ac\ub85c, \uc0ac\uadfc\ub3d9, \uc131\ub3d9\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 04763, \ub300\ud55c\ubbfc\uad6d", "37.55572710", "127.04366420", "edu", "", "2018"], ["Scan window based pedestrian recognition methods improvement by search space and scale reduction", "Image Processing and Pattern Recognition Group, Computer Science Department, Technical University of Cluj-Napoca, Romania", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "2014"], ["Integrating Perception and Cognition for AGI", "", "Carnegie Mellon University", "Carnegie Mellon University", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "2011"], ["Pedestrian detection and direction estimation by cascade detector with multi-classifiers utilizing feature interaction descriptor", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "Toyota Central R&D Labs, Japan", "Toyota Central R&D Labs., Inc., Nagakute, Aichi 480-1192, Japan", "41\u756a\uff11 Yokomichi, Nagakute, Aichi Prefecture 480-1192, Japan", "35.16898430", "137.05429210", "company", "", "2011"], ["Integrated Pedestrian and Direction Classification Using a Random Decision Forest", "", "University of Auckland", "The University of Auckland, Auckland, New Zealand", "Auckland 1010, New Zealand", "-36.85233780", "174.76910730", "edu", "", "2013"], ["Co-occurrence flow for pedestrian detection", "", "University of Cambridge", "University of Cambridge", "Clifford Allbutt Lecture Theatre, Robinson Way, Romsey, Cambridge, Cambridgeshire, East of England, England, CB2 0QH, UK", "52.17638955", "0.14308882", "edu", "", "2011"], ["Enabling Pedestrian Safety using Computer Vision Techniques: A Case Study of the 2018 Uber Inc. Self-driving Car Crash", "", "Texas A&M University", "Texas A&M University", "Texas A&M University, Horticulture Street, Park West, College Station, Brazos County, Texas, 77841, USA", "30.61083650", "-96.35212800", "edu", "", "2018"], ["Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice", "", "York University", "York University", "York University, Keele Campus, Campus Walk, North York, Toronto, Ontario, M3J 2S5, Canada", "43.77439110", "-79.50481085", "edu", "", "2018"], ["Adaptation for Person Detection", "", "Duke University", "Duke University", "Nasher Museum of Art, 2001, Campus Drive, Burch Avenue, Durham, Durham County, North Carolina, 27705, USA", "35.99905220", "-78.92906290", "edu", "", "2016"], ["Pedestrian Detection with Semantic Regions of Interest", "", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences", "University of Chinese Academy of Sciences, UCAS, Yuquanlu, \u7389\u6cc9\u8def, \u7530\u6751, \u6d77\u6dc0\u533a, 100049, \u4e2d\u56fd", "39.90828040", "116.24585270", "edu", "", "2017"], ["Human Detection by Quadratic Classification on Subspace of Extended Histogram of Gradients", "School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "2014"], ["Part-Based Pedestrian Detection and Feature-Based Tracking for Driver Assistance: Real-Time, Robust Algorithms, and Evaluation", "", "Member", "Member", "1322 N Inglewood Ave, Coffeyville, KS 67337, USA", "37.05826350", "-95.67914910", "edu", "", "2013"], ["Intensity self similarity features for pedestrian detection in Far-Infrared images", "Laboratoire d'Informatique, de Traitement de l'Information et des Systemes, INSA Rouen, Avenue de l'Universite, 76800, Saint-Etienne-du-Rouvray, France", "INSA Rouen, France", "Laboratoire d'Informatique, de Traitement de l'Information et des Systemes, INSA Rouen, Avenue de l'Universite, 76800, Saint-Etienne-du-Rouvray, France", "685 Avenue de l'Universit\u00e9, 76800 Saint-\u00c9tienne-du-Rouvray, France", "49.38497570", "1.06832570", "edu", "", "2012"]]}
\ No newline at end of file |