{"id": "f72f6a45ee240cc99296a287ff725aaa7e7ebb35", "paper": {"paperId": "f72f6a45ee240cc99296a287ff725aaa7e7ebb35", "key": "caltech_pedestrians", "title": "Pedestrian Detection: An Evaluation of the State of the Art", "journal": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "address": "California Institute of Technology", "country": "United States", "address_type": "edu", "lat": "34.13710185", "lng": "-118.12527487", "pdf_link": "http://vision.caltech.edu/Image_Datasets/CaltechPedestrians/files/PAMI12pedestrians.pdf", "report_link": "papers/f72f6a45ee240cc99296a287ff725aaa7e7ebb35.html", "citation_count": 999, "citations_geocoded": 499, "citations_unknown": 500, "citations_empty": 71, "citations_pdf": 541, "citations_doi": 464, "name": "Caltech Pedestrians"}, "address": ["California Institute of Technology", "California Institute of Technology", "California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA", "34.13710185", "-118.12527487", "edu", "", "United States"], "citations": [["Vision-Based Parking-Slot Detection: A DCNN-Based Approach and a Large-Scale Benchmark Dataset", "School of Software Engineering, Tongji University, Shanghai, China", "Tongji University", "Tongji University", "\u540c\u6d4e\u5927\u5b66, 1239, \u56db\u5e73\u8def, \u6c5f\u6e7e, \u8679\u53e3\u533a, \u4e0a\u6d77\u5e02, 200092, \u4e2d\u56fd", "31.28473925", "121.49694909", "edu", "", "China", "2018"], ["Parsing occluded people by flexible compositions", "", "University of California", "University of California", "Berkeley, CA, USA", "37.87189920", "-122.25853990", "edu", "", "United States", "2015"], ["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", "", "United States", "2017"], ["Occlusion Handling Human Detection with Refocused Images", "National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan", "National Institute of Advanced Industrial Science and Technology (AIST), Japan", "National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan", "1 Chome-1-1 Umezono, Tsukuba, Ibaraki Prefecture 305-8560, Japan", "36.06146340", "140.13389070", "edu", "", "Japan", "2018"], ["Vision-Based Intersection Monitoring : Behavior Analysis & Safety Issues", "", "University of Nevada", "University of Nevada", "Orange 1, Evans Avenue, Reno, Washoe County, Nevada, 89557, USA", "39.54694490", "-119.81346566", "edu", "", "United States", "2017"], ["Real-Time Detection and Tracking of Multiple Humans from High Bird's-Eye Views in the Visual and Infrared Spectrum", "", "ETH Zurich", "ETH Zurich", "R\u00e4mistrasse 101, 8092 Z\u00fcrich, Switzerland", "47.37631300", "8.54766990", "edu", "", "Switzerland", "2016"], ["Internal-to-internal transition method for consecutive hierarchical template matching", "", "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", "", "South Korea", "2014"], ["Object detection by labeling superpixels", "", "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", "", "China", "2015"], ["An open benchmark implementation for multi-CPU multi-GPU pedestrian detection in automotive systems", "Universitat Polit\u00e8cnica de Catalunya", "Universitat Polit\u00e8cnica de Catalunya", "Universitat Polit\u00e8cnica de Catalunya", "Campus Nord, Carrer de Jordi Girona, 1, 3, 08034 Barcelona, Spain", "41.38800400", "2.11328040", "edu", "", "Spain", "2017"], ["Pedestrian Detection Based on Incremental Learning", "", "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", "", "China", "2013"], ["How do you develop a face detector for the unconstrained environment?", "The University of Queensland, Brisbane, Australia", "University of Queensland", "University of Queensland", "University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia", "-27.49741805", "153.01316956", "edu", "", "Australia", "2016"], ["Pedestrian detection in digital videos using committee of motion feature extractors", "Universidade de Pernambuco(UPE), Recife, Brazil, Instituto Federal de Pernambuco (IFPE), Palmares, Brazil", "Universidade de Pernambuco, Brazil", "Universidade de Pernambuco(UPE), Recife, Brazil, Instituto Federal de Pernambuco (IFPE), Palmares, Brazil", "Palmares - State of Pernambuco, 55540-000, Brazil", "-8.66529440", "-35.56880500", "edu", "", "Brazil", "2017"], ["Online Motion Agreement Tracking", "", "Boston University", "Boston University", "BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA", "42.35042530", "-71.10056114", "edu", "", "United States", "2013"], ["Multi-Level Common Space Learning for Person Re-Identification", "National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan, China", "Huazhong University of Science and Technology", "Huazhong University of Science and Technology", "\u534e\u4e2d\u5927, \u73de\u55bb\u8def, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a, \u5173\u4e1c\u8857\u9053, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a\uff08\u6258\u7ba1\uff09, \u6d2a\u5c71\u533a (Hongshan), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430074, \u4e2d\u56fd", "30.50975370", "114.40628810", "edu", "", "China", "2018"], ["Pedestrian detection from salient regions", "School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, 100190, China", "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", "", "China", "2014"], ["TabletGaze : Dataset and Algorithm for Unconstrained Appearance-based Gaze Estimation in Mobile Tablets", "", "Rice University", "Rice University", "Rice University, Stockton Drive, Houston, Harris County, Texas, 77005-1890, USA", "29.71679145", "-95.40478113", "edu", "", "United States", "2015"], ["Multiple-Kernel, Multiple-Instance Similarity Features for Efficient Visual Object Detection", "Department of Electronic and Information Engineering, Center for Signal Processing, The Hong Kong Polytechnic University, Hong Kong", "Hong Kong Polytechnic University", "Hong Kong Polytechnic University", "hong kong, 11, \u80b2\u624d\u9053 Yuk Choi Road, \u5c16\u6c99\u5480 Tsim Sha Tsui, \u6cb9\u5c16\u65fa\u5340 Yau Tsim Mong District, \u4e5d\u9f8d Kowloon, HK, 00000, \u4e2d\u56fd", "22.30457200", "114.17976285", "edu", "", "China", "2013"], ["A moving target detection algorithm based on BING objectness and background estimation", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "Xihu, Hangzhou, Zhejiang, China, 310007", "30.23578590", "120.14053930", "edu", "", "China", "2017"], ["Efficient Detection for Spatially Local Coding", "", "University of British Columbia", "University of British Columbia", "University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada", "49.25839375", "-123.24658161", "edu", "", "Canada", "2014"], ["Pedestrian detection via PCA filters based convolutional channel features", "School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China", "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", "", "China", "2015"], ["Improving Object Tracking by Adapting Detectors", "", "Delft University of Technology", "Delft University of Technology", "TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland", "51.99882735", "4.37396037", "edu", "", "Netherlands", "2014"], ["Detecting Surgical Tools by Modelling Local Appearance and Global Shape", "Medicis team. INSERM U1099, Universit\u00e9 de Rennes 1 LTSI, Rennes, France", "Medicis team. INSERM U1099, Universit\u00e9 de Rennes 1 LTSI, Rennes, France", "Medicis team. INSERM U1099, Universit\u00e9 de Rennes 1 LTSI, Rennes, France", "2 Avenue du Professeur L\u00e9on Bernard, 35043 Rennes, France", "48.11746700", "-1.69615390", "edu", "", "France", "2015"], ["Empowering Low-Latency Applications Through a Serverless Edge Computing Architecture", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy", "5 Politecnico di Milano, Via Giuseppe Ponzio, 34, 20133 Milano MI, Italy", "45.47866980", "9.23242090", "edu", "", "Italy", "2017"], ["Multi-player detection in soccer broadcast videos using a blob-guided particle swarm optimization method", "Department of Photogrammetry and Remote Sensing, K.N. Toosi University of Technology, Tehran, Iran", "K.N. Toosi University of Technology", "K.N. Toosi University of Technology", "\u062f\u0627\u0646\u0634\u06a9\u062f\u0647 \u0645\u0647\u0646\u062f\u0633\u06cc \u0639\u0645\u0631\u0627\u0646 \u0648 \u0646\u0642\u0634\u0647 \u0628\u0631\u062f\u0627\u0631\u06cc, \u0648\u0644\u06cc \u0639\u0635\u0631, \u06a9\u0627\u0648\u0648\u0633\u06cc\u0647, \u0645\u0646\u0637\u0642\u0647 \u06f3 \u0634\u0647\u0631 \u062a\u0647\u0631\u0627\u0646, \u062a\u062c\u0631\u06cc\u0634, \u0628\u062e\u0634 \u0631\u0648\u062f\u0628\u0627\u0631\u0642\u0635\u0631\u0627\u0646, \u0634\u0647\u0631\u0633\u062a\u0627\u0646 \u0634\u0645\u06cc\u0631\u0627\u0646\u0627\u062a, \u0627\u0633\u062a\u0627\u0646 \u062a\u0647\u0631\u0627\u0646, 1968653111, \u200f\u0627\u06cc\u0631\u0627\u0646\u200e", "35.76427925", "51.40970276", "edu", "", "Iran", "2016"], ["Transferring a generic pedestrian detector towards specific scenes", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2012"], ["A Framework for Applying Point Clouds Grabbed by Multi-Beam LIDAR in Perceiving the Driving Environment", "", "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", "", "China", "2015"], ["Build a Robust Learning Feature Descriptor by Using a New Image Visualization Method for Indoor Scenario Recognition", "", "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", "", "China", "2017"], ["A scalable architecture for multi-class visual object detection", "Toshiba, Japan", "The Pennsylvania State University", "The Pennsylvania State University", "Old Main, State College, PA 16801, USA", "40.79821330", "-77.85990840", "edu", "", "United States", "2015"], ["What makes an on-road object important?", "Computer Vision and Robotics Research Laboratory, University of California San Diego, United States of America", "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", "", "United States", "2016"], ["Efficient and robust indoor people detection based on RGB-D camera", "Key Laboratory of Intelligent Computation & Signal Processing, Ministry of Education, Anhui University, Hefei, China", "Anhui University", "Anhui University", "\u5b89\u5fbd\u5927\u5b66(\u78ec\u82d1\u6821\u533a), 111, \u4e5d\u9f99\u8def, \u5f18\u6cf0\u82d1, \u5408\u80a5\u56fd\u5bb6\u7ea7\u7ecf\u6d4e\u6280\u672f\u5f00\u53d1\u533a, \u8299\u84c9\u793e\u533a, \u5408\u80a5\u7ecf\u6d4e\u6280\u672f\u5f00\u53d1\u533a, \u5408\u80a5\u5e02\u533a, \u5408\u80a5\u5e02, \u5b89\u5fbd\u7701, 230601, \u4e2d\u56fd", "31.76909325", "117.17795091", "edu", "", "China", "2017"], ["Learning to Filter Object Detections", "", "Microsoft", "Microsoft Corporation, Redmond, WA, USA", "One Microsoft Way, Redmond, WA 98052, USA", "47.64233180", "-122.13693020", "company", "", "United States", "2017"], ["Detangling People: Individuating Multiple Close People and Their Body Parts via Region Assembly", "", "University of Texas at Austin", "University of Texas at Austin", "University of Texas at Austin, 1, East 23rd Street, The Drag, Austin, Travis County, Texas, 78712, USA", "30.28415100", "-97.73195598", "edu", "", "United States", "2017"], ["Fused Discriminative Metric Learning for Low Resolution Pedestrian Detection", "IAIR, Xi'an Jiaotong University, China", "Xi'an Jiaotong University", "Xi'an Jiaotong University", "\u897f\u5b89\u4ea4\u901a\u5927\u5b66\u5174\u5e86\u6821\u533a, \u6587\u6cbb\u8def, \u4e50\u5c45\u573a, \u7891\u6797\u533a (Beilin), \u897f\u5b89\u5e02, \u9655\u897f\u7701, 710048, \u4e2d\u56fd", "34.24749490", "108.97898751", "edu", "", "China", "2018"], ["Analyzing Headlight Flicker Patterns for Improving the Pedestrian Detectability from a Driver", "Institutes of Innovation for Future Society, Nagoya University, Aichi, Japan", "Nagoya University", "Nagoya University", "SuperDARN (Hokkaido West), \u592a\u8f9b\u7b2c1\u652f\u7dda\u6797\u9053, \u9678\u5225\u753a, \u8db3\u5bc4\u90e1, \u5341\u52dd\u7dcf\u5408\u632f\u8208\u5c40, \u5317\u6d77\u9053, \u5317\u6d77\u9053\u5730\u65b9, \u65e5\u672c", "43.53750985", "143.60768225", "edu", "", "Japan", "2018"], ["ANALY\u0301ZA POHYBU OSOB STACIONA\u0301RNI\u0301 KAMEROU ANALYSIS OF MOTION OF PEOPLE BY A STATIONARY CAMERA", "", "Brno University of Technology", "Brno University of Technology", "1 548 Anton\u00ednsk\u00e1 Brno-st\u0159ed Brno \u010cesk\u00e1 republika, 601 90, Czechia", "49.20172000", "16.60331680", "edu", "", "Czech Republic", "2014"], ["Pedestrian Detection Using Regional Proposal Network with Feature Fusion", "Key Lab of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, P. R. China", "Dalian University", "Key Lab of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian, P. R. China", "Jinzhou, Dalian, China", "39.10041000", "121.82193200", "edu", "", "China", "2018"], ["MIO-TCD: A New Benchmark Dataset for Vehicle Classification and Localization", "Systems Design Engineering Department, University of Waterloo, Waterloo, Canada", "University of Waterloo", "University of Waterloo", "University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada", "43.47061295", "-80.54724732", "edu", "", "Canada", "2018"], ["Multispectral Deep Neural Networks for Pedestrian Detection", "", "Rutgers University", "Rutgers University", "Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA", "40.47913175", "-74.43168868", "edu", "", "United States", "2016"], ["Learning a multiview part-based model in virtual world for pedestrian detection", "Computer Vision Center, Autonomous University of Barcelona, Edifici O, 08193 Bellaterra, Barcelona, Spain", "Autonomous University of Barcelona", "Computer Vision Center, Autonomous University of Barcelona, Edifici O, 08193 Bellaterra, Barcelona, Spain", "Campus UAB, Edifici O, s/n, 08193 Cerdanyola del Vall\u00e8s, Barcelona, Spain", "41.50089570", "2.11155300", "edu", "", "Spain", "2013"], ["Evaluation of stacked autoencoders for pedestrian detection", "Escuela de Ingeníeria Informática, Universidad Católica de Temuco, Temuco, Chile", "Universidad Cat\u00f2lica de Temuco, Temuco, Chile", "Escuela de Ingeníeria Informática, Universidad Católica de Temuco, Temuco, Chile", "Temuco, Araucania, Chile", "-38.73590180", "-72.59037390", "edu", "", "Chile", "2016"], ["Fast multi-feature pedestrian detection algorithm based on histogram of oriented gradient using discrete wavelet transform", "Department of Computer Engineering, SunMoon University, Asan, South Korea", "Automotive IT Platform Research Team, ETRI, Daegu, South Korea", "Automotive IT Platform Research Team, ETRI, Daegu, South Korea", "1110-6 Oryong-dong, Buk-gu, Kwangju, South Korea", "35.22537080", "126.84618340", "company", "", "South Korea", "2015"], ["Density Enhancement-Based Long-Range Pedestrian Detection Using 3-D Range Data", "Tsinghua University, Beijing, China", "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", "", "China", "2016"], ["Fast visual people tracking using a feature-based people detector", "LSIIT, Strasbourg University - CNRS - INSA, Strasbourg, France", "Strasbourg University - CNRS - INSA", "LSIIT, Strasbourg University - CNRS - INSA, Strasbourg, France", "24 Boulevard de la Victoire, 67000 Strasbourg, France", "48.58217470", "7.76506760", "edu", "", "France", "2011"], ["Semantic Channels for Fast Pedestrian Detection", "", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2016"], ["Counting pedestrians with a zenithal arrangement of depth cameras", "CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Quer\u00e9taro, Mexico", "CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Quer\u00e9taro, Mexico", "CICATA Quer\u00e9taro, Instituto Polit\u00e9cnico Nacional, Quer\u00e9taro, Mexico", "Cerro Blanco 141, Colinas del Cimatario, 76090 Santiago de Quer\u00e9taro, Qro., Mexico", "20.57408800", "-100.37062820", "edu", "", "Mexico", "2015"], ["Fast Deformable Model for Pedestrian Detection with Haar-like features", "School of Electrical and Data Engineering, FEIT, University of Technology Sydney, Australia", "University of Technology Sydney", "University of Technology Sydney", "University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia", "-33.88096510", "151.20107299", "edu", "", "Australia", "2017"], ["RGB-D and laser data fusion-based human detection and tracking for socially aware robot navigation framework", "University of Brunei Darussalam, The More-Than-One Robotics Laboratory, Brunei Darussalam", "University of Brunei Darussalam", "University of Brunei Darussalam, Faculty of Science, Brunei Darussalam", "Universiti Brunei Darussalam, Brunei", "4.97542740", "114.89602470", "edu", "", "Brunei", "2015"], ["Online Discriminative Structured Output SVM Learning for Multi-Target Tracking", "University of Chinese Academy of Sciences, Beijing, China", "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", "", "China", "2014"], ["Design and performance analysis of an IEEE 802.15.4 V2P pedestrian protection system", "Communication Networks Institute (CNI) Dortmund University of Technology, Germany", "Communication Networks Institute (CNI) Dortmund University of Technology", "Communication Networks Institute (CNI) Dortmund University of Technology, Germany", "Otto-Hahn-Stra\u00dfe 6, 44227 Dortmund, Germany", "51.49158450", "7.41178040", "edu", "", "Germany", "2013"], ["Micro-Expression Spotting: A Benchmark", "", "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", "", "Finland", "2017"], ["Pedestrian detection at 100 frames per second", "", "Katholieke Universiteit Leuven", "Katholieke Universiteit Leuven", "Laboratorium voor Bos, natuur en landschap, 102, Vital Decosterstraat, Sint-Maartensdal, Leuven, Vlaams-Brabant, Vlaanderen, 3000, Belgi\u00eb / Belgique / Belgien", "50.88306860", "4.70195030", "edu", "", "Belgium", "2012"], ["Performance of haar and LBP features in cascade classifiers to whiteflies detection and counting", "School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom", "Queen Mary University of London", "Queen Mary University of London", "Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK", "51.52472720", "-0.03931035", "edu", "", "United Kingdom", "2017"], ["How to reach top accuracy for a visual pedestrian warning system from a car?", "KULeuven, EAVISE", "KULeuven, EAVISE", "KULeuven, EAVISE", "Oude Markt 13, 3000 Leuven, Belgium", "50.87795450", "4.70029530", "edu", "", "Belgium", "2016"], ["CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes", "", "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", "", "China", "2018"], ["Graph mining for object tracking in videos", "Laboratoire Hubert Curien, UMR CNRS 5516, Universit\u00e9 de Lyon, Universit\u00e9 Jean Monnet de Saint-Etienne, Saint-Etienne, France", "Universit\u00e9 Jean Monnet de Saint-Etienne, France", "Laboratoire Hubert Curien, UMR CNRS 5516, Universit\u00e9 de Lyon, Universit\u00e9 Jean Monnet de Saint-Etienne, Saint-Etienne, France", "10 Rue Tr\u00e9filerie, 42100 Saint-\u00c9tienne, France", "45.42462200", "4.39298500", "edu", "", "France", "2012"], ["Improving HOG with Image Segmentation: Application to Human Detection", "", "University of Amsterdam", "University of Amsterdam", "Institute for Logic, Language and Computation (ILLC), 107, Science Park, Oost-Watergraafsmeer, Amsterdam, Oost, Amsterdam, Noord-Holland, Nederland, 1098XG, Nederland", "52.35536550", "4.95016440", "edu", "", "Netherlands", "2012"], ["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", "", "Germany", "2017"], ["AWStream: adaptive wide-area streaming analytics", "UC Berkeley", "University of California, Berkeley", "University of California, Berkeley", "Berkeley Art Museum and Pacific Film Archive, Bancroft Way, Southside, Berkeley, Alameda County, California, 94720-1076, USA", "37.86871260", "-122.25586815", "edu", "", "United States", "2018"], ["Object Detection with Active Sample Harvesting", "", "EPFL", "EPFL", "Route Cantonale, 1015 Lausanne, Switzerland", "46.51905570", "6.56675760", "edu", "", "Switzerland", "2017"], ["Supervised Local High-Order Differential Channel Feature Learning for Pedestrian Detection", "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", "", "China", "2016"], ["Float Cascade Method for Pedestrian Detection", "", "Anhui University", "Anhui University", "\u5b89\u5fbd\u5927\u5b66(\u78ec\u82d1\u6821\u533a), 111, \u4e5d\u9f99\u8def, \u5f18\u6cf0\u82d1, \u5408\u80a5\u56fd\u5bb6\u7ea7\u7ecf\u6d4e\u6280\u672f\u5f00\u53d1\u533a, \u8299\u84c9\u793e\u533a, \u5408\u80a5\u7ecf\u6d4e\u6280\u672f\u5f00\u53d1\u533a, \u5408\u80a5\u5e02\u533a, \u5408\u80a5\u5e02, \u5b89\u5fbd\u7701, 230601, \u4e2d\u56fd", "31.76909325", "117.17795091", "edu", "", "China", "2012"], ["Learning appearance models for road detection", "NICTA", "NICTA", "NICTA", "1111 E Touhy Ave #400, Des Plaines, IL 60018, USA", "42.00877410", "-87.89585490", "edu", "", "United States", "2013"], ["A network shaped cascade classifier based on potential functions for pedestrian detection", "Science and Technology on Aircraft Control Laboratory, Beihang University, Beijing, 100191 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", "", "China", "2014"], ["Multi-Pedestrian Detection from Effective Proposal in Crowd Scene", "State Key Laboratory of Software Engineering, School of Computer, Wuhan University, China and Collaborative Innovation Center of Geospatial Technology, Wuhan University, China and National Enginee ...", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2016"], ["A Philosophy for Developing Trust in Self \u2010 Driving Cars", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2015"], ["Fast Head-Shoulder Proposal for Scare-Aware Pedestrian Detection", "Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom", "Imperial College London", "Imperial College London", "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "51.49887085", "-0.17560797", "edu", "", "United Kingdom", "2017"], ["Deep Learning Strong Parts for Pedestrian Detection", "", "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", "", "China", "2015"], ["Ground truth annotation of traffic video data", "ITeam, Universitat Polit\u00e8cnica de Val\u00e8ncia, Valencia, Spain", "ITeam, Universitat Polit\u00e8cnica de Val\u00e8ncia, Valencia, Spain", "ITeam, Universitat Polit\u00e8cnica de Val\u00e8ncia, Valencia, Spain", "Cam\u00ed de Vera, s/n Edificio 8G, Planta 4\u00aa, 46022 Val\u00e8ncia, Spain", "39.47844400", "-0.33375450", "edu", "", "Spain", "2013"], ["Beyond Sliding Windows: Saliency Prior Based Random Partition for Fast Pedestrian Detection", "School of Logistics, Engineering in Wuhan University of Technology, Wuhan, China", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2016"], ["Real-time Pedestrian and Vehicle Detection for Autonomous Driving", "Shenzhen Institutes of Advanced Technology, The Chinese University of Hong Kong, Chinese Academy of Science, Shenzhen, 518055, China", "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", "", "China", "2018"], ["Robust tracking of articulated human movements through Component-Based Multiple Instance Learning with particle filtering", "", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "United States", "2014"], ["Pedestrian Detection from Low Resolution Public Cameras in the Wild", "Department of Telecommunication, Brno University of Technology, Czech Republic", "Brno University of Technology", "Brno University of Technology", "1 548 Anton\u00ednsk\u00e1 Brno-st\u0159ed Brno \u010cesk\u00e1 republika, 601 90, Czechia", "49.20172000", "16.60331680", "edu", "", "Czech Republic", "2018"], ["The Fastest Deformable Part Model 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", "", "China", "2014"], ["Partially occluded object detection by finding the visible features and parts", "Purdue University", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "United States", "2015"], ["Aggregating Deep Convolutional Feature Maps for Insulator Detection in Infrared Images", "School of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China", "North China Electric Power University", "North China Electric Power University", "\u534e\u5317\u7535\u529b\u5927\u5b66, \u6c38\u534e\u5317\u5927\u8857, \u83b2\u6c60\u533a, \u4fdd\u5b9a\u5e02, \u83b2\u6c60\u533a (Lianchi), \u4fdd\u5b9a\u5e02, \u6cb3\u5317\u7701, 071000, \u4e2d\u56fd", "38.87604460", "115.49738730", "edu", "", "China", "2017"], ["${\\rm C}^{4}$: A Real-Time Object Detection Framework", "iRobot Corporation, Bedford, MA, USA", "iRobot Corporation, Bedford, MA, USA", "iRobot Corporation, Bedford, MA, USA", "8 Crosby Dr, Bedford, MA 01730, USA", "42.50450780", "-71.24421490", "company", "", "United States", "2013"], ["Camera based pedestrian detection for railway driver support systems", "Kentkart \u0130zmir, T\u00dcRK\u0130YE", "Kentkart \u0130zmir, T\u00dcRK\u0130YE", "Kentkart \u0130zmir, T\u00dcRK\u0130YE", "Kahramanlar Mahallesi, M\u00fcrselpa\u015fa Blv. No:163, 35230 Konak/\u0130zmir, Turkey", "38.42486480", "27.14912080", "edu", "", "Turkey", "2018"], ["Simultaneous detection of pedestrians, pose, and the camera viewpoint from 3D models", "School of Computer Science, Kookmin University, Seoul, Korea", "Kookmin University", "Kookmin University", "\uad6d\ubbfc\ub300\ud559\uad50\uc55e, \uc815\ub989\ub85c, \uc815\ub9892\ub3d9, \uc815\ub989\ub3d9, \uc131\ubd81\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 02708, \ub300\ud55c\ubbfc\uad6d", "37.61075540", "126.99466350", "edu", "", "South Korea", "2015"], ["A real-time cascade pedestrian detection based on heterogeneous features", "", "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", "", "United States", "2015"], ["Crowd count in low resolution surveillance video using head detector and color based segementation for disaster management", "Thiagarajar College of Engineering, Madurai, TN 625015 India", "Thiagarajar College of Engineering, India", "Thiagarajar College of Engineering, Madurai, TN 625015 India", "GST Road, Thiruparankundram, Tamil Nadu 625015, India", "9.88288390", "78.08252960", "edu", "", "India", "2015"], ["Motion classification of pedestrian walking behaviors on the sidewalk", "Department of Mechanical Engineering, Ajou University, Suwon, Korea", "Ajou University", "Ajou University", "\uc544\uc8fc\ub300\ud559\uad50, \uc131\ud638\ub300\uad50, \uc774\uc758\ub3d9, \uc601\ud1b5\uad6c, \uc218\uc6d0\uc2dc, \uacbd\uae30, 16499, \ub300\ud55c\ubbfc\uad6d", "37.28300030", "127.04548469", "edu", "", "Korea", "2015"], ["Human detection using orientation shape histogram and coocurrence textures", "Department of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India", "National Institute of Technology, Rourkela", "National Institute of Technology Rourkela", "National Institute of Technology, inside the department, Koel Nagar, Rourkela, Sundargarh, Odisha, 769002, India", "22.25015890", "84.90668557", "edu", "", "India", "2018"], ["Virtual and Real World Adaptation for Pedestrian Detection", "Centro de Visi\u00f3n Por Computador-Edificio O, Universidad Aut\u00f3noma de Barcelona, Bellaterra, Spain", "Centro de Visi\u00f3n Por Computador-Edificio O, Universidad Aut\u00f3noma de Barcelona, Bellaterra, Spain", "Centro de Visi\u00f3n Por Computador-Edificio O, Universidad Aut\u00f3noma de Barcelona, Bellaterra, Spain", "Campus UAB, Edifici O, s/n, 08193 Cerdanyola del Vall\u00e8s, Barcelona, Spain", "41.50089570", "2.11155300", "edu", "", "Spain", "2013"], ["Annotation driven MAP search space estimation for sliding-window based person detection", "Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany", "Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany", "Fraunhofer IOSB, Gutleuthausstr. 1, 76275 Ettlingen, Germany", "Gutleuthausstra\u00dfe 1, 76275 Ettlingen, Germany", "48.94744960", "8.41171790", "company", "", "Germany", "2015"], ["Bi-box Regression for Pedestrian Detection and Occlusion Estimation", "", "SUNY Buffalo", "SUNY Buffalo", "SUNY College at Buffalo, Academic Drive, Elmwood Village, Buffalo, Erie County, New York, 14222, USA", "42.93362780", "-78.88394479", "edu", "", "United States", "2018"], ["Advanced Concepts for Intelligent Vision Systems", "University of Antwerp, Wilrijk, Belgium", "University of Antwerp", "University of Antwerp, Wilrijk, Belgium", "Prinsstraat 13, 2000 Antwerpen, Belgium", "51.22280970", "4.41023180", "edu", "", "Belgium", "2012"], ["Deformable parts model for people detection in heavy machines applications", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), CNRS Heudiasyc UMR 7253, Compi\u00e8gne, France", "Universit\u00e9 de Technologie de Compi\u00e8gne, Compi\u00e8gne, France", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), CNRS Heudiasyc UMR 7253, Compi\u00e8gne, France", "57 Avenue de Landshut, 60200 Compi\u00e8gne, France", "49.40075300", "2.79528080", "edu", "", "France", "2014"], ["Object Detection: Current and Future Directions", "", "Kyoto University", "Kyoto University", "\u4eac\u90fd\u5927\u5b66, \u4eca\u51fa\u5ddd\u901a, \u5409\u7530\u6cc9\u6bbf\u753a, \u5de6\u4eac\u533a, \u4eac\u90fd\u5e02, \u4eac\u90fd\u5e9c, \u8fd1\u757f\u5730\u65b9, 606-8501, \u65e5\u672c", "35.02749960", "135.78154513", "edu", "", "Japan", "2015"], ["Improve object detection via a multi-feature and multi-task CNN model", "Beijing University of Posts and Telecommunications, Beijing, P.R. China, 100876", "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", "", "China", "2017"], ["Stereo-based pedestrian detection using the dynamic ground plane estimation method", "Daegu Gyeongbuk Institute of Science & Technology, Daegu, Republic of Korea", "Daegu Gyeongbuk Institute of Science & Technology, Korea", "Division of Advanced Industrial Science and Technology, Daegu Gyeongbuk Institute of Science & Technology, Room 511, 5 floor, 3 research center, 223, Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, Republic of Korea", "223 Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, South Korea", "35.70270780", "128.45462720", "edu", "", "South Korea", "2016"], ["Long-Term Tracking by Decision Making", "", "University of California", "University of California", "Berkeley, CA, USA", "37.87189920", "-122.25853990", "edu", "", "United States", "2017"], ["In Teacher We Trust : Deep Network Compression for Pedestrian Detection", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2017"], ["Information theoretic sensor management for multi-target tracking with a single pan-tilt-zoom camera", "", "University of Verona", "University of Verona", "Via S. Francesco, 22, 37129 Verona VR, Italy", "45.43739800", "11.00337600", "edu", "", "Italy", "2014"], ["Stereo vision based negative obstacle detection", "School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2017"], ["Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry", "", "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", "", "China", "2016"], ["Switchable Deep Network for Pedestrian Detection", "", "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", "", "China", "2014"], ["Deep Feature Pyramid Reconfiguration for Object Detection", "", "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", "", "China", "2018"], ["A robust algorithm for detecting people in overhead views", "Centre of Excellence in IT, Institute of Management Sciences, Peshawar, Pakistan", "Centre of Excellence in IT, Institute of Management Sciences, Peshawar, Pakistan", "Centre of Excellence in IT, Institute of Management Sciences, Peshawar, Pakistan", "1-A, Sector E-5, Phase VII, Hayatabad\u060c Phase 7 Hayatabad, Peshawar, Khyber Pakhtunkhwa 25000, Pakistan", "33.95828240", "71.41671770", "edu", "", "Pakistan", "2017"], ["A Deeply-Recursive Convolutional Network For Crowd Counting", "", "Xiamen University", "Xiamen University", "\u53a6\u95e8\u5927\u5b66, \u601d\u660e\u5357\u8def Siming South Road, \u601d\u660e\u533a, \u601d\u660e\u533a (Siming), \u53a6\u95e8\u5e02 / Xiamen, \u798f\u5efa\u7701, 361005, \u4e2d\u56fd", "24.43994190", "118.09301781", "edu", "", "China", "2018"], ["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", "", "United States", "2018"], ["Smombie Guardian: We watch for potential obstacles while you are walking and conducting smartphone activities", "", "Ajou University", "Ajou University", "\uc544\uc8fc\ub300\ud559\uad50, \uc131\ud638\ub300\uad50, \uc774\uc758\ub3d9, \uc601\ud1b5\uad6c, \uc218\uc6d0\uc2dc, \uacbd\uae30, 16499, \ub300\ud55c\ubbfc\uad6d", "37.28300030", "127.04548469", "edu", "", "Korea", "2018"], ["Human tracking using multiple views", "Computer Science Department, University Politehnica of Bucharest, Bucharest, Romania", "University Politehnica of Bucharest", "University Politehnica of Bucharest", "Universitatea Politehnica din Bucure\u0219ti, Novum Invest, Bucure\u0219ti, Militari, Sector 6, Municipiul Bucure\u0219ti, 060042, Rom\u00e2nia", "44.43918115", "26.05044565", "edu", "", "Romania", "2017"], ["K-tangent spaces on Riemannian manifolds for improved pedestrian detection", "", "University of Queensland", "University of Queensland", "University of Queensland, University Drive, Hill End, St Lucia, Brisbane, QLD, 4072, Australia", "-27.49741805", "153.01316956", "edu", "", "Australia", "2012"], ["Recognizing Actions Through Action-Specific Person Detection", "Department of Information and Computer Science, Aalto University School of Science, Aalto, Finland", "Computer Vision Centre Barcelona, Barcelona, Spain", "Computer Vision Centre Barcelona, Barcelona, Spain", "Campus UAB, Edifici O, s/n, 08193 Cerdanyola del Vall\u00e8s, Barcelona, Spain", "41.50089570", "2.11155300", "edu", "", "Spain", "2015"], ["Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing", "National University of Singapore, Singapore, Singapore", "National University of Singapore", "National University of Singapore", "NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore", "1.29620180", "103.77689944", "edu", "", "Singapore", "2018"], ["Using Simulation to Improve Human Pose Estimation for Corner Cases", "Computer Science Department, Reutlingen University, Cognitive Systems Group, Germany", "Reutlingen University", "Reutlingen University", "Campus Hohbuch, Campus Hochschule Reutlingen, Reutlingen, Landkreis Reutlingen, Regierungsbezirk T\u00fcbingen, Baden-W\u00fcrttemberg, 72762, Deutschland", "48.48187645", "9.18682404", "edu", "", "Germany", "2018"], ["Assistive Intelligent Transportation Systems: The Need for User Localization and Anonymous Disability Identification", "Signal Theory Department, Polytechnic School, University of Madrid, Spain", "University of Alcala", "Geintra Research Group, University of Alcala", "Plaza de San Diego, s/n, 28801 Alcal\u00e1 de Henares, Madrid, Spain", "40.48247220", "-3.36286740", "edu", "", "Spain", "2017"], ["Real time security framework for detecting abnormal events at ATM installations", "Uttarakhand Technical University, Dehradun, India", "Uttarakhand Technical University", "Uttarakhand Technical University, Dehradun, India", "Post Office , Girls Polytechnic Campus, Chakrata Road, Chandanwadi, Sudhowala, Dehradun, Uttarakhand 248007, India", "30.34350270", "77.94006780", "edu", "", "India", "2016"], ["Pedestrian detection combining RGB and dense LIDAR data", "Institute of Systems and Robotics, Electrical and Computer Engineering Department, University of Coimbra, Portugal", "Institute of Systems and Robotics", "Institute of Systems and Robotics", "Institut f\u00fcr Robotik und Kognitive Systeme, 160, Ratzeburger Allee, Strecknitz, Sankt J\u00fcrgen, Strecknitz, L\u00fcbeck, Schleswig-Holstein, 23562, Deutschland", "53.83383710", "10.70359390", "edu", "", "Germany", "2014"], ["Efficient local filter bank with over complete spatiotemporal pooling in action recognition", "Science and Technology on Electro-optic Control Laboratory, Luoyang,471009,China", "Science and Technology on Electro-optic Control Laboratory, Luoyang,471009,China", "Science and Technology on Electro-optic Control Laboratory, Luoyang,471009,China", "Xigong, Luoyang, Henan, China, 471009", "34.66684840", "112.44663850", "edu", "", "China", "2013"], ["Ceiling analysis of pedestrian recognition pipeline for an autonomous car application", "Mobile Robotics Lab (LabRoM), S\u00e3o Carlos School of Engineering (EESC), University of S\u00e3o Paulo, Av. Trabalhador Sancarlense 400, Brazil", "University of S\u00e3o Paulo", "University of S\u00e3o Paulo", "S\u00e3o Paulo - State of S\u00e3o Paulo, Brazil", "-23.56139910", "-46.73078910", "edu", "", "Brazil", "2013"], ["Fast and Efficient Pedestrian Detection via the Cascade Implementation of an Additive Kernel Support Vector Machine", "Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea", "Yonsei University", "Yonsei University", "\uc5f0\uc138\ub300, \uc5f0\uc138\ub85c, \uc2e0\ucd0c\ub3d9, \ucc3d\ucc9c\ub3d9, \uc11c\ub300\ubb38\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 03789, \ub300\ud55c\ubbfc\uad6d", "37.56004060", "126.93692480", "edu", "", "South Korea", "2017"], ["S-CNN: Subcategory-Aware Convolutional Networks for Object Detection", "Visual Computing Department, Agency for Science Technology and Research, Singapore", "Singapore", "Singapore", "Singapore", "1.35208300", "103.81983600", "edu", "", "Singapore", "2018"], ["Highway Vehicle Counting in Compressed Domain", "", "National University of Singapore", "National University of Singapore", "NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore", "1.29620180", "103.77689944", "edu", "", "Singapore", "2016"], ["Structure maps based pedestrian detection", "Tsinghua University, Department of Electronic Engineering, Beijing, China", "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", "", "China", "2014"], ["Recognition in-the-Tail: Training Detectors for Unusual Pedestrians with Synthetic Imposters", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2017"], ["Real-time pedestrian detection system with novel thermal features at night", "Instrument Technology Research Center, National Applied Research Laboratories, Taiwan, Republic of China", "Instrument Technology Research Center, National Applied Research Laboratories, Taiwan, Republic of China", "Instrument Technology Research Center, National Applied Research Laboratories, Taiwan, Republic of China", "No. 20\u865f, R&D 6th Rd, East District, Hsinchu City, Taiwan 300", "24.78275380", "120.99661660", "edu", "", "Taiwan", "2014"], ["MutualCascade method for pedestrian detection", "State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2014"], ["Minimal filtered channel features for pedestrian detection", "Yamaha Motor Co., Ltd., Japan", "Yamaha Motor Co., Ltd., Japan", "Yamaha Motor Co., Ltd., Japan", "Japan, \u3012437-0066 \u9759\u5ca1\u770c\u888b\u4e95\u5e02\u5c71\u79d1\uff13\uff10\uff18\uff10", "34.76542100", "137.90685900", "company", "", "Japan", "2016"], ["An MRF-Poselets Model for Detecting Highly Articulated Humans", "", "Singapore University of Technology and Design", "Singapore University of Technology and Design", "Singapore University of Technology and Design, Simpang Bedok, Changi Business Park, Southeast, 486041, Singapore", "1.34021600", "103.96508900", "edu", "", "Singapore", "2015"], ["Fast stereo-based pedestrian detection using hypotheses", "DGIST, Hyeonpung-Myeon, Dalseong-Gun Daegu, South KOREA", "DGIST", "DGIST", "South Korea, Daegu, Dalseong-gun, Yuga-myeon, \ud14c\ud06c\ub178\uc911\uc559\ub300\ub85c 333", "35.70528600", "128.45710200", "edu", "", "South Korea", "2015"], ["Recognition and pose estimation of urban road users from on-board camera for collision avoidance", "Institute of Industrial Science, the University of Tokyo, 4-6-1 Komaba, 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", "", "Japan", "2014"], ["FPGA Implementation of a Real-Time Pedestrian Detection Processor Aided by E-HOG IP", "", "Shanghai, China", "Shanghai, China", "Shanghai, China", "31.23039040", "121.47370210", "edu", "", "", "2017"], ["Histograms of Salience for Pedestrian Detection", "School of Computer, Wuhan University, Wuhan, China", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2014"], ["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", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2012"], ["Local Context Priors for Object Proposal Generation", "", "ETH Zurich", "ETH Zurich", "R\u00e4mistrasse 101, 8092 Z\u00fcrich, Switzerland", "47.37631300", "8.54766990", "edu", "", "Switzerland", "2012"], ["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", "", "China", "2015"], ["Histogram of Oriented Phase (HOP): A New Descriptor Based on Phase Congruency", "", "University of Dayton", "University of Dayton", "University of Dayton, Caldwell Street, South Park Historic District, Dayton, Montgomery, Ohio, 45409, USA", "39.73844400", "-84.17918747", "edu", "", "United States", "2016"], ["Pedestrian detection with an improved Adaboost", "Multimedia Signal Analysis Lab at Electronics & Comms, Eng. Dpt., Electrical & Electronics Faculty, Yildiz, Technical University, Istanbul, Turkey", "Yildiz Technical University", "Yildiz Technical University, Electronics & Telecommunications Eng. Dpt., Istanbul, Turkey", "Y\u0131ld\u0131z Mh., 34349 Be\u015fikta\u015f/\u0130stanbul, Turkey", "41.05208610", "29.01065530", "edu", "", "Turkey", "2013"], ["Pedestrian detection based on Region Proposal Fusion", "Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China, 100190", "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", "", "China", "2015"], ["Pedestrian monitoring techniques for crowd-fl ow prediction", "", "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", "", "United Kingdom", "2017"], ["Accurate pedestrian detection using RGB-D camera", "Beijing Innovisgroup Tec Co. LTD, Beijing, China", "Beijing Innovisgroup Tec Co. LTD, Beijing, China", "Beijing Innovisgroup Tec Co. LTD, Beijing, China", "Beijing, China", "39.90419990", "116.40739630", "company", "", "", "2017"], ["Co-training of feature extraction and classification using partitioned convolutional neural networks", "School of Electrical Engineering and Computer Science, Pennsylvania State University, PA USA", "Pennsylvania State University", "Pennsylvania State University", "Old Main, State College, PA 16801, USA", "40.79821330", "-77.85990840", "edu", "", "United States", "2017"], ["Online Motion Agreement Tracking", "", "Boston University", "Boston University", "BU, Bay State Road, Fenway, Boston, Suffolk County, Massachusetts, 02215, USA", "42.35042530", "-71.10056114", "edu", "", "United States", "2015"], ["Distributed Object Detection With Linear SVMs", "School of Electronic Information Engineering, Tianjin University, Tianjin, China", "Tianjin University", "Tianjin University", "\u6cf0\u5c71\u822a\u7a7a\u6e2f/\u5929\u6d25\u5927\u53a6, \u67a3\u884c\u8def, \u67a3\u884c \u9ad8\u738b\u5bfa, \u957f\u57ce\u8def, \u5927\u6cb3, \u5cb1\u5cb3\u533a (Daiyue), \u6cf0\u5b89\u5e02, \u5c71\u4e1c\u7701, 271000, \u4e2d\u56fd", "36.20304395", "117.05842113", "edu", "", "China", "2014"], ["Pedestrian detection based on multi-convolutional features by feature maps pruning", "State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing Shi, China", "Nanjing University", "Nanjing University", "NJU, \u4e09\u6c5f\u8def, \u9f13\u697c\u533a, \u5357\u4eac\u5e02, \u6c5f\u82cf\u7701, 210093, \u4e2d\u56fd", "32.05659570", "118.77408833", "edu", "", "China", "2017"], ["Pedestrian Verification for Multi-Camera Detection", "", "University of North Carolina at Charlotte", "University of North Carolina at Charlotte", "Lot 20, Poplar Terrace Drive, Charlotte, Mecklenburg County, North Carolina, 28223, USA", "35.31034410", "-80.73261617", "edu", "", "United States", "2014"], ["Real-time Human Detection based on Personness Estimation", "", "Samsung Electronics", "Samsung Electronics", "25 The West Mall, Etobicoke, ON M9C 1B8, Canada", "43.61294840", "-79.55903030", "edu", "", "Canada", "2015"], ["Are we ready for autonomous driving? The KITTI vision benchmark suite", "Toyota Technological Institute at Chicago", "Toyota Technological Institute at Chicago", "Toyota Technological Institute at Chicago", "6045 S Kenwood Ave, Chicago, IL 60637, USA", "41.78469820", "-87.59258480", "company", "", "United States", "2012"], ["Real-Time Pedestrian Detection and Tracking", "", "Kumamoto University", "Kumamoto University", "\u718a\u672c\u5927\u5b66\u9ed2\u9aea\u30ad\u30e3\u30f3\u30d1\u30b9, \u718a\u672c\u83ca\u967d\u7dda, \u4e2d\u592e\u533a, \u718a\u672c\u5e02, \u718a\u672c\u770c, \u4e5d\u5dde\u5730\u65b9, 860-0863, \u65e5\u672c", "32.81641780", "130.72703969", "edu", "", "Japan", "2014"], ["Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2018"], ["Fast pedestrian detection using BWLSD for ROI", "Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Hongshan, Wuhuan, Hubei 430074, China", "Huazhong University of Science and Technology", "Huazhong University of Science and Technology", "\u534e\u4e2d\u5927, \u73de\u55bb\u8def, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a, \u5173\u4e1c\u8857\u9053, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a\uff08\u6258\u7ba1\uff09, \u6d2a\u5c71\u533a (Hongshan), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430074, \u4e2d\u56fd", "30.50975370", "114.40628810", "edu", "", "China", "2013"], ["Pedestrian Detection , Tracking and Re-Identification for Search in Visual Surveillance Data", "", "Graz University of Technology", "Graz University of Technology", "TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, \u00d6sterreich", "47.05821000", "15.46019568", "edu", "", "Austria", "2013"], ["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", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2016"], ["Dissertation S cene specific object detection and tracking", "", "Graz University of Technology", "Graz University of Technology", "TU Graz, Inffeldgasse, Harmsdorf, Jakomini, Graz, Steiermark, 8010, \u00d6sterreich", "47.05821000", "15.46019568", "edu", "", "Austria", "2013"], ["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", "", "China", "2017"], ["Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects", "", "University of Tokyo", "University of Tokyo", "\u6771\u4eac\u5927\u5b66 \u67cf\u30ad\u30e3\u30f3\u30d1\u30b9, \u5b66\u878d\u5408\u306e\u9053, \u67cf\u5e02, \u5343\u8449\u770c, \u95a2\u6771\u5730\u65b9, 277-8583, \u65e5\u672c", "35.90204480", "139.93622009", "edu", "", "Japan", "2017"], ["Fast region-based DPM object detection for autonomous vehicles", "The Center for Advanced Computer Studies (CACS), University of Louisiana at Lafayette, LA, USA", "University of Louisiana at Lafayette", "University of Louisiana at Lafayette, Lafayette, LA", "104 East University Avenue, Lafayette, LA 70504, USA", "30.21144040", "-92.02041210", "edu", "", "United States", "2016"], ["Fusion of Perception and V2P Communication Systems for the Safety of Vulnerable Road Users", "RITS Project-Team, INRIA Paris, Paris, France", "RITS Project-Team, INRIA Paris, Paris, France", "RITS Project-Team, INRIA Paris, Paris, France", "Institut National de Recherche en Informatique et en Automatique, 54600 Villers-l\u00e8s-Nancy, France", "48.66544710", "6.15702390", "edu", "", "France", "2017"], ["A Speed-Up Scheme Based on Multiple-Instance Pruning for Pedestrian Detection Using a Support Vector Machine", "School of Science and Technology, Meiji University, Kanagawa, Japan", "Meiji University", "Meiji University", "\u660e\u6cbb\u5927\u5b66, \u9326\u83ef\u5742, \u733f\u697d\u753a1, \u733f\u697d\u753a, \u6771\u4eac, \u5343\u4ee3\u7530\u533a, \u6771\u4eac\u90fd, \u95a2\u6771\u5730\u65b9, 101-0051, \u65e5\u672c", "35.69750290", "139.76139175", "edu", "", "Japan", "2013"], ["Histogram of Radon Projections: A new descriptor for object detection", "College of Engineering, Trivandrum, India", "College of Engineering, Trivandrum, India", "College of Engineering, Trivandrum, India", "Engineering College, Sreekaryam - Kulathoor Rd, Ambady Nagar, P O, Sreekariyam, Thiruvananthapuram, Kerala 695016, India", "8.54585130", "76.90634070", "edu", "", "India", "2015"], ["Local descriptors based random forests for human detection", "", "University of Ulsan", "University of Ulsan, Korea", "93 Daehak-ro, Mugeo-dong, Nam-gu, Ulsan, South Korea", "35.54374110", "129.25628430", "edu", "", "South Korea", "2016"], ["A SSD-based Crowded Pedestrian Detection Method", "Xi'an Jiaotong University, School of Software Engineering, Xi'an, China", "Xi'an Jiaotong University", "Xi'an Jiaotong University", "\u897f\u5b89\u4ea4\u901a\u5927\u5b66\u5174\u5e86\u6821\u533a, \u6587\u6cbb\u8def, \u4e50\u5c45\u573a, \u7891\u6797\u533a (Beilin), \u897f\u5b89\u5e02, \u9655\u897f\u7701, 710048, \u4e2d\u56fd", "34.24749490", "108.97898751", "edu", "", "China", "2018"], ["Real-time traffic estimation at vehicular edge nodes", "", "University of Southern California", "University of Southern California", "University of Southern California, Watt Way, Saint James Park, LA, Los Angeles County, California, 90089, USA", "34.02241490", "-118.28634407", "edu", "", "United States", "2017"], ["A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community", "", "University of Malaya", "University of Malaya", "UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia", "3.12267405", "101.65356103", "edu", "", "Malaysia", "2017"], ["CoDeL: A Human Co-detection and Labeling Framework", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2013"], ["Saliency-Based Pedestrian Detection in Far Infrared Images", "School of Automotive and Traffic 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", "", "China", "2017"], ["Context and Subcategories for SlidingWindowObject Recognition", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2012"], ["Pyramidal channel features for pedestrian detector", "Daegu Gyeongbuk Institute of Science & Technology, Daegu, Republic of Korea", "Daegu Gyeongbuk Institute of Science & Technology, Korea", "Division of Advanced Industrial Science and Technology, Daegu Gyeongbuk Institute of Science & Technology, Room 511, 5 floor, 3 research center, 223, Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, Republic of Korea", "223 Sang-ri, Hyeonpung-myeon, Dalseong-gun, Daegu, South Korea", "35.70270780", "128.45462720", "edu", "", "South Korea", "2015"], ["On-Board Object Detection: Multicue, Multimodal, and Multiview Random Forest of Local Experts", "United Technologies Research Center, Cork, Ireland", "United Technologies Research Center, Cork, Ireland", "United Technologies Research Center, Cork, Ireland", "411 Silver Ln, East Hartford, CT 06108, USA", "41.75805010", "-72.62483360", "edu", "", "United States", "2017"], ["A hierarchical method for pedestrian detection with random forests", "School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China 611731", "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", "", "United States", "2014"], ["Characterizing a Heterogeneous System for Person Detection in Video Using Histograms of Oriented Gradients: Power Versus Speed Versus Accuracy", "Visionlab at Heriot-Watt University, UK", "Visionlab at Heriot-Watt University", "Visionlab at Heriot-Watt University, UK", "Edinburgh Campus, Boundary Rd N, Edinburgh EH14 4AS, UK", "55.90966020", "-3.32034940", "edu", "", "United Kingdom", "2013"], ["Taking a deeper look at pedestrians", "", "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", "", "Germany", "2015"], ["Local Decorrelation For Improved Pedestrian Detection", "", "Microsoft", "Microsoft Corporation, Redmond, WA, USA", "One Microsoft Way, Redmond, WA 98052, USA", "47.64233180", "-122.13693020", "company", "", "United States", "2014"], ["A Two Phase Approach for Pedestrian Detection", "", "KAIST", "KAIST", "291 Daehak-ro, Eoeun-dong, Yuseong-gu, Daejeon, South Korea", "36.37214270", "127.36039000", "edu", "", "South Korea", "2014"], ["Object classification and localization with spatially localized features", "", "University of British Columbia", "University of British Columbia", "University of British Columbia, Eagles Drive, Hawthorn Place, University Endowment Lands, Metro Vancouver, British Columbia, V6T, Canada", "49.25839375", "-123.24658161", "edu", "", "Canada", "2014"], ["ViS-HuD: Using Visual Saliency to Improve Human Detection with Convolutional Neural Networks", "", "Ahmedabad University", "Ahmedabad University", "School of Science and Technology, University Road, Gurukul, Gulbai tekra, Ahmedabad, Ahmedabad District, Gujarat, 380001, India", "23.03787430", "72.55180046", "edu", "", "India", "2018"], ["Leveraging Dynamics in Computer Vision Problems: User Friendly and Theoretically Sound Tools", "", "Northeastern University", "Northeastern University", "Snell Library, 360, Huntington Avenue, Roxbury Crossing, Fenway, Boston, Suffolk County, Massachusetts, 02115, USA", "42.33836680", "-71.08793524", "edu", "", "United States", "2017"], ["Real-time moving pedestrian detection using contour features", "School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, People\u2019s Republic of China", "China University of Mining and Technology", "China University of Mining and Technology", "China University of Mining and Technology, 1\u53f7, \u5927\u5b66\u8def, \u6cc9\u5c71\u533a (Quanshan), \u5f90\u5dde\u5e02 / Xuzhou, \u6c5f\u82cf\u7701, 221116, \u4e2d\u56fd", "34.21525380", "117.13985410", "edu", "", "China", "2018"], ["Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption", "", "University of Waterloo", "University of Waterloo", "University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada", "43.47061295", "-80.54724732", "edu", "", "Canada", "2017"], ["Multi-channel Convolutional Neural Network Ensemble for Pedestrian Detection", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2017"], ["Online, Real-Time Tracking Using a Category-to-Individual Detector", "", "California Institute of Technology", "California Institute of Technology", "California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA", "34.13710185", "-118.12527487", "edu", "", "United States", "2014"], ["Illuminating Pedestrians via Simultaneous Detection and Segmentation", "", "Michigan State University", "Michigan State University", "Michigan State University, Farm Lane, East Lansing, Ingham County, Michigan, 48824, USA", "42.71856800", "-84.47791571", "edu", "", "United States", "2017"], ["Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing", "", "National University of Defense Technology, China", "National University of Defence Technology, Changsha 410000, China", "\u56fd\u9632\u79d1\u5b66\u6280\u672f\u5927\u5b66, \u4e09\u4e00\u5927\u9053, \u5f00\u798f\u533a, \u5f00\u798f\u533a (Kaifu), \u957f\u6c99\u5e02 / Changsha, \u6e56\u5357\u7701, 410073, \u4e2d\u56fd", "28.22902090", "112.99483204", "mil", "", "China", "2018"], ["A novel set of pixel difference-based features for pedestrian detection", "Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea", "Yonsei University", "Yonsei University", "\uc5f0\uc138\ub300, \uc5f0\uc138\ub85c, \uc2e0\ucd0c\ub3d9, \ucc3d\ucc9c\ub3d9, \uc11c\ub300\ubb38\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 03789, \ub300\ud55c\ubbfc\uad6d", "37.56004060", "126.93692480", "edu", "", "South Korea", "2018"], ["Low-level multimodal integration on Riemannian manifolds for automatic pedestrian detection", "", "University of Verona", "University of Verona", "Via S. Francesco, 22, 37129 Verona VR, Italy", "45.43739800", "11.00337600", "edu", "", "Italy", "2012"], ["Influence of binning in Histograms of Oriented Gradients method representation", "Department of Electronics Engineering, Madras Institute of Technology, Anna University, Chennai-600044, India", "Anna University", "Anna University", "Anna University, Nuclear Physics Road, Srinagar Colony, Ward 171, Zone 13 Adyar, Chennai, Chennai district, Tamil Nadu, 600025, India", "13.01058380", "80.23537360", "edu", "", "India", "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", "", "Singapore", "2014"], ["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", "Robot Bosch LLC, Pittsburgh, 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", "company", "", "United States", "2014"], ["Delving Deep into Multiscale Pedestrian Detection via Single Scale Feature Maps", "", "East China Normal University", "East China Normal University", "\u534e\u4e1c\u5e08\u8303\u5927\u5b66, 3663, \u4e2d\u5c71\u5317\u8def, \u66f9\u5bb6\u6e21, \u666e\u9640\u533a, \u666e\u9640\u533a (Putuo), \u4e0a\u6d77\u5e02, 200062, \u4e2d\u56fd", "31.22849230", "121.40211389", "edu", "", "China", "2018"], ["Energy-Efficient Pedestrian Detection System: Exploiting Statistical Error Compensation for Lossy Memory Data Compression", "Department of Electrical Engineering, Princeton University, Princeton, NJ, USA", "Princeton University", "Princeton University", "Lot 9, University Place, Princeton Township, Mercer County, New Jersey, 08540, USA", "40.34829285", "-74.66308325", "edu", "", "United States", "2018"], ["MetaAnchor: Learning to Detect Objects with Customized Anchors", "", "Fudan University", "Fudan University", "\u590d\u65e6\u5927\u5b66, 220, \u90af\u90f8\u8def, \u4e94\u89d2\u573a\u8857\u9053, \u6768\u6d66\u533a, \u4e0a\u6d77\u5e02, 200433, \u4e2d\u56fd", "31.30104395", "121.50045497", "edu", "", "China", "2018"], ["Exploiting Multispectral and Contextual Information to Improve Human Detection", "", "State University of New Jersey", "The State University of New Jersey", "Rutgers New Brunswick: Livingston Campus, Joyce Kilmer Avenue, Piscataway Township, Middlesex County, New Jersey, 08854, USA", "40.51865195", "-74.44099801", "edu", "", "United States", "2017"], ["A patch memory system for image processing and computer vision", "Qualcomm, Santa Clara, CA", "Qualcomm, Santa Clara, CA", "Qualcomm, Santa Clara, CA", "3165 Kifer Rd, Santa Clara, CA 95051, USA", "37.37540580", "-121.98356780", "company", "", "United States", "2016"], ["Learning Efficient Single-Stage Pedestrian Detectors by Asymptotic Localization Fitting", "", "National University of Defense Technology, China", "National University of Defence Technology, Changsha 410000, China", "\u56fd\u9632\u79d1\u5b66\u6280\u672f\u5927\u5b66, \u4e09\u4e00\u5927\u9053, \u5f00\u798f\u533a, \u5f00\u798f\u533a (Kaifu), \u957f\u6c99\u5e02 / Changsha, \u6e56\u5357\u7701, 410073, \u4e2d\u56fd", "28.22902090", "112.99483204", "mil", "", "China", "2018"], ["A hybrid fusion based frontal-lateral collaborative pedestrian detection and tracking", "imec-IPI-Ghent University, Sint-Pietersnieuwstraat 41, 9000 Gent, Belgium", "Ghent University", "Ghent University", "St. Pietersnieuwstraat 33, 9000 Gent, Belgium", "51.04656190", "3.72791810", "edu", "", "Belgium", "2017"], ["SpaFIND: An Effective and Low-Cost Feature Descriptor for Pedestrian Protection Systems in Economy Cars", "Toyota Central R&D Labs., Inc., Nagakute, Japan", "Toyota Central R&D Labs., Inc., Nagakute, Japan", "Toyota Central R&D Labs., Inc., Nagakute, Japan", "41\u756a\uff11 Yokomichi, Nagakute, Aichi Prefecture 480-1192, Japan", "35.16898430", "137.05429210", "company", "", "Japan", "2017"], ["Traffic sign detection from video: A fast approach with tracking", "National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences", "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", "", "China", "2015"], ["FEASIBILITY OF IN-PLANE ARTICULATION MONITORING OF EXCAVATOR ARM USING PLANAR MARKER TRACKING", "", "University of Michigan", "University of Michigan", "University of Michigan, 500, Hayward Street, Ann Arbor, Washtenaw County, Michigan, 48109, USA", "42.29421420", "-83.71003894", "edu", "", "United States", "2015"], ["An Adaptive Background Modeling Method for Foreground Segmentation", "Mobile Video Networking Technology Research Center, Shenzhen Graduate School, Peking University, Shenzhen, China", "Peking University", "Peking University", "\u5317\u4eac\u5927\u5b66, 5\u53f7, \u9890\u548c\u56ed\u8def, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100871, \u4e2d\u56fd", "39.99223790", "116.30393816", "edu", "", "China", "2017"], ["Tracking articulated human movements witha component based approach to boosted multiple instance learning", "", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "United States", "2013"], ["Local Transform Features and Hybridization for Accurate Face and Human Detection", "Pohang University of Science and Technology, Pohang", "Pohang University of Science and Technology", "Pohang University of Science and Technology", "\ud3ec\uc2a4\ud14d, 77, \uccad\uc554\ub85c, \ud6a8\uace1\ub3d9, \ub0a8\uad6c, \ud3ec\ud56d\uc2dc, \uacbd\ubd81, 37673, \ub300\ud55c\ubbfc\uad6d", "36.01773095", "129.32107509", "edu", "", "South Korea", "2013"], ["SLTP: A Fast Descriptor for People Detection in Depth Images", "", "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", "", "China", "2012"], ["A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection", "", "UC San Diego", "UC San Diego", "9500 Gilman Dr, La Jolla, CA 92093, USA", "32.88006040", "-117.23401350", "edu", "", "United States", "2016"], ["Unsupervised domain adaptation of virtual and real worlds for pedestrian detection", "CVC and C. Sc. Dpt. UAB, Barcelona, Spain", "UAB, Barcelona, Spain", "CVC and C. Sc. Dpt. UAB, Barcelona, Spain", "Campus de la UAB, Pla\u00e7a C\u00edvica, 08193 Bellaterra, Barcelona, Spain", "41.50192550", "2.10485380", "edu", "", "Spain", "2012"], ["Vision-based pedestrian detection for rear-view cameras", "Advanced Technical Center - Israel, General Motors R&D, Hamada 7 Herzlyia, Israel", "General Motors R&D, Israel", "Advanced Technical Center - Israel, General Motors R&D, Hamada 7 Herzlyia, Israel", "46733, HaMada St 7, Herzliya, Israel", "32.16659230", "34.81274680", "company", "", "Israel", "2014"], ["Improving the Generalization Capacity of Cascade Classifiers", "Informatics Engineering Department, Faculty of Science and Technology, University of Coimbra, Portugal", "University of Coimbra", "University of Coimbra", "Reitoria da Universidade de Coimbra, Rua de Entre-Col\u00e9gios, Almedina, Alta, Almedina, S\u00e9 Nova, Santa Cruz, Almedina e S\u00e3o Bartolomeu, CBR, Coimbra, Baixo Mondego, Centro, 3000-062, Portugal", "40.20759510", "-8.42566148", "edu", "", "Portugal", "2013"], ["Illumination-aware faster R-CNN for robust multispectral pedestrian detection", "", "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", "", "China", "2019"], ["An RRT-based navigation approach for mobile robots and automated vehicles", "", "Coimbra, Portugal", "Coimbra, Portugal", "Coimbra, Portugal", "40.20331450", "-8.41025730", "edu", "", "", "2014"], ["A Low-Complexity Pedestrian Detection Framework for Smart Video Surveillance Systems", "Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea", "Korea Advanced Institute of Science and Technology", "Korea Advanced Institute of Science and Technology", "\uce74\uc774\uc2a4\ud2b8, 291, \ub300\ud559\ub85c, \uc628\ucc9c2\ub3d9, \uc628\ucc9c\ub3d9, \uc720\uc131\uad6c, \ub300\uc804, 34141, \ub300\ud55c\ubbfc\uad6d", "36.36971910", "127.36253700", "edu", "", "South Korea", "2017"], ["Template Visible Map GT box Neg Proposal Training Patch Head \u2010 Shoulder Part Detector ( ConvNet ) Part", "", "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", "", "China", "2015"], ["Pedestrian Detection in Low Quality Moving Camera Videos", "", "University of South Florida", "University of South Florida", "University of South Florida, Leroy Collins Boulevard, Tampa, Hillsborough County, Florida, 33620, USA", "28.05999990", "-82.41383619", "edu", "", "United States", "2017"], ["Human Detection in Infrared Imagery using Gradient and Texture Features and Super-pixel Segmentation", "Electrical and Computer Engineering, University of Dayton, Dayton, Ohio, USA", "Electrical and Computer Engineering", "Electrical and Computer Engineering", "Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA", "33.58667840", "-101.87539204", "edu", "", "United States", "2018"], ["Multi-Stream Region Proposal Network for Pedestrian Detection", "University of Chinese Academy of Sciences, Beijing, China", "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", "", "China", "2018"], ["CADP : A Novel Dataset for CCTV Traffic Camera based Accident Analysis", "", "University of Tokyo", "University of Tokyo", "\u6771\u4eac\u5927\u5b66 \u67cf\u30ad\u30e3\u30f3\u30d1\u30b9, \u5b66\u878d\u5408\u306e\u9053, \u67cf\u5e02, \u5343\u8449\u770c, \u95a2\u6771\u5730\u65b9, 277-8583, \u65e5\u672c", "35.90204480", "139.93622009", "edu", "", "Japan", "2018"], ["Construction Worker Detection and Tracking in Bird \u2019 sEye View Camera Images", "", "Ruhr-University Bochum", "Ruhr-University Bochum", "RUB, 150, Universit\u00e4tsstra\u00dfe, Ruhr-Universit\u00e4t, Querenburg, Bochum-S\u00fcd, Bochum, Regierungsbezirk Arnsberg, Nordrhein-Westfalen, 44801, Deutschland", "51.44415765", "7.26096541", "edu", "", "Germany", "2018"], ["Improving channel features using statistical analysis for pedestrian detection", "Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, USA", "Illinois Institute of Technology", "Illinois Institute of Technology", "Illinois Institute of Technology, South State Street, Bronzeville, Chicago, Cook County, Illinois, 60616, USA", "41.83619630", "-87.62655913", "edu", "", "United States", "2017"], ["SPID: Surveillance Pedestrian Image Dataset and Performance Evaluation for Pedestrian Detection", "", "Shanghai, China", "Shanghai, China", "Shanghai, China", "31.23039040", "121.47370210", "edu", "", "", "2016"], ["Fast and Accurate Pedestrian Detection using Dual-Stage Group Cost-Sensitive RealBoost with Vector Form Filters", "Nanyang Technological University, Singapore, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2017"], ["Onboard monocular pedestrian detection by combining spatio-temporal hog with structure from motion algorithm", "The State Key Lab of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 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", "", "China", "2014"], ["Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery", "", "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", "", "China", "2016"], ["Pedestrian recognition using a dynamic modality fusion approach", "Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes, EA 4108, Institut National des Sciences Appliquées, Rouen, France", "Institut National des Sciences Appliqu\u00e9es, Rouen, France", "Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes, EA 4108, Institut National des Sciences Appliquées, Rouen, France", "Rouen, France", "49.44323200", "1.09997100", "edu", "", "France", "2015"], ["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", "", "Canada", "2018"], ["A multiple kernel learning approach to multi-modal pedestrian classification", "Pattern Analysis & Computer Vision, Istituto Italiano di Tecnologia, Genova - Italy", "Istituto Italiano di Tecnologia", "Istituto Italiano di Tecnologia", "77 Massachusetts Ave, Cambridge, MA 02139, USA", "42.36009100", "-71.09416000", "edu", "", "United States", "2012"], ["Pedestrian detection in thermal images using adaptive fuzzy C-means clustering and convolutional neural networks", "", "Toyota Technological Institute", "Toyota Technological Institute", "6045 S Kenwood Ave, Chicago, IL 60637, USA", "41.78469820", "-87.59258480", "edu", "", "", "2015"], ["Looking at Pedestrians at Different Scales: A Multiresolution Approach and Evaluations", "Laboratory for Intelligent and Safe Automobiles (LISA), University of California San Diego, La Jolla, CA, USA", "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", "", "United States", "2016"], ["Pedestrian Detectability Estimation Considering Visual Adaptation to Drastic Illumination Change", "", "Nagoya University", "Nagoya University", "SuperDARN (Hokkaido West), \u592a\u8f9b\u7b2c1\u652f\u7dda\u6797\u9053, \u9678\u5225\u753a, \u8db3\u5bc4\u90e1, \u5341\u52dd\u7dcf\u5408\u632f\u8208\u5c40, \u5317\u6d77\u9053, \u5317\u6d77\u9053\u5730\u65b9, \u65e5\u672c", "43.53750985", "143.60768225", "edu", "", "Japan", "2018"], ["Detecting occluded people for robotic guidance", "Toyota InfoTechnology Center, Mountain View, CA 94943 USA", "Toyota InfoTechnology Center, Mountain View, CA", "Toyota InfoTechnology Center, Mountain View, CA 94943 USA", "465 N Bernardo Ave, Mountain View, CA 94043, USA", "37.38904990", "-122.04956330", "company", "", "United States", "2014"], ["Learning deep compact channel features for object detection in traffic scenes", "School of Engineering and Advanced Technology, Massey University", "Massey University", "Massey University", "1600 Belmont Blvd, Nashville, TN 37212, USA", "36.13564170", "-86.79379500", "edu", "", "United States", "2016"], ["Privacy-conscious human detection using low-resolution video", "Fujitsu Laboratories Limited, Kanagawa, Japan", "Fujitsu Laboratories Limited, Kanagawa, Japan", "Fujitsu Laboratories Limited, Kanagawa, Japan", "4 Chome-1-1 Kamikodanaka, Nakahara Ward, Kawasaki, Kanagawa Prefecture 211-0053, Japan", "35.58263610", "139.64226560", "company", "", "Japan", "2015"], ["A precise human detection model using combination of feature extraction techniques in a dynamic environment", "Faculty of Engineering and Information Technology, University of Technology, Sydney(UTS) Taibah University", "Sydney Taibah University", "Faculty of Engineering and Information Technology, University of Technology, Sydney(UTS) Taibah University", "15 Broadway, Ultimo NSW 2007, Australia", "-33.88323760", "151.20049420", "edu", "", "Australia", "2017"], ["The Role of Machine Vision for Intelligent Vehicles", "FZI Research Center for Information Technology, Karlsruhe, Germany", "FZI Research Center for Information Technology, Karlsruhe, Germany", "FZI Research Center for Information Technology, Karlsruhe, Germany", "Haid-und-Neu-Stra\u00dfe 10-14, 76131 Karlsruhe, Germany", "49.01186900", "8.42552660", "edu", "", "", "2016"], ["Transfer of sparse coding representations and object classifiers across heterogeneous robots", "Georgia Tech Research Institute, Atlanta, 30318 USA", "Georgia Tech Research Institute", "Georgia Tech Research Institute, Atlanta, 30318 USA", "400 10th St NW, Atlanta, GA 30318, USA", "33.78101090", "-84.40039930", "edu", "", "United States", "2014"], ["Local Associated Features for Pedestrian 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", "", "China", "2014"], ["Incremental Domain Adaptation of Deformable Part-based Models", "", "Universitat Aut\u00f2noma de Barcelona", "Universitat Aut\u00f2noma de Barcelona", "Centre de Visi\u00f3 per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vall\u00e8s, Vall\u00e8s Occidental, BCN, CAT, 08214, Espa\u00f1a", "41.50078110", "2.11143663", "edu", "", "Spain", "2014"], ["Toward Real-Time Pedestrian Detection Based on a Deformable Template Model", "Computer Vision Center, Universitat Aut\u00f2noma de Barcelona, Cerdanyola del Vall\u00e8s, Spain", "Universitat Aut\u00f2noma de Barcelona", "Universitat Aut\u00f2noma de Barcelona", "Centre de Visi\u00f3 per Computador (CVC), Carrer de l'Albareda, Serraperera, UAB, Cerdanyola del Vall\u00e8s, Vall\u00e8s Occidental, BCN, CAT, 08214, Espa\u00f1a", "41.50078110", "2.11143663", "edu", "", "Spain", "2014"], ["A stereo cameras setup for pedestrian detection enhancement", "Department of Electrical and Computer Engineering, S\u00e3o Carlos School of Engineering, University of S\u00e3o Paulo, S\u00e3o Carlos, Brazil", "University of S\u00e3o Paulo", "University of S\u00e3o Paulo", "S\u00e3o Paulo - State of S\u00e3o Paulo, Brazil", "-23.56139910", "-46.73078910", "edu", "", "Brazil", "2017"], ["Multi-patch deep features for power line insulator status classification from aerial images", "School of Electrical and Electronic Engineering, North China Electric Power University, Baoding, China", "North China Electric Power University", "North China Electric Power University", "\u534e\u5317\u7535\u529b\u5927\u5b66, \u6c38\u534e\u5317\u5927\u8857, \u83b2\u6c60\u533a, \u4fdd\u5b9a\u5e02, \u83b2\u6c60\u533a (Lianchi), \u4fdd\u5b9a\u5e02, \u6cb3\u5317\u7701, 071000, \u4e2d\u56fd", "38.87604460", "115.49738730", "edu", "", "China", "2016"], ["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", "", "United States", "2015"], ["Low-resolution pedestrian detection via a novel resolution-score discriminative surface", "National Engineering Research Center for Multimedia Software, Wuhan University, China", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2017"], ["Occlusion reasoning for object detection under arbitrary viewpoint", "", "Robotics Institute", "Robotics Institute", "Institute for Field Robotics, \u0e1b\u0e23\u0e30\u0e0a\u0e32\u0e2d\u0e38\u0e17\u0e34\u0e28, \u0e01\u0e23\u0e38\u0e07\u0e40\u0e17\u0e1e\u0e21\u0e2b\u0e32\u0e19\u0e04\u0e23, \u0e40\u0e02\u0e15\u0e23\u0e32\u0e29\u0e0e\u0e23\u0e4c\u0e1a\u0e39\u0e23\u0e13\u0e30, \u0e01\u0e23\u0e38\u0e07\u0e40\u0e17\u0e1e\u0e21\u0e2b\u0e32\u0e19\u0e04\u0e23, 10140, \u0e1b\u0e23\u0e30\u0e40\u0e17\u0e28\u0e44\u0e17\u0e22", "13.65450525", "100.49423171", "edu", "", "Thailand", "2012"], ["Online Cross-Modal Adaptation for Audio\u2013Visual Person Identification With Wearable Cameras", "Centre for Intelligent Sensing, Queen Mary University of London, London, U.K.", "Queen Mary University of London", "Queen Mary University of London", "Queen Mary (University of London), Mile End Road, Globe Town, Mile End, London Borough of Tower Hamlets, London, Greater London, England, E1 4NS, UK", "51.52472720", "-0.03931035", "edu", "", "United Kingdom", "2017"], ["A pipelined multi-softcore approach for the HOG algorithm", "University of S\u00e3o Paulo, S\u00e3o Carlos, Brazil", "University of S\u00e3o Paulo", "University of S\u00e3o Paulo", "S\u00e3o Paulo - State of S\u00e3o Paulo, Brazil", "-23.56139910", "-46.73078910", "edu", "", "Brazil", "2016"], ["Efficient Point Process Inference for Large-Scale Object Detection", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2016"], ["Moving Pedestrian Detection Using Normed Proposals and Key Points Matching", "", "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", "", "China", "2016"], ["ZoomNet: Deep Aggregation Learning for High-Performance Small Pedestrian 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", "", "China", "2018"], ["Using context to improve cascaded pedestrian detection", "", "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", "", "United States", "2014"], ["A general method for sensitive identification detection in the terrorist video", "Beijing Jiaotong University, Beijing, China", "Beijing Jiaotong University", "Beijing Jiaotong University", "\u5317\u4eac\u4ea4\u901a\u5927\u5b66, \u94f6\u674f\u5927\u9053, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100044, \u4e2d\u56fd", "39.94976005", "116.33629046", "edu", "", "China", "2015"], ["Adaptive Structural Model for Video Based Pedestrian 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", "", "China", "2014"], ["Convolutional Channel Features : Tailoring CNN to Diverse Tasks", "", "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", "", "China", "2015"], ["Double Phase Pedestrian Detection with Minimal Number of False Positives per Image", "Electronics and Telecommunications Research Institute, Youga, Dalsung, Daegu, Korea", "Electronics and Telecommunications Research Institute, Youga, Dalsung, Daegu, Korea", "Electronics and Telecommunications Research Institute, Youga, Dalsung, Daegu, Korea", "1110-6 Oryong-dong, Buk-gu, Kwangju, South Korea", "35.22537080", "126.84618340", "edu", "", "", "2017"], ["Hierarchical detection of persons in groups", "Universidad Autonoma de Madrid, Madrid, Spain", "Universidad Autonoma de Madrid", "Universidad Autonoma de Madrid", "Facultad de Medicina de la Universidad Aut\u00f3noma de Madrid, Calle de Arturo Duperier, Fuencarral, Fuencarral-El Pardo, Madrid, \u00c1rea metropolitana de Madrid y Corredor del Henares, Comunidad de Madrid, 28001, Espa\u00f1a", "40.48256135", "-3.69060790", "edu", "", "Spain", "2017"], ["A new IoT combined body detection of people by using computer vision for security application", "Dept of Computer Engineering, Firat University, Elazig, Turkey", "Firat University", "Firat University", "Erzincan \u00dcniversitesi Hukuk Fak\u00fcltesi Dekanl\u0131\u011f\u0131, Sivas-Erzincan yolu, \u00dc\u00e7konak, Erzincan, Erzincan merkez, Erzincan, Do\u011fu Anadolu B\u00f6lgesi, 24000, T\u00fcrkiye", "39.72750370", "39.47127034", "edu", "", "Turkey", "2017"], ["Unveiling contrast in darkness", "", "University of Malaya", "University of Malaya", "UM, Lingkaran Wawasan, Bukit Pantai, Bangsar, KL, 50603, Malaysia", "3.12267405", "101.65356103", "edu", "", "Malaysia", "2015"], ["Reconstruction error based pedestrian detection in infrared videos", "Science and Technology on Information, Systems Engineering Laboratory, Nanjing 210007, China", "Systems Engineering Laboratory, Nanjing, China", "Science and Technology on Information, Systems Engineering Laboratory, Nanjing 210007, China", "Qinhuai, Nanjing, Jiangsu, China, 210007", "32.01814510", "118.83728030", "edu", "", "China", "2015"], ["Information Fusion on Oversegmented Images: An Application for Urban Scene Understanding", "", "Peking University", "Peking University", "\u5317\u4eac\u5927\u5b66, 5\u53f7, \u9890\u548c\u56ed\u8def, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100871, \u4e2d\u56fd", "39.99223790", "116.30393816", "edu", "", "China", "2013"], ["Training-free moving object detection system based on hierarchical color-guided motion segmentation", "SPS-VCA, TU/e, 5600 MB Eindhoven, the Netherlands", "SPS-VCA, TU/e, 5600 MB Eindhoven, the Netherlands", "SPS-VCA, TU/e, 5600 MB Eindhoven, the Netherlands", "5612 AZ Eindhoven, Netherlands", "51.44860980", "5.49071480", "edu", "", "Netherlands", "2015"], ["Normalized Autobinomial Markov Channels For Pedestrian Detection", "", "University Politehnica of Bucharest", "University Politehnica of Bucharest", "Universitatea Politehnica din Bucure\u0219ti, Novum Invest, Bucure\u0219ti, Militari, Sector 6, Municipiul Bucure\u0219ti, 060042, Rom\u00e2nia", "44.43918115", "26.05044565", "edu", "", "Romania", "2015"], ["An end-to-end generative adversarial network for crowd counting under complicated scenes", "Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai 200240, China", "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", "", "China", "2017"], ["Efficient multiclass object detection: Detecting pedestrians and bicyclists in a truck's blind spot camera", "EAVISE, Technology Campus De Nayer, KU Leuven, Belgium", "EAVISE, Technology Campus De Nayer, KU Leuven, Belgium", "EAVISE, Technology Campus De Nayer, KU Leuven, Belgium", "Jan Pieter de Nayerlaan 5, 2860 Sint-Katelijne-Waver, Belgium", "51.06802560", "4.50002790", "edu", "", "", "2015"], ["Motorbike theft detection based on object detection and human activity recognition", "University of Information Technology, Vietnam", "University of Information Technology, Vietnam", "University of Information Technology, Vietnam", "Khu ph\u1ed1 6 P, Vietnam", "10.87030000", "106.80345130", "edu", "", "Vietnam", "2013"], ["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", "", "Germany", ""], ["A robust person detector for overhead views", "Electronics and Computer Science, Southampton University, UK", "Southampton University", "Southampton University, Southampton, UK", "University of Southampton, 12 University Rd, Southampton SO17 1BJ, UK", "50.93657970", "-1.39601690", "edu", "", "United Kingdom", "2012"], ["Incremental learning for bootstrapping object classifier models", "ENSTA ParisTech, UIIS Lab University of Paris-Saclay, 91762 Palaiseau, France", "UIIS Lab University of Paris-Saclay", "ENSTA ParisTech, UIIS Lab University of Paris-Saclay, 91762 Palaiseau, France", "828 Boulevard des Mar\u00e9chaux, 91120 Palaiseau, France", "48.71073390", "2.21805010", "edu", "", "France", "2016"], ["Single-Pedestrian Detection Aided by Multi-pedestrian Detection", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2013"], ["Partially Occluded Pedestrian Classification using Three Stage Cascaded Classifier", "Department of Electrical Engineering, Faculty of Engineering, Aswan University, Egypt", "Aswan University", "Faculty of Science, Aswan University, Egypt", ".\u060c SAHARY\u060c Aswan Governorate, Egypt", "23.99786700", "32.85839500", "edu", "", "Egypt", "2014"], ["Occlusion-Aware R-CNN: Detecting Pedestrians in a Crowd", "", "Macau University of Science and Technology", "Macau University of Science and Technology", "Universidade de Ci\u00eancia e Tecnologia de Macau \u6fb3\u9580\u79d1\u6280\u5927\u5b78 Macau University of Science and Technology, \u5049\u9f8d\u99ac\u8def Avenida Wai Long, \u6c39\u4ed4Taipa, \u6c39\u4ed4\u820a\u57ce\u5340 Vila de Taipa, \u5609\u6a21\u5802\u5340 Nossa Senhora do Carmo, \u6c39\u4ed4 Taipa, \u6fb3\u9580 Macau, 853, \u4e2d\u56fd", "22.15263985", "113.56803206", "edu", "", "China", "2018"], ["Spatiotemporal Stacked Sequential Learning for Pedestrian Detection", "", "Computer Vision Center, Barcelona", "Computer Vision Center, Barcelona", "Campus UAB, Edifici O, s/n, 08193 Cerdanyola del Vall\u00e8s, Barcelona, Spain", "41.50089570", "2.11155300", "edu", "", "Spain", "2015"], ["Pattern Recognition and Image Analysis", "University of Alicante, Spain", "University of Alicante", "University of Alicante, Alicante, Spain", "Carretera de San Vicente del Raspeig, s/n, 03690 San Vicente del Raspeig, Alicante, Spain", "38.38524460", "-0.51431610", "edu", "", "Spain", "2013"], ["Multichannel-Sniffing-System for Real-World Analysing of Wi-Fi-Packets", "University of Applied Sciences Erfurt, Applied Computer Science, Erfurtn, Germany", "University of Applied Sciences Erfurt", "University of Applied Sciences Erfurt, Applied Computer Science, Erfurtn, Germany", "Altonaer Str. 25, 99085 Erfurt, Germany", "50.98479130", "11.04149510", "edu", "", "Germany", "2018"], ["Is Faster R-CNN Doing Well for Pedestrian Detection?", "", "Microsoft", "Microsoft Corporation, Redmond, WA, USA", "One Microsoft Way, Redmond, WA 98052, USA", "47.64233180", "-122.13693020", "company", "", "United States", "2016"], ["Analysing of key point description applied in the pedestrian path detection in low resolution images", "Shri JJT University, Rajasthan", "Shri JJT University", "Shri JJT University, Rajasthan", "Jhunjhunu, Churu Road, Vidyanagari, Churela, Rajasthan 333001, India", "28.17676300", "75.24554380", "edu", "", "India", "2017"], ["Foreign object detection ( FOD ) using multi-class classifier with single camera vs . distance map with stereo configuration", "", "Iowa State University", "Iowa State University", "Iowa State University, Farm House Road, Ames, Story County, Iowa, 50014, USA", "42.02791015", "-93.64464415", "edu", "", "United States", "2016"], ["Word Channel Based Multiscale Pedestrian Detection without Image Resizing and Using Only One Classifier", "", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2014"], ["Intelligent Pedestrian Detection u sing Optical Flow and HOG", "", "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", "", "Pakistan", "2016"], ["Pedestrian detection in depth images using framelet regularization", "College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, P. R. China", "Shenzhen University", "Shenzhen University", "\u6df1\u5733\u5927\u5b66, 3688, \u5357\u6d77\u5927\u9053, \u86c7\u53e3, \u540c\u4e50\u6751, \u5357\u5c71\u533a, \u6df1\u5733\u5e02, \u5e7f\u4e1c\u7701, 518060, \u4e2d\u56fd", "22.53521465", "113.93159110", "edu", "", "China", "2012"], ["Local Decorrelation For Improved Detection", "", "Microsoft", "Microsoft Corporation, Redmond, WA, USA", "One Microsoft Way, Redmond, WA 98052, USA", "47.64233180", "-122.13693020", "company", "", "United States", "2014"], ["Semantic Amodal Segmentation", "", "Rutgers University", "Rutgers University", "Rutgers Cook Campus - North, Biel Road, New Brunswick, Middlesex County, New Jersey, 08901, USA", "40.47913175", "-74.43168868", "edu", "", "United States", "2017"], ["PCN: Part and Context Information for Pedestrian Detection with CNNs", "", "University of Edinburgh", "University of Edinburgh", "New College, New College Courtyard, The Mound, Old Town, Edinburgh, City of Edinburgh, Scotland, EH1 2LX, UK", "55.94951105", "-3.19534913", "edu", "", "United Kingdom", "2017"], ["Autonomous Navigation Control for Quadrotors in Trajectories Tracking", "IOC Research Institute, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "IOC Research Institute, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "IOC Research Institute, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "Campus Nord, Carrer de Jordi Girona, 1, 3, 08034 Barcelona, Spain", "41.38800400", "2.11328040", "edu", "", "Spain", "2017"], ["High performance and fast object detection in road environments", "DGIST", "DGIST", "DGIST", "South Korea, Daegu, Dalseong-gun, Yuga-myeon, \ud14c\ud06c\ub178\uc911\uc559\ub300\ub85c 333", "35.70528600", "128.45710200", "edu", "", "South Korea", "2017"], ["Low-light pedestrian detection from RGB images using multi-modal knowledge distillation", "Harman International Industries, India", "Harman International Industries, India", "Harman International Industries, India", "Hiranandani Gardens, Powai, Mumbai, Maharashtra 400076, India", "19.11088100", "72.90829900", "edu", "", "India", "2017"], ["An Efficient Vision-Based Pedestrian Detection and Tracking System for ITS Applications", "", "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", "", "Canada", "2014"], ["Exploiting Learning and Scenario-Based Specification Languages for the Verification and Validation of Highly Automated Driving", "Robert Bosch GmbH, Abstatt, Germany", "Robert Bosch GmbH, Abstatt, Germany", "Robert Bosch GmbH, Abstatt, Germany", "Robert-Bosch-Allee 1, 74232 Abstatt, Germany", "49.07683180", "9.30466890", "company", "", "Germany", "2018"], ["Vision-based formation for UAVs", "Temasek Laboratories, National University of Singapore, 117411 Singapore", "National University of Singapore", "National University of Singapore", "NUS, Former 1936 British Outpost, Nepal Hill, Clementi, Southwest, 117542, Singapore", "1.29620180", "103.77689944", "edu", "", "Singapore", "2014"], ["Car-to-Pedestrian Communication Safety System Based on the Vehicular Ad-Hoc Network Environment: A Systematic Review", "", "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", "", "China", "2017"], ["Pedestrian detection with dynamic iterative bootstrapping", "Communication and Information Security Lab, Institute of Big Data Technologies, Shenzhen Graduate School, Peking University", "Peking University", "Peking University", "\u5317\u4eac\u5927\u5b66, 5\u53f7, \u9890\u548c\u56ed\u8def, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100871, \u4e2d\u56fd", "39.99223790", "116.30393816", "edu", "", "China", "2017"], ["Pedestrian detection via a leg-driven physiology framework", "Western Kentucky University, Department of Computer Science, Ogden College of Science & Engineering, Bowling Green, KY 42101, USA", "Western Kentucky University", "Western Kentucky University", "Western Kentucky University, Avenue of Champions, Bowling Green, Warren County, Kentucky, 42101, USA", "36.98453170", "-86.45764430", "edu", "", "United States", "2016"], ["Pedestrian detection aided by deep learning semantic tasks", "", "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", "", "China", "2015"], ["A Layered Approach for Robust Spatial Virtual Human Pose Reconstruction Using a Still Image", "", "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", "", "China", "2016"], ["Contour-based Pedestrian Detection with Foreground Distribution Trend Filtering and Tracking", "", "National Cheng Kung University", "National Cheng Kung University", "\u6210\u5927, 1, \u5927\u5b78\u8def, \u5927\u5b78\u91cc, \u524d\u7532, \u6771\u5340, \u81fa\u5357\u5e02, 70101, \u81fa\u7063", "22.99919160", "120.21625134", "edu", "", "Taiwan", "2015"], ["Dense disparity map-based pedestrian detection for intelligent vehicle", "IoT and Robotics Convergence Research Division, Daegu Gyeongbuk Institute of Science & Technology (DGIST) Daegu, Republic of Korea", "IoT and Robotics Convergence Research Division, Daegu Gyeongbuk Institute of Science & Technology", "IoT and Robotics Convergence Research Division, Daegu Gyeongbuk Institute of Science & Technology (DGIST) Daegu, Republic of Korea", "South Korea, Daegu, Dalseong-gun, Yuga-myeon, \ud14c\ud06c\ub178\uc911\uc559\ub300\ub85c 333", "35.70528600", "128.45710200", "edu", "", "South Korea", "2016"], ["Analysis of Multi-planar Probability Maps for People Localization in Overlapping Camera Systems", "Sorbonne Universites, UPMC, Univ Paris 06 and CNRS, UMR 7222, ISIR, F-75005, Paris, France", "UPMC, France", "Sorbonne Universites, UPMC, Univ Paris 06 and CNRS, UMR 7222, ISIR, F-75005, Paris, France", "4 Place Jussieu, 75005 Paris, France", "48.84710360", "2.35749900", "edu", "", "France", "2014"], ["LIDAR and vision based pedestrian detection and tracking system", "National University of Defense Technology, Changsha, Hunan Prov., China", "National University of Defense Technology, China", "National University of Defence Technology, Changsha 410000, China", "\u56fd\u9632\u79d1\u5b66\u6280\u672f\u5927\u5b66, \u4e09\u4e00\u5927\u9053, \u5f00\u798f\u533a, \u5f00\u798f\u533a (Kaifu), \u957f\u6c99\u5e02 / Changsha, \u6e56\u5357\u7701, 410073, \u4e2d\u56fd", "28.22902090", "112.99483204", "mil", "", "China", "2015"], ["An Occlusion-Robust Feature Selection Framework in Pedestrian Detection \u2020", "", "Shandong University", "Shandong University", "\u5c71\u4e1c\u5927\u5b66, \u6cf0\u5b89\u8857, \u9ccc\u5c71\u536b\u8857\u9053, \u5373\u58a8\u533a, \u9752\u5c9b\u5e02, \u5c71\u4e1c\u7701, 266200, \u4e2d\u56fd", "36.36934730", "120.67381800", "edu", "", "China", "2018"], ["Live video synopsis for multiple cameras", "", "Hebrew University of Jerusalem", "The Hebrew University of Jerusalem", "\u05d4\u05d0\u05d5\u05e0\u05d9\u05d1\u05e8\u05e1\u05d9\u05d8\u05d4 \u05d4\u05e2\u05d1\u05e8\u05d9\u05ea \u05d1\u05d9\u05e8\u05d5\u05e9\u05dc\u05d9\u05dd, Reagan Plaza, \u05e7\u05e8\u05d9\u05ea \u05de\u05e0\u05d7\u05dd \u05d1\u05d2\u05d9\u05df, \u05d4\u05e8 \u05d4\u05e6\u05d5\u05e4\u05d9\u05dd, \u05d9\u05e8\u05d5\u05e9\u05dc\u05d9\u05dd, \u05de\u05d7\u05d5\u05d6 \u05d9\u05e8\u05d5\u05e9\u05dc\u05d9\u05dd, NO, \u05d9\u05e9\u05e8\u05d0\u05dc", "31.79185550", "35.24472300", "edu", "", "Israel", "2015"], ["Fast and robust detection and tracking of multiple persons on RGB-D data fusing spatio-temporal information", "Dept. of Informatics, University of Hamburg, Germany", "Universit\u00e4t Hamburg", "Universit\u00e4t Hamburg", "Informatikum, 30, Vogt-K\u00f6lln-Stra\u00dfe, Stellingen, Eimsb\u00fcttel, Hamburg, 22527, Deutschland", "53.59948200", "9.93353436", "edu", "", "Germany", "2015"], ["Visual object detection by parts-based modeling using extended histogram of gradients", "", "Singapore", "Singapore", "Singapore", "1.35208300", "103.81983600", "edu", "", "Singapore", "2013"], ["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", "", "Canada", "2018"], ["Pedestrian Detection with RCNN", "", "Stanford University", "Stanford University", "Stanford University, Memorial Way, Stanford, Santa Clara County, California, 94305-6015, USA", "37.43131385", "-122.16936535", "edu", "", "United States", "2015"], ["Hybrid human-machine vision systems: image annotation using crowds, experts and machines", "", "California Institute of Technology", "California Institute of Technology", "California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA", "34.13710185", "-118.12527487", "edu", "", "United States", "2012"], ["Multi-modal people tracking on a mobile companion robot", "Neuroinformatics and Cognitive Robotics Lab, Ilmenau University of Technology, 98684 Ilmenau, Germany", "Ilmenau University of Technology", "Ilmenau University of Technology, Neuroinformatics and Cognitive Robotics Lab, 98684, Germany", "Ilmenau, Germany", "50.68435020", "10.92547280", "edu", "", "Germany", "2013"], ["Normalized channel features for accurate pedestrian detection", "Osaka University, Graduate School of Information Science and Technology, 1-5 Yamadaoka, Suita, Osaka, 565-0871, Japan", "Osaka University", "Osaka University", "\u5927\u962a\u5927\u5b66\u6e05\u660e\u5bee, \u670d\u90e8\u897f\u753a\u56db\u4e01\u76ee, \u8c4a\u4e2d\u5e02, \u5927\u962a\u5e9c, \u8fd1\u757f\u5730\u65b9, \u65e5\u672c", "34.80809035", "135.45785218", "edu", "", "Japan", "2014"], ["Cascade classifiers based robust pedestrian detection", "Universitat de Barcelona, Barcelona, Espa\u00f1a", "Universitat de Barcelona, Barcelona, Espa\u00f1a", "Universitat de Barcelona, Barcelona, Espa\u00f1a", "Gran Via de les Corts Catalanes, 585, 08007 Barcelona, Spain", "41.38660800", "2.16402000", "edu", "", "Spain", "2017"], ["Insatiate boosted forest: Towards data exploitation in object detection", "Delphi Deutschland GmbH", "Delphi Deutschland GmbH", "Delphi Deutschland GmbH", "Delphipl. 1, 42119 Wuppertal, Germany", "51.23524380", "7.15931320", "company", "", "Germany", "2017"], ["Weakly supervised pedestrian detector training by unsupervised prior learning and cue fusion in videos", "University of Leeds Leeds, UK", "University of Leeds Leeds", "University of Leeds Leeds, UK", "Leeds LS2 9JT, UK", "53.80668150", "-1.55503280", "edu", "", "United Kingdom", "2014"], ["Combining background subtraction and temporal persistency in pedestrian detection from static videos", "", "NICTA", "NICTA", "1111 E Touhy Ave #400, Des Plaines, IL 60018, USA", "42.00877410", "-87.89585490", "edu", "", "United States", "2013"], ["Context-Based Path Prediction for Targets with Switching Dynamics", "Department of Environment Perception, Daimler AG, Ulm, Germany", "Delft University of Technology", "Delft University of Technology", "TU Delft, Mekelweg, TU-wijk, Delft, Zuid-Holland, Nederland, 2628, Nederland", "51.99882735", "4.37396037", "edu", "", "Netherlands", "2018"], ["Construction of a bird image dataset for ecological investigations", "", "University of Tokyo", "University of Tokyo", "\u6771\u4eac\u5927\u5b66 \u67cf\u30ad\u30e3\u30f3\u30d1\u30b9, \u5b66\u878d\u5408\u306e\u9053, \u67cf\u5e02, \u5343\u8449\u770c, \u95a2\u6771\u5730\u65b9, 277-8583, \u65e5\u672c", "35.90204480", "139.93622009", "edu", "", "Japan", "2015"], ["Reduce false positives for human detection by a priori probability in videos", "Key Laboratory of System Control and Information Processing, Department of Automation, Shanghai Jiao Tong University, 800 Dongchuan RD, Shanghai 200240, China", "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", "", "China", "2015"], ["Comparison of Visual Datasets for Machine Learning", "", "Florida International University", "Florida International University", "FIU, Southwest 14th Street, Sweetwater, University Park, Miami-Dade County, Florida, 33199, USA", "25.75533775", "-80.37628897", "edu", "", "United States", "2017"], ["Improving the performance of pedestrian detectors using convolutional learning", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2017"], ["Car Detection in Aerial Images of Dense Urban Areas", "Imperial College London, London, U.K.", "Imperial College London", "Imperial College London", "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "51.49887085", "-0.17560797", "edu", "", "United Kingdom", "2018"], ["Pedestrian Counting with Occlusion Handling Using Stereo Thermal Cameras", "", "Aalborg University", "Aalborg University", "AAU, Pontoppidanstr\u00e6de, S\u00f8nder Tranders, Aalborg, Aalborg Kommune, Region Nordjylland, 9220, Danmark", "57.01590275", "9.97532827", "edu", "", "Denmark", "2016"], ["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", "", "Canada", "2013"], ["Shadow removal for pedestrian detection and tracking in indoor environments", "School of Information Science and Engineering, Xiamen University, Xiamen, China", "Xiamen University", "Xiamen University", "\u53a6\u95e8\u5927\u5b66, \u601d\u660e\u5357\u8def Siming South Road, \u601d\u660e\u533a, \u601d\u660e\u533a (Siming), \u53a6\u95e8\u5e02 / Xiamen, \u798f\u5efa\u7701, 361005, \u4e2d\u56fd", "24.43994190", "118.09301781", "edu", "", "China", "2016"], ["A new edge feature for head-shoulder detection", "Institute of Information Science, Beijing Jiaotong University, Beijing, China", "Institute of Information Science", "Institute of Information Science", "\u8cc7\u8a0a\u79d1\u5b78\u7814\u7a76\u6240, \u6578\u7406\u5927\u9053, \u4e2d\u7814\u91cc, \u5357\u6e2f\u5b50, \u5357\u6e2f\u5340, \u81fa\u5317\u5e02, 11574, \u81fa\u7063", "25.04107280", "121.61475620", "edu", "", "Taiwan", "2013"], ["Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "Germany", "2017"], ["Deep Learning Framework for Pedestrian Collision Avoidance System (PeCAS)", "", "University of Massachusetts", "University of Massachusetts", "University of Massachusetts, Hicks Way, Amherst, Hampshire, Massachusetts, 01003, USA", "42.38897850", "-72.52869870", "edu", "", "United States", "2018"], ["Evaluation of Synthetic Video Data in Machine Learning Approaches for Parking Space Classification", "University of Bochum, Institute for Neural Computation", "University of Bochum", "University of Bochum, Institute for Neural Computation", "Universit\u00e4tsstra\u00dfe 150, 44801 Bochum, Germany", "51.44566590", "7.26160930", "edu", "", "Germany", "2018"], ["Video Inpainting by Jointly Learning Temporal Structure and Spatial Details.", "", "Chinese University of Hong Kong", "Chinese University of Hong Kong", "Hong Kong, \u99ac\u6599\u6c34\u6c60\u65c1\u8def", "22.41626320", "114.21093180", "edu", "", "China", "2018"], ["Cross-connected Networks for Multi-task Learning of Detection and Segmentation", "", "University of Tokyo", "University of Tokyo", "\u6771\u4eac\u5927\u5b66 \u67cf\u30ad\u30e3\u30f3\u30d1\u30b9, \u5b66\u878d\u5408\u306e\u9053, \u67cf\u5e02, \u5343\u8449\u770c, \u95a2\u6771\u5730\u65b9, 277-8583, \u65e5\u672c", "35.90204480", "139.93622009", "edu", "", "Japan", "2018"], ["A Practical Point Cloud Based Road Curb Detection Method for Autonomous Vehicle", "", "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", "", "China", "2017"], ["An ROIs based pedestrian detection system for single images", "Enjoyor Labs, Enjoyor Inc., Hangzhou, China", "Enjoyor Labs, Enjoyor Inc., Hangzhou, China", "Enjoyor Labs, Enjoyor Inc., Hangzhou, China", "Hangzhou, Zhejiang, China", "30.27408400", "120.15507000", "company", "", "China", "2012"], ["A comparative study on street sign detection", "Zhejiang University, Department of Information Science and Electronic Engineering, 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", "", "China", "2012"], ["Bio-inspired heterogeneous architecture for real-time pedestrian detection applications", "TeCIP Institute, Scuola Superiore Sant\u2019Anna, Pisa, Italy", "TeCIP Institute, Scuola Superiore Sant\u2019Anna, Pisa, Italy", "TeCIP Institute, Scuola Superiore Sant\u2019Anna, Pisa, Italy", "1, Via Giuseppe Moruzzi, 1, 56124 Pisa PI, Italy", "43.71925890", "10.42400630", "edu", "", "Italy", "2016"], ["Partially occluded pedestrian classification using part-based classifiers and Restricted Boltzmann Machine model", "Graduate School of Information Science, Department of Media Science, Nagoya University, Japan", "Nagoya University", "Nagoya University", "SuperDARN (Hokkaido West), \u592a\u8f9b\u7b2c1\u652f\u7dda\u6797\u9053, \u9678\u5225\u753a, \u8db3\u5bc4\u90e1, \u5341\u52dd\u7dcf\u5408\u632f\u8208\u5c40, \u5317\u6d77\u9053, \u5317\u6d77\u9053\u5730\u65b9, \u65e5\u672c", "43.53750985", "143.60768225", "edu", "", "Japan", "2013"], ["Body Structure Aware Deep Crowd Counting", "School of Information Science and Technology, ShanghaiTech University, Shanghai, China", "ShanghaiTech University", "ShanghaiTech University", "Yueyang Rd, Xuhui Qu, Shanghai Shi, China", "31.20254500", "121.45308600", "edu", "", "", "2018"], ["Cooperative multi-scale Convolutional Neural Networks for person detection", "Ilmenau University of Technology, Neuroinformatics and Cognitive Robotics Lab, 98684, Germany", "Ilmenau University of Technology", "Ilmenau University of Technology, Neuroinformatics and Cognitive Robotics Lab, 98684, Germany", "Ilmenau, Germany", "50.68435020", "10.92547280", "edu", "", "Germany", "2016"], ["Onboard Video Stabilization for Rotorcrafts", "GREC Research Group, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "GREC Research Group, Universitat Polit\u00e8cnica de Catalunya, Barcelona, Spain", "Campus Nord, Carrer de Jordi Girona, 1, 3, 08034 Barcelona, Spain", "41.38800400", "2.11328040", "edu", "", "Spain", "2017"], ["A texture based mani-fold approach for crowd density estimation using Gaussian Markov Random Field", "Malaviya National Institute of Technology, Jaipur, India", "Malaviya National Institute of Technology, Jaipur, India", "Malaviya National Institute of Technology, Jaipur, India", "Jawahar Lal Nehru Marg, Jhalana Gram, Malviya Nagar, Jaipur, Rajasthan 302017, India", "26.86301440", "75.81059200", "edu", "", "India", "2017"], ["Multi-sensors people detection system for heavy machines", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "rue Roger Coutolenc, 60200 Compi\u00e8gne, France", "49.41522420", "2.81911440", "edu", "", "France", "2014"], ["Video scene analysis: an overview and challenges on deep learning algorithms", "Department of Computer Science, Al Imam Muhamad Ibn Saud Islamic University, Riyadh, Kingdom of Saudi Arabia", "Benha University", "Benha University", "\u0643\u0644\u064a\u0629 \u0627\u0644\u0647\u0646\u062f\u0633\u0629 \u0628\u0634\u0628\u0631\u0627 \u062c\u0627\u0645\u0639\u0629 \u0628\u0646\u0647\u0627, \u0634\u0627\u0631\u0639 \u0627\u0644\u064a\u0627\u0632\u062c\u064a, \u0631\u0648\u0636 \u0627\u0644\u0641\u0631\u062c, \u0627\u0644\u0642\u0627\u0647\u0631\u0629, \u0645\u062d\u0627\u0641\u0638\u0629 \u0627\u0644\u0642\u0627\u0647\u0631\u0629, 2466, \u0645\u0635\u0631", "30.08187270", "31.24454841", "edu", "", "Egypt", "2017"], ["Moving pedestrian detection based on motion segmentation", "University of 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", "", "Germany", "2013"], ["Pedestrian detection from thermal images with a scattered difference of directional gradients feature descriptor", "Research Centre for Smart Vehicles, Toyota Technological Institute, Nagoya, Aichi 468-8511, Japan", "Toyota Technological Institute", "Toyota Technological Institute", "6045 S Kenwood Ave, Chicago, IL 60637, USA", "41.78469820", "-87.59258480", "edu", "", "", "2014"], ["Evaluation of optimum path forest classifier for pedestrian detection", "Sorbonne universit\u00e9s, Universit\u00e9 de technologie de Compi\u00e8gne, CNRS 7253 UMR/Heudiasyc. CS 60319, 60203 Compi\u00e8gne cedex", "Universit\u00e9 de technologie de Compi\u00e8gne", "Sorbonne universit\u00e9s, Universit\u00e9 de technologie de Compi\u00e8gne, CNRS 7253 UMR/Heudiasyc. CS 60319, 60203 Compi\u00e8gne cedex", "57 Avenue de Landshut, 60200 Compi\u00e8gne, France", "49.40187640", "2.79699060", "edu", "", "France", "2015"], ["Vehicles of the Future: A Survey of Research on Safety Issues", "German\u2013Turkish Advanced Research Centre for Information and Communication Technology, Berlin, Germany", "German-Turkish Advanced Research Centre for Information and Communication Technology, Berlin, Germany", "German\u2013Turkish Advanced Research Centre for Information and Communication Technology, Berlin, Germany", "Berlin, Germany", "52.52000660", "13.40495400", "edu", "", "Germany", "2017"], ["Saliency Map Generation by the Convolutional Neural Network for Real-Time Traffic Light Detection Using Template Matching", "Research Centre for Smart Vehicles, Toyota Technological Institute, Nagoya, Japan", "Research Centre for Smart Vehicles, Toyota Technological Institute, Nagoya, Japan", "Research Centre for Smart Vehicles, Toyota Technological Institute, Nagoya, Japan", "2 Chome-12-1 Hisakata, Tenpaku Ward, Nagoya, Aichi Prefecture 468-0034, Japan", "35.10657600", "136.98301800", "edu", "", "Japan", "2015"], ["Fused DNN: A Deep Neural Network Fusion Approach to Fast and Robust Pedestrian Detection", "", "Samsung Electronics", "Samsung Electronics", "25 The West Mall, Etobicoke, ON M9C 1B8, Canada", "43.61294840", "-79.55903030", "edu", "", "Canada", "2017"], ["Efficient Pedestrian Detection at Nighttime Using a Thermal Camera", "", "Yonsei University", "Yonsei University", "\uc5f0\uc138\ub300, \uc5f0\uc138\ub85c, \uc2e0\ucd0c\ub3d9, \ucc3d\ucc9c\ub3d9, \uc11c\ub300\ubb38\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 03789, \ub300\ud55c\ubbfc\uad6d", "37.56004060", "126.93692480", "edu", "", "South Korea", "2017"], ["To boost or not to boost? On the limits of boosted trees for object detection", "", "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", "", "United States", "2016"], ["Extended HOG-CLBC for pedstrain detection", "", "China University of Mining and Technology", "China University of Mining and Technology", "China University of Mining and Technology, 1\u53f7, \u5927\u5b66\u8def, \u6cc9\u5c71\u533a (Quanshan), \u5f90\u5dde\u5e02 / Xuzhou, \u6c5f\u82cf\u7701, 221116, \u4e2d\u56fd", "34.21525380", "117.13985410", "edu", "", "China", "2018"], ["ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd Understanding", "", "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", "", "China", "2018"], ["A comprehensive review on intelligent surveillance systems", "", "King Saud University", "King Saud University", "King Saud University \u062c\u0627\u0645\u0639\u0629 \u0627\u0644\u0645\u0644\u0643 \u0633\u0639\u0648\u062f, road_16, King Saud University District, Al Maather Municipality, \u0627\u0644\u0631\u064a\u0627\u0636, \u0645\u0646\u0637\u0642\u0629 \u0627\u0644\u0631\u064a\u0627\u0636, 12393 4057, \u0627\u0644\u0633\u0639\u0648\u062f\u064a\u0629", "24.72464030", "46.62335012", "edu", "", "Saudi Arabia", "2016"], ["Speed Complexity Pedestrian Driving Highway Lane-Keeping Parking Traffic Jam Urban Driving Racing Circuit", "", "MIT", "Massachusetts Institute", "MIT, Amherst Street, Cambridgeport, Cambridge, Middlesex County, Massachusetts, 02238, USA", "42.35839610", "-71.09567788", "edu", "", "United States", "2017"], ["Extending the Detection Range of Vision-Based Vehicular Instrumentation", "School of Electrical Engineering and Computer Science, DIVA Strategic Research Network, 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", "", "Canada", "2016"], ["Moving object surveillance using object proposals and background prior prediction", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou, China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou, China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou, China", "Hangzhou, Zhejiang, China", "30.27408400", "120.15507000", "edu", "", "China", "2017"], ["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", "", "Romania", "2014"], ["Integrating Orientation Cue With EOH-OLBP-Based Multilevel Features for Human Detection", "Research and Development Department, AnKe Smart City Technology Company Ltd., Shenzhen, China", "Inner Mongolia University", "College of Computer Science, Inner Mongolia University, Hohhot, China", "Saihan, Hohhot, Inner Mongolia, China, 010000", "40.81426100", "111.68929800", "edu", "", "China", "2013"], ["Latent training for convolutional neural networks", "Key Laboratory of System Control and Information Processing, Ministry of Education of China, School of Electron Information and Electrical Engineering, Shanghai Jiao Tong University, China, 200240", "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", "", "China", "2015"], ["Stationary Detection of the Pedestrian?s Intention at Intersections", "Measurement, Control and Mircotechnology , University of Ulm, Ulm, 89075 Germany, Germany", "University of Ulm", "University of Ulm, Control and Microtechnology, Ulm, 89081, Germany", "Helmholtzstra\u00dfe 16, 89081 Ulm, Germany", "48.42223050", "9.95558200", "edu", "", "Germany", "2013"], ["Symbolic road marking recognition using convolutional neural networks", "Nissan Research Center, Silicon Valley, USA", "Nissan Research Center, Silicon Valley, USA", "Nissan Research Center, Silicon Valley, USA", "1215 Bordeaux Dr, Sunnyvale, CA 94089, USA", "37.41036640", "-122.02344020", "company", "", "United States", "2017"], ["Velocity estimation from monocular video for automotive applications using convolutional neural networks", "Nauto Inc., 380 Portage Ave., Palo Alto, CA 94306, USA", "Nauto Inc., Palo Alto, CA", "Nauto Inc., 380 Portage Ave., Palo Alto, CA 94306, USA", "220 Portage Ave, Palo Alto, CA 94306, USA", "37.42406500", "-122.13615230", "edu", "", "United States", "2017"], ["A two-stage training deep neural network for small pedestrian detection", "Graduate School of Science and Engineering, Teikyo University", "Teikyo University", "Teikyo University", "Japan, \u3012173-8605 Tokyo, \u677f\u6a4b\u533a\u52a0\u8cc0\uff12\u4e01\u76ee\uff11\uff11\u2212\uff11", "35.75927460", "139.71450290", "edu", "", "Japan", "2017"], ["Efficient pose machine based on parameter-sensitive hashing", "Shenzhen Tencent Computer System Co. Ltd., Shenzhen, China", "Shenzhen Tencent Computer System Co. Ltd., Shenzhen, China", "Shenzhen Tencent Computer System Co. Ltd., Shenzhen, China", "China, Guangdong, Shenzhen, Keji South 12th Rd, \u98de\u4e9a\u8fbe\u79d1\u6280\u5927\u53a63\u5c42\u30015-10\u5c42\u30011202", "22.53937100", "113.95574800", "edu", "", "China", "2017"], ["Balanced Mixture of Deformable Part Models With Automatic Part Configurations", "Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an, Shaanxi, China", "Xi\u2019an Jiaotong University", "Institute of Information and System Sciences, Faculty of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China", "28 Xianning W Rd, JiaoDa ShangYe JieQu, Beilin Qu, Xian Shi, Shaanxi Sheng, China", "34.25080300", "108.98369300", "edu", "", "China", "2017"], ["Pedestrian detection from traffic scenes based on probabilistic models of the contour fragments", "", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2013"], ["Histograms of Oriented Gradients for Landmine Detection in Ground-Penetrating Radar Data", "Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA", "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", "", "United States", "2014"], ["Person Re-identification in the Wild", "", "University of Technology Sydney", "University of Technology Sydney", "University of Technology Sydney, Omnibus Lane, Ultimo, Sydney, NSW, 2007, Australia", "-33.88096510", "151.20107299", "edu", "", "Australia", "2017"], ["Using Multi-Stage Features in Fast R-CNN for Pedestrian Detection", "Vision Laboratory, LARSyS University of the Algarve, Faro, Portugal", "LARSyS University of the Algarve", "Vision Laboratory, LARSyS University of the Algarve, Faro, Portugal", "Estr. da Penha 139, 8005-139 Faro, Portugal", "37.04397130", "-7.97220790", "edu", "", "Portugal", "2016"], ["Movement direction-based approaches for pedestrian detection in road scenes", "School of Computer Science and Engineering, Chung-Ang University, Seoul, Korea", "Chung-Ang University", "Chung-Ang University", "\uc911\uc559\ub300\ud559\uad50, \uc11c\ub2ec\ub85c15\uae38, \ud751\uc11d\ub3d9, \ub3d9\uc791\uad6c, \uc11c\uc6b8\ud2b9\ubcc4\uc2dc, 06981, \ub300\ud55c\ubbfc\uad6d", "37.50882000", "126.96190000", "edu", "", "South Korea", "2015"], ["THE UNIVERSITY OF CHICAGO OBJECT DETECTION WITH CAD-TRAINED STATISTICAL MODELS FOR THE DEGREE OF MASTER OF SCIENCE DEPARTMENT OF COMPUTER SCIENCE BY GUSTAV LARSSON ADVISOR: YALI AMIT", "", "University of Chicago", "THE UNIVERSITY OF CHICAGO", "University of Chicago, South Ellis Avenue, Woodlawn, Chicago, Cook County, Illinois, 60637, USA", "41.78468745", "-87.60074933", "edu", "", "United States", "2014"], ["The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking", "", "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", "", "United States", "2018"], ["Leveraging Unlabeled Data for Crowd Counting by Learning to Rank", "", "University of Florence", "University of Florence", "Piazza di San Marco, 4, 50121 Firenze FI, Italy", "43.77764260", "11.25976500", "edu", "", "Italy", "2018"], ["Structured forests for pixel-level hand detection and hand part labelling", "", "University of Hong Kong", "University of Hong Kong", "\u6d77\u6d0b\u79d1\u5b78\u7814\u7a76\u6240 The Swire Institute of Marine Science, \u9db4\u5480\u9053 Cape D'Aguilar Road, \u9db4\u5480\u4f4e\u96fb\u53f0 Cape D'Aguilar Low-Level Radio Station, \u77f3\u6fb3 Shek O, \u82bd\u83dc\u5751\u6751 Nga Choy Hang Tsuen, \u5357\u5340 Southern District, \u9999\u6e2f\u5cf6 Hong Kong Island, HK, \u4e2d\u56fd", "22.20814690", "114.25964115", "edu", "", "China", "2015"], ["DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density Estimation", "", "Carnegie Mellon University Silicon Valley", "CARNEGIE MELLON UNIVERSITY", "Carnegie Mellon University Silicon Valley, South Akron Road, ARC, Santa Clara County, California, 94035-0016, USA", "37.41021930", "-122.05965487", "edu", "", "United States", "2018"], ["Pedestrian detection with dilated convolution, region proposal network and boosted decision trees", "College of Electronics & Information Engineering, Tongji University, 201804, Shanghai, China", "Tongji University", "Tongji University", "\u540c\u6d4e\u5927\u5b66, 1239, \u56db\u5e73\u8def, \u6c5f\u6e7e, \u8679\u53e3\u533a, \u4e0a\u6d77\u5e02, 200092, \u4e2d\u56fd", "31.28473925", "121.49694909", "edu", "", "China", "2017"], ["Detecting walking pedestrians from leg motion in driving video", "Transportation Active Safety Institute (TASI), Indiana University-Purdue University Indianapolis, 46202 USA", "Indiana University-Purdue University Indianapolis", "Indiana University-Purdue University Indianapolis, Indianapolis, USA", "420 University Blvd, Indianapolis, IN 46202, USA", "39.77388320", "-86.17633930", "edu", "", "United States", "2014"], ["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", "", "China", "2016"], ["Facial expression recognition under a wide range of head poses", "", "University of Trento", "University of Trento", "University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia", "46.06588360", "11.11598940", "edu", "", "Italy", "2015"], ["Reliable pedestrian detection using a deep neural network trained on pedestrian counts", "Sensing and Industrial Imaging, Siemens Corporate Technology, Munich, Germany", "Sensing and Industrial Imaging, Siemens Corporate Technology, Munich, Germany", "Sensing and Industrial Imaging, Siemens Corporate Technology, Munich, Germany", "Otto-Hahn-Ring 6, 81739 M\u00fcnchen, Germany", "48.09159280", "11.64982970", "edu", "", "Germany", "2017"], ["High-level spatial modeling in convolutional neural network with application to pedestrian detection", "School of Automation, Southeast University, Nanjing 210096, 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", "", "China", "2015"], ["Robot Perception of Human Groups in the Real World: State of the Art", "", "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", "", "United States", "2016"], ["Automatic categorization-based multi-stage pedestrian detection", "Vehicle Engineering Development Div., Toyota Motor Corporation, Japan", "Vehicle Engineering Development Div., Toyota Motor Corporation, Japan", "Vehicle Engineering Development Div., Toyota Motor Corporation, Japan", "Japan", "36.20482400", "138.25292400", "edu", "", "Japan", "2012"], ["Automatic Tuberculosis Screening Using Chest Radiographs", "Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA", "National Institutes of Health", "National Institutes of Health", "NIH, Pooks Hill, Bethesda, Montgomery County, Maryland, USA", "39.00041165", "-77.10327775", "edu", "", "United States", "2014"], ["Video-Based Human Behavior Understanding: A Survey", "Department of Information Engineering and Computer Science, University of Trento, Trento, Italy", "University of Trento", "University of Trento", "University of Trento, Via Giuseppe Verdi, Piedicastello, Trento, Territorio Val d'Adige, TN, TAA, 38122, Italia", "46.06588360", "11.11598940", "edu", "", "Italy", "2013"], ["Full weighting Hough Forests for object detection", "Computer Vision Lab, Inha University, Inha-ro 100, Nam-gu, Incheon, South Korea", "Inha University", "Intelligent Technology Laboratory, Inha University, Incheon, Korea", "100 Inha-ro, Yonghyeon 1(il).4(sa)-dong, Nam-gu, Incheon, South Korea", "37.45002210", "126.65348800", "edu", "", "South Korea", "2014"], ["Learning and Using Taxonomies for Visual and Olfactory Classification", "", "California Institute of Technology", "California Institute of Technology", "California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA", "34.13710185", "-118.12527487", "edu", "", "United States", "2013"], ["Multimodal information fusion for urban scene understanding", "UMR CNRS 7253, Heudiasyc, Universit\u00e9 de Technologie de Compi\u00e8gne, Compi\u00e8gne Cedex, France", "UMR CNRS 7253, Heudiasyc, Universit\u00e9 de Technologie de Compi\u00e8gne, Compi\u00e8gne Cedex, France", "UMR CNRS 7253, Heudiasyc, Universit\u00e9 de Technologie de Compi\u00e8gne, Compi\u00e8gne Cedex, France", "57 Avenue de Landshut, 60200 Compi\u00e8gne, France", "49.40187640", "2.79699060", "edu", "", "France", "2014"], ["Pedestrian detection and tracking using deformable part models and Kalman filtering", "Dept. of Electronics and Communication Engineering, Hanyang University, Sangnok-gu, 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", "", "South Korea", "2012"], ["Deep Learning of Scene-Specific Classifier for Pedestrian Detection", "", "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", "", "China", "2014"], ["A Hardware Architecture for Cell-Based Feature-Extraction and Classification Using Dual-Feature Space", "Research Institute for Nanodevice and Bio Systems, Hiroshima University, Higashi-Hiroshima, Japan", "Hiroshima University", "Hiroshima University", "Hiroshima University\u3000\u5e83\u5cf6\u5927\u5b66 \u6771\u5e83\u5cf6\u30ad\u30e3\u30f3\u30d1\u30b9, \u51fa\u4f1a\u3044\u306e\u9053\u3000Deai-no-michi Str., \u897f\u6761\u4e0b\u898b, \u6771\u5e83\u5cf6\u5e02, \u5e83\u5cf6\u770c, \u4e2d\u56fd\u5730\u65b9, 739-0047, \u65e5\u672c", "34.40197660", "132.71231950", "edu", "", "Japan", "2018"], ["Fast and Accurate Human Detection Using a Cascade of Boosted MS-LBP Features", "School of Computing and Communication, University of Technology, Sydney, Australia", "Nanjing University", "Nanjing University", "NJU, \u4e09\u6c5f\u8def, \u9f13\u697c\u533a, \u5357\u4eac\u5e02, \u6c5f\u82cf\u7701, 210093, \u4e2d\u56fd", "32.05659570", "118.77408833", "edu", "", "China", "2012"], ["Accuracy prediction for pedestrian detection", "Video and Image Processing Lab (VIPER), Purdue University, West Lafayette, Indiana USA", "Purdue University", "Purdue University", "Purdue University, West Stadium Avenue, West Lafayette, Tippecanoe County, Indiana, 47907, USA", "40.43197220", "-86.92389368", "edu", "", "United States", "2017"], ["Towards Reversible De-Identification in Video Sequences Using 3D Avatars and Steganography", "", "University of Zagreb", "University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia", "Unska ul. 3, 10000, Zagreb, Croatia", "45.80112100", "15.97084090", "edu", "", "Croatia", "2015"], ["Pedestrian detection based on Visconti2 7502", "School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, China", "Hangzhou Dianzi University", "Hangzhou Dianzi University", "\u676d\u5dde\u7535\u5b50\u79d1\u6280\u5927\u5b66, 2\u53f7\u5927\u8857, \u767d\u6768\u8857\u9053, \u6c5f\u5e72\u533a (Jianggan), \u676d\u5dde\u5e02 Hangzhou, \u6d59\u6c5f\u7701, 310018, \u4e2d\u56fd", "30.31255250", "120.34309460", "edu", "", "China", "2017"], ["Random Forests of Local Experts for Pedestrian Detection", "", "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", "", "Germany", "2013"], ["A Novel Multi-Feature Descriptor for Human Detection Using Cascaded Classifiers in Static Images", "Department of Computer Science and Engineering, Lehigh University, Bethlehem, USA", "Lehigh University", "Lehigh University", "Lehigh University, Library Drive, Sayre Park, Bethlehem, Northampton County, Pennsylvania, 18015, USA", "40.60680280", "-75.37824880", "edu", "", "United States", "2015"], ["Multiple Human Tracking in RGB-D Data: A Survey", "", "University of Bristol", "University of Bristol", "Victoria Rooms, Whiteladies Road, Cliftonwood, Spike Island, Bristol, City of Bristol, South West England, England, BS8 2PY, UK", "51.45848370", "-2.60977520", "edu", "", "United Kingdom", "2016"], ["Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset", "", "Jiangnan University", "Jiangnan University", "\u6c5f\u5357\u5927\u5b66\u7ad9, \u8821\u6e56\u5927\u9053, \u6ee8\u6e56\u533a, \u5357\u573a\u6751, \u6ee8\u6e56\u533a (Binhu), \u65e0\u9521\u5e02 / Wuxi, \u6c5f\u82cf\u7701, 214121, \u4e2d\u56fd", "31.48542550", "120.27395810", "edu", "", "China", "2018"], ["Using Raspberry Pi for scientific video observation of pedestrians during a music festival", "", "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", "", "Germany", "2015"], ["Deep Perm-Set Net: Learn to predict sets with unknown permutation and cardinality using deep neural networks", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2018"], ["Two Dimensional Visual Tracking in Construction Scenarios", "", "Concordia University", "Concordia University", "Concordia University, 2811, Northeast Holman Street, Concordia, Portland, Multnomah County, Oregon, 97211, USA", "45.57022705", "-122.63709346", "edu", "", "United States", "2017"], ["Harvesting Discriminative Meta Objects with Deep CNN Features for Scene Classification", "", "University of Hong Kong", "University of Hong Kong", "\u6d77\u6d0b\u79d1\u5b78\u7814\u7a76\u6240 The Swire Institute of Marine Science, \u9db4\u5480\u9053 Cape D'Aguilar Road, \u9db4\u5480\u4f4e\u96fb\u53f0 Cape D'Aguilar Low-Level Radio Station, \u77f3\u6fb3 Shek O, \u82bd\u83dc\u5751\u6751 Nga Choy Hang Tsuen, \u5357\u5340 Southern District, \u9999\u6e2f\u5cf6 Hong Kong Island, HK, \u4e2d\u56fd", "22.20814690", "114.25964115", "edu", "", "China", "2015"], ["Warping approach for rearview pedestrian detection with fish eye cameras", "Data Science Research Laboratories, NEC Corporation. Kawasaki, Japan", "Data Science Research Laboratories, NEC Corporation. Kawasaki, Japan", "Data Science Research Laboratories, NEC Corporation. Kawasaki, Japan", "Kawasaki, Kanagawa Prefecture, Japan", "35.52981980", "139.70240390", "company", "", "Japan", "2017"], ["Towards culturally aware robot navigation", "Shenzhen Institute of Advanced Technology", "Shenzhen Institute of Advanced Technology", "Shenzhen Institute of Advanced Technology", "Tengfei Rd, LongGang ZhongXin Cheng, Longgang Qu, Shenzhen Shi, Guangdong Sheng, China, 518172", "22.72147100", "114.21548200", "edu", "", "China", "2016"], ["A Visual Words Selection Strategy for Pedestrian Detection and Analysis of the Feature Points Distribution", "", "Akita Prefectural University", "Akita Prefectural University", "\u79cb\u7530\u770c\u7acb\u5927\u5b66, \u79cb\u7530\u5929\u738b\u7dda, \u6f5f\u4e0a\u5e02, \u79cb\u7530\u770c, \u6771\u5317\u5730\u65b9, 011-0946, \u65e5\u672c", "39.80114990", "140.04591160", "edu", "", "Japan", "2015"], ["Robust visual pedestrian detection by tight coupling to tracking", "IUT d'Orsay, Université de Paris-Sud, Plateau de Moulon, 91400, France", "IUT d'Orsay, Universit\u00e9 de Paris-Sud, Plateau de Moulon, 91400, France", "IUT d'Orsay, Université de Paris-Sud, Plateau de Moulon, 91400, France", "15 Rue Georges Clemenceau, 91400 Orsay, France", "48.69768470", "2.17648390", "edu", "", "France", "2014"], ["Probabilistic Integration of Intensity and Depth Information for Part-Based Vehicle Detection", "INRIA Grenoble Rhône-Alpes, Saint Ismier, France", "INRIA Grenoble", "INRIA Grenoble Rhone-Alpes, FRANCE", "INRIA, 655, Avenue de l'Europe, Innovall\u00e9e Montbonnot, Montbonnot-Saint-Martin, Grenoble, Is\u00e8re, Auvergne-Rh\u00f4ne-Alpes, France m\u00e9tropolitaine, 38330, France", "45.21829860", "5.80703193", "edu", "", "France", "2013"], ["A High Accuracy Pedestrian Detection System Combining a Cascade AdaBoost Detector and Random Vector Functional-Link Net", "", "Chonbuk National University", "Chonbuk National University", "\uc804\ubd81\ub300\ud559\uad50, 567, \ubc31\uc81c\ub300\ub85c, \uae08\uc554\ub3d9, \ub355\uc9c4\uad6c, \uc804\uc8fc\uc2dc, \uc804\ubd81, 54896, \ub300\ud55c\ubbfc\uad6d", "35.84658875", "127.13501330", "edu", "", "South Korea", "2014"], ["Human detection model using feature extraction method in video frames", "Faculty of Engineering and Information Technology, University of Technology, Sydney(UTS) Taibah University", "Sydney Taibah University", "Faculty of Engineering and Information Technology, University of Technology, Sydney(UTS) Taibah University", "15 Broadway, Ultimo NSW 2007, Australia", "-33.88323760", "151.20049420", "edu", "", "Australia", "2016"], ["Learning Cascaded Shared-Boost Classifiers for Part-Based Object Detection", "State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing, China", "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", "", "China", "2014"], ["A convnet for non-maximum suppression", "", "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", "", "Germany", "2016"], ["Pedestrian detection based on DCT of multi-channel feature", "College of Communications Engineering, PLA University, of Science and Technology, Nanjing, China", "PLA University", "College of Communications Engineering, PLA University, of Science and Technology, Nanjing, China", "China, Jiangsu, Nanjing, Xuanwu, \u4e2d\u5c71\u95e8\u5916\u5927\u8857", "32.03522500", "118.85531700", "edu", "", "China", "2017"], ["A multi-configuration part-based person detector", "Video Processing and Understanding Lab, Universidad Autonoma de Madrid, Spain", "Universidad Autonoma de Madrid", "Universidad Autonoma de Madrid", "Facultad de Medicina de la Universidad Aut\u00f3noma de Madrid, Calle de Arturo Duperier, Fuencarral, Fuencarral-El Pardo, Madrid, \u00c1rea metropolitana de Madrid y Corredor del Henares, Comunidad de Madrid, 28001, Espa\u00f1a", "40.48256135", "-3.69060790", "edu", "", "Spain", "2014"], ["Efficient pedestrian detection with enhanced object segmentation in far IR night vision", "Poznan University of Technology, Department of Computing, Division of Signal Processing and Electronic Systems, Pozna\u0144, Poland", "Poznan University of Technology", "Poznan University of Technology", "Dom Studencki nr 3, 3, K\u00f3rnicka, \u015awi\u0119ty Roch, Rataje, Pozna\u0144, wielkopolskie, 61-141, RP", "52.40048370", "16.95158083", "edu", "", "Poland", "2017"], ["Pedestrian Detection Based on Multi-Block Local Binary Pattern and Biologically Inspired Feature", "", "Huazhong University of Science and Technology", "Huazhong University of Science and Technology", "\u534e\u4e2d\u5927, \u73de\u55bb\u8def, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a, \u5173\u4e1c\u8857\u9053, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a\uff08\u6258\u7ba1\uff09, \u6d2a\u5c71\u533a (Hongshan), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430074, \u4e2d\u56fd", "30.50975370", "114.40628810", "edu", "", "China", "2014"], ["Real-time human detection based on gentle MILBoost with variable granularity HOG-CSLBP", "School of Automation, 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", "", "China", "2012"], ["Convolutional neural networks for crowd behaviour analysis: a survey", "Department of Information Technology, Delhi Technological University, Delhi, India", "Central Research Lab, Bharat Electronics Ltd., Ghaziabad, India", "Central Research Lab, Bharat Electronics Ltd., Ghaziabad, India", "Site 4, Maharajpur, Sahibabad Industrial Area Site 4, Sahibabad, Ghaziabad, Uttar Pradesh 201010, India", "28.65508600", "77.33309490", "company", "", "India", "2018"], ["Stixmantics: A Medium-Level Model for Real-Time Semantic Scene Understanding", "", "TU Darmstadt", "TU Darmstadt", "Karolinenpl. 5, 64289 Darmstadt, Germany", "49.87482770", "8.65632810", "edu", "", "Germany", "2014"], ["Unsupervised network pretraining via encoding human design", "", "University of Maryland College Park", "University of Maryland College Park", "University of Maryland, College Park, Farm Drive, Acredale, College Park, Prince George's County, Maryland, 20742, USA", "38.99203005", "-76.94610290", "edu", "", "United States", "2016"], ["Detection of pedestrians at far distance", "Sorbonne Universit\u00e9s, Universit\u00e9 de Technologie de Compi\u00e8gne, CNRS, Heudiasyc Laboratory, France", "Sorbonne Universit\u00e9s, Universit\u00e9 de Technologie de Compi\u00e8gne, CNRS, Heudiasyc Laboratory, France", "Sorbonne Universit\u00e9s, Universit\u00e9 de Technologie de Compi\u00e8gne, CNRS, Heudiasyc Laboratory, France", "57 Avenue de Landshut, 60200 Compi\u00e8gne, France", "49.40075300", "2.79528080", "edu", "", "France", "2016"], ["State estimation for tracking in image space with a de- and re-coupled IMM filter", "Fraunhofer IOSB, Ettlingen, Germany", "Fraunhofer IOSB, Ettlingen, Germany", "Fraunhofer IOSB, Ettlingen, Germany", "Gutleuthausstra\u00dfe 1, 76275 Ettlingen, Germany", "48.94744960", "8.41171790", "company", "", "", "2017"], ["Hierarchical Feature Pooling with Structure Learning: A New Method for Pedestrian Detection", "", "University of Missouri", "University of Missouri", "L1, Maguire Boulevard, Lemone Industrial Park, Columbia, Boone County, Missouri, 65201, USA", "38.92676100", "-92.29193783", "edu", "", "United States", "2013"], ["Pedestrian Movement Direction Recognition Using Convolutional Neural Networks", "University of Alicante, Alicante, Spain", "University of Alicante", "University of Alicante, Alicante, Spain", "Carretera de San Vicente del Raspeig, s/n, 03690 San Vicente del Raspeig, Alicante, Spain", "38.38524460", "-0.51431610", "edu", "", "Spain", "2017"], ["DIOD: Fast, Semi-Supervised Deep ISAR Object Detection", "Shaanxi Rural Commercial Bank Co., Ltd., Shangluo, China", "Shaanxi Rural Commercial Bank Co., Ltd., Shangluo, China", "Shaanxi Rural Commercial Bank Co., Ltd., Shangluo, China", "Shangluo, Shaanxi, China", "33.87042200", "109.94047700", "company", "", "China", "2019"], ["Filtered channel features for pedestrian detection", "", "MPI Informatics, Saarbr\u00fccken, Germany", "MPI Informatics, Saarbr\u00fccken, Germany", "Campus E1 4, 66123, Stuhlsatzenhausweg, 66123 Saarbr\u00fccken, Germany", "49.25786570", "7.04579560", "company", "", "Germany", "2015"], ["Robust 3-D Human Detection in Complex Environments With a Depth Camera", "School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore", "Nanyang Technological University", "Nanyang Technological University", "NTU, Faculty Avenue, Jurong West, Southwest, 637460, Singapore", "1.34841040", "103.68297965", "edu", "", "Singapore", "2018"], ["Pedestrian detection in infrared images using HOG, LBP, gradient magnitude and intensity feature channels", "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", "", "Romania", "2014"], ["Pedestrian Tracking Using Online Boosted Random Ferns Learning in Far-Infrared Imagery for Safe Driving at Night", "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", "", "South Korea", "2017"], ["Structural inpainting of road patches for anomaly detection", "IBM Research - Tokyo, Japan", "IBM Research - Tokyo, Japan", "IBM Research - Tokyo, Japan", "19-21 Nihonbashihakozakicho, Ch\u016b\u014d, Tokyo 103-8510, Japan", "35.67854170", "139.78712380", "company", "", "Japan", "2015"], ["Boosting algorithms for detector cascade learning", "", "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", "", "United States", "2014"], ["A Graded Offline Evaluation Framework for Intelligent Vehicle\u2019s Cognitive Ability", "Institute of Artificial Intelligence and Robotics, Xi\u2019an Jiaotong University, Xi\u2019an, China", "Xi'an Jiaotong University", "Xi'an Jiaotong University", "\u897f\u5b89\u4ea4\u901a\u5927\u5b66\u5174\u5e86\u6821\u533a, \u6587\u6cbb\u8def, \u4e50\u5c45\u573a, \u7891\u6797\u533a (Beilin), \u897f\u5b89\u5e02, \u9655\u897f\u7701, 710048, \u4e2d\u56fd", "34.24749490", "108.97898751", "edu", "", "China", "2018"], ["Exploring Weak Stabilization for Motion Feature Extraction", "", "Microsoft", "Microsoft Corporation, Redmond, WA, USA", "One Microsoft Way, Redmond, WA 98052, USA", "47.64233180", "-122.13693020", "company", "", "United States", "2013"], ["Did You See Me?: Assessing Perceptual vs. Real Driving Gains Across Multi-Modal Pedestrian Alert Systems", "Virginia Tech", "Virginia Tech", "Virginia Tech", "Blacksburg, VA 24061, USA", "37.22838430", "-80.42341670", "edu", "", "United States", "2017"], ["Aerial Imagery for Roof Segmentation: A Large-Scale Dataset towards Automatic Mapping of Buildings", "", "University of Waterloo", "University of Waterloo", "University of Waterloo, 200, University Avenue West, Northdale, Beechwood, Waterloo, Regional Municipality of Waterloo, Ontario, N2L 3G1, Canada", "43.47061295", "-80.54724732", "edu", "", "Canada", "2018"], ["Joint Human Detection and Head Pose Estimation via Multistream Networks for RGB-D Videos", "University of Maryland, School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing, Fudan University, College Park, Shanghai, MD, USAChina", "University of Maryland", "University of Maryland", "The Grand Garage, 5, North Paca Street, Seton Hill, Baltimore, Maryland, 21201, USA", "39.28996850", "-76.62196103", "edu", "", "United States", "2017"], ["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", "", "United States", "2018"], ["Machine to Machine Perception for Safer Traffic", "", "University of Groningen", "University of Groningen", "Academiegebouw, Professorgang, Binnenstad, Groningen, Nederland, 9712EA, Nederland", "53.21967825", "6.56251482", "edu", "", "Netherlands", "2013"], ["Embedded vision system for pedestrian detection based on HOG+SVM and use of motion information implemented in Zynq heterogeneous device", "AGH University of Science and Technology Krakow, Poland", "AGH University of Science and Technology Krakow", "AGH University of Science and Technology Krakow, Poland", "aleja Adama Mickiewicza 30, 30-059 Krak\u00f3w, Poland", "50.06688580", "19.91361920", "edu", "", "Poland", "2017"], ["Pedestrian Detection Based on YOLO Network Model", "Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, LANZHOU JIAOTONG UNIVERSITY, Lanzhou, Gansu Province, China", "LANZHOU JIAOTONG UNIVERSITY", "Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing, LANZHOU JIAOTONG UNIVERSITY, Lanzhou, Gansu Province, China", "88 Anning W Rd, Anning Qu, Lanzhou Shi, Gansu Sheng, China", "36.10567300", "103.72427300", "edu", "", "China", "2018"], ["Deep Learning Based Machine Vision: First Steps Towards a Hand Gesture Recognition Set Up for Collaborative Robots", "University of Brescia, Department of Mechanical and Industrial Engineering, Via Branze 38 Brescia, Italy", "University of Brescia", "University of Brescia", "Brescia University, West 7th Street, Owensboro, Daviess County, Kentucky, 42303, USA", "37.76893740", "-87.11138590", "edu", "", "United States", "2018"], ["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", "", "Germany", "2017"], ["Fusion of stereo camera and MIMO-FMCW radar for pedestrian tracking in indoor environments", "", "University of Stuttgart", "University of Stuttgart", "P\u00e4dagogische Hochschule Ludwigsburg, 46, Reuteallee, Ludwigsburg-Nord, Ludwigsburg, Landkreis Ludwigsburg, Regierungsbezirk Stuttgart, Baden-W\u00fcrttemberg, 71634, Deutschland", "48.90953380", "9.18318920", "edu", "", "Germany", "2016"], ["DeepSetNet: Predicting Sets with Deep Neural Networks", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2017"], ["Mind Your Language: Abuse and Offense Detection for Code-Switched Languages", "", "Singapore", "Singapore", "Singapore", "1.35208300", "103.81983600", "edu", "", "Singapore", "2018"], ["Anticipating Traffic Accidents with Adaptive Loss and Large-Scale Incident DB", "", "Keio University", "Keio University", "\u7db1\u5cf6\u5e02\u6c11\u306e\u68ee, \u3051\u3064\u308f\u308a\u5742, \u6e2f\u5317\u533a, \u6a2a\u6d5c\u5e02, \u795e\u5948\u5ddd\u770c, \u95a2\u6771\u5730\u65b9, 223-0053, \u65e5\u672c", "35.54169690", "139.63471840", "edu", "", "Japan", "2018"], ["Depth Information Guided Crowd Counting for Complex Crowd 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", "", "China", "2018"], ["Scale-variance pedestrian detection via an integrated system", "Shenzhen Key Lab. of Information Sci&Tech, Shenzhen Engineering Lab. of IS&DRM, Dept. of Electronic Engineering, Graduate School at Shenzhen, Tsinghua University, China", "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", "", "China", "2017"], ["Person-following UAVs", "", "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", "", "United States", "2016"], ["A pedestrian detection system with weak classifiers", "Multimedya Sinyal Analiz Laboratuar\u0131, Elektronik ve Haberle\u015fme M\u00fch. Bl., Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye", "Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye", "Multimedya Sinyal Analiz Laboratuar\u0131, Elektronik ve Haberle\u015fme M\u00fch. Bl., Y\u0131ld\u0131z Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye", "Davut Pa\u015fa Mahallesi, Davutpa\u015fa Cd., 34220 Esenler/\u0130stanbul, Turkey", "41.02858820", "28.88994020", "edu", "", "Turkey", "2013"], ["De-identifying people in videos using neural art", "University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, HR-10000 Zagreb, Croatia", "University of Zagreb", "University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia", "Unska ul. 3, 10000, Zagreb, Croatia", "45.80112100", "15.97084090", "edu", "", "Croatia", "2016"], ["Temporal and Fine-Grained Pedestrian Action Recognition on Driving Recorder Database", "", "Tokyo Metropolitan University", "Tokyo Metropolitan University", "\u9996\u90fd\u5927\u5b66\u6771\u4eac, \u7531\u6728\u7dd1\u9053, \u516b\u738b\u5b50\u5e02, \u6771\u4eac\u90fd, \u95a2\u6771\u5730\u65b9, 1920364, \u65e5\u672c", "35.62009250", "139.38296706", "edu", "", "Japan", "2018"], ["Efficient Pedestrian Detection by Directly Optimizing the Partial Area under the ROC Curve", "", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2013"], ["Pedestrian detection in traffic scenes using multi-attitude classifiers", "Technical University of Cluj-Napoca, Computer Science Department, Romania", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2013"], ["Effective Vehicle-Based Kangaroo Detection for Collision Warning Systems Using Region-Based Convolutional Networks", "", "Deakin University", "Deakin University", "Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia", "-38.19928505", "144.30365229", "edu", "", "Australia", "2018"], ["Real-time multi-scale pedestrian detection for driver assistance systems", "LAMIH/CNRS University of Valenciennes and Hainaut-Cambresis, Valenciennes, France", "University of Valenciennes", "LAMIH, UMR CNRS 8201 UVHC, University of Valenciennes, France", "Voirie Communale Universit\u00e9 Val Mont Houy, 59300 Famars, France", "50.32355800", "3.51258270", "edu", "", "France", "2017"], ["Evaluation of pedestrian detection fusion and localization based on the idea of car-to-X communication", "Faculty of Electrical Engineering and Media Technologies, University of Wuppertal, D-42119 Wuppertal, Germany", "University of Wuppertal", "Faculty of Electrical Engineering and Media Technologies, University of Wuppertal, D-42119 Wuppertal, Germany", "Gau\u00dfstra\u00dfe 20, 42119 Wuppertal, Germany", "51.24500000", "7.14950000", "edu", "", "Germany", "2015"], ["Fine-grained evaluation on face detection in the wild", "", "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", "", "China", "2015"], ["Robust detection of non-motorized road users using deep learning on optical and LIDAR data", "Electrical and Computer Engineering, The University of Texas at Austin, 201 E 24th Street, 78705, USA", "Electrical and Computer Engineering", "Electrical and Computer Engineering", "Electrical and Computer Engineering, Boston Avenue, South Overton, Lubbock, Lubbock County, Texas, 79409, USA", "33.58667840", "-101.87539204", "edu", "", "United States", "2016"], ["Appearance Descriptors for Person Re-identification: a Comprehensive Review", "", "University of Cagliari", "University of Cagliari, Italy", "Via Universit\u00e0, 40, 09124 Cagliari CA, Italy", "39.21736570", "9.11492180", "edu", "", "Italy", "2013"], ["An Embarrassingly Simple Approach to Visual Domain Adaptation", "National Key Laboratory of Science and Technology on Multi-Spectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan, China", "Huazhong University of Science and Technology", "Huazhong University of Science and Technology", "\u534e\u4e2d\u5927, \u73de\u55bb\u8def, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a, \u5173\u4e1c\u8857\u9053, \u4e1c\u6e56\u65b0\u6280\u672f\u5f00\u53d1\u533a\uff08\u6258\u7ba1\uff09, \u6d2a\u5c71\u533a (Hongshan), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430074, \u4e2d\u56fd", "30.50975370", "114.40628810", "edu", "", "China", "2018"], ["Pedestrian recognition through different cross-modality deep learning methods", "RITS Team, INRIA Paris, 2 Rue Simone IFF, 75012 Paris, France", "RITS Team, INRIA Paris, 2 Rue Simone IFF, 75012 Paris, France", "RITS Team, INRIA Paris, 2 Rue Simone IFF, 75012 Paris, France", "2 Rue Simone IFF, 75012 Paris, France", "48.84162120", "2.38448010", "edu", "", "", "2017"], ["Confidence-based pedestrian tracking in unstructured environments using 3D laser distance measurements", "Active Vision Group, University of Koblenz-Landau, Universit\u00e4tsstr. 1, 56070, Germany", "University of Koblenz-Landau", "Active Vision Group, Institute for Computational Visualistics, University of Koblenz-Landau, 56070, Germany", "Rhabanusstra\u00dfe 3, 55118 Mainz, Germany", "50.00335000", "8.25958700", "edu", "", "Germany", "2014"], ["Traffic Sensory Data Classification by Quantifying Scenario Complexity", "school of Software Engineering, Xi\u2019an Jiaotong University, Xi\u2019an, China", "Xi'an Jiaotong University", "Xi'an Jiaotong University", "\u897f\u5b89\u4ea4\u901a\u5927\u5b66\u5174\u5e86\u6821\u533a, \u6587\u6cbb\u8def, \u4e50\u5c45\u573a, \u7891\u6797\u533a (Beilin), \u897f\u5b89\u5e02, \u9655\u897f\u7701, 710048, \u4e2d\u56fd", "34.24749490", "108.97898751", "edu", "", "China", "2018"], ["Extending the detection range of vision-based driver assistance systems application to Pedestrian Protection System", "PARADISE Research laboratory, DIVA Strategic Research Network, University of Ottawa, Ottawa, Ontario, 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", "", "Canada", "2014"], ["Designing Efficient Multimodal Classification Systems Based on Features and Svm Kernels Selection", "", "Technical University of Cluj-Napoca", "Technical University of Cluj-Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "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", "", "South Korea", "2015"], ["Pedestrian detection in infrared images using Aggregated Channel Features", "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", "", "Romania", "2014"], ["Pedestrian Detection Based on HOG Features Optimized by Gentle AdaBoost in ROI", "", "Dalian University of Technology", "Dalian University of Technology", "\u5927\u8fde\u7406\u5de5\u5927\u5b66, \u7ea2\u51cc\u8def, \u7518\u4e95\u5b50\u533a, \u51cc\u6c34\u9547, \u7518\u4e95\u5b50\u533a / Ganjingzi, \u5927\u8fde\u5e02 / Dalian, \u8fbd\u5b81\u7701, 116023, \u4e2d\u56fd", "38.88140235", "121.52281098", "edu", "", "China", "2013"], ["Benchmarking the Grasping Capabilities of the iCub Hand With the YCB Object and Model Set", "Instituto de Sistemas e Rob\u00f3tica, Lisbon, Portugal", "Instituto de Sistemas e Rob\u00f3tica, Lisbon, Portugal", "Instituto de Sistemas e Rob\u00f3tica, Lisbon, Portugal", "Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal", "38.73756890", "-9.13865920", "edu", "", "Portugal", "2016"], ["Deep convolutional neural networks for pedestrian detection with skip pooling", "", "Nanjing University", "Nanjing University", "NJU, \u4e09\u6c5f\u8def, \u9f13\u697c\u533a, \u5357\u4eac\u5e02, \u6c5f\u82cf\u7701, 210093, \u4e2d\u56fd", "32.05659570", "118.77408833", "edu", "", "China", "2017"], ["Target detection on high-resolution SAR image using Part-based CFAR Model", "The State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079, China", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2013"], ["Pedestrian Detection Based on Informed Haar-like Features and Switchable Deep Network", "", "Anhui Polytechnic University", "Anhui Polytechnic University", "\u5b89\u5fbd\u5de5\u7a0b\u5927\u5b66, \u9e20\u6c5f\u5317\u8def, \u829c\u6e56\u5e02, \u829c\u6e56\u5e02\u533a, \u829c\u6e56\u5e02 / Wuhu, \u5b89\u5fbd\u7701, 241000, \u4e2d\u56fd", "31.34185955", "118.40739712", "edu", "", "China", "2017"], ["A Boosted Multi-Task Model for Pedestrian Detection With Occlusion Handling", "Institute of Computer Science and Technology, Peking University, Beijing, China", "Peking University", "Peking University", "\u5317\u4eac\u5927\u5b66, 5\u53f7, \u9890\u548c\u56ed\u8def, \u7a3b\u9999\u56ed\u5357\u793e\u533a, \u6d77\u6dc0\u533a, \u5317\u4eac\u5e02, 100871, \u4e2d\u56fd", "39.99223790", "116.30393816", "edu", "", "China", "2015"], ["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", "", "United States", "2018"], ["Fast algorithm for moving target detection", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "State Grid Zhejiang Electric Power Company Information & Telecommunication Branch, Hangzhou 310007, P. R. China", "Xihu, Hangzhou, Zhejiang, China, 310007", "30.23578590", "120.14053930", "edu", "", "China", "2017"], ["An UNet-Based Head Shoulder Segmentation Network", "Dept. of Information Communication Yuan-Ze University, Innovation Center for Big Data and Digital Convergence, Taiwan", "Fujian Normal University", "College of Mathematics and Informatics, Fujian Normal University, Fuzhou, China", "1 Guangxian Rd, Minhou Xian, Fuzhou Shi, Fujian Sheng, China", "26.02527760", "119.21178450", "edu", "", "China", "2018"], ["An Extended Filtered Channel Framework for Pedestrian Detection", "School of Computer Science, The University of Adelaide, Adelaide, SA, Australia", "University of Adelaide", "University of Adelaide", "University of Adelaide, North Terrace, Adelaide, 5000, City of Adelaide, South Australia, 5000, Australia", "-34.91892260", "138.60423668", "edu", "", "Australia", "2018"], ["Demo: Real-time contour-based pedestrian detection", "AIT Austrian Institute of Technology GmbH, Donau-City-Straße 1, 1220 Vienna, Austria", "AIT Austrian Institute of Technology, Vienna, Austria", "AIT Austrian Institute of Technology, Vienna, Austria", "Giefinggasse 2, 1210 Wien, Austria", "48.26830140", "16.42724830", "edu", "", "Austria", "2012"], ["Weight-loss control sampling for the training of boosted pedestrian detectors", "College of Information System and Management, National University of Defense Technology, Changsha, Hunan 410073, P. R. China", "National University of Defense Technology, China", "National University of Defence Technology, Changsha 410000, China", "\u56fd\u9632\u79d1\u5b66\u6280\u672f\u5927\u5b66, \u4e09\u4e00\u5927\u9053, \u5f00\u798f\u533a, \u5f00\u798f\u533a (Kaifu), \u957f\u6c99\u5e02 / Changsha, \u6e56\u5357\u7701, 410073, \u4e2d\u56fd", "28.22902090", "112.99483204", "mil", "", "China", "2014"], ["Towards neural art-based face de-identification in video data", "University of Zagreb, Faculty of Electrical Engineering and Computing, Unska 3, HR-10000 Zagreb, Croatia", "University of Zagreb", "University of Zagreb, Faculty of Electrical Engineering and Computing, Croatia", "Unska ul. 3, 10000, Zagreb, Croatia", "45.80112100", "15.97084090", "edu", "", "Croatia", "2016"], ["I am a Smartwatch and I can Track my User's Arm", "University of Illinois at Urbana-Champaign, Champaign, IL, USA", "University of Illinois, Urbana-Champaign", "University of Illinois, Urbana-Champaign", "B-3, South Mathews Avenue, Urbana, Champaign County, Illinois, 61801, USA", "40.11116745", "-88.22587665", "edu", "", "United States", "2016"], ["Vehicle Detection, Tracking and Behavior Analysis in Urban Driving Environments Using Road Context", "Singapore-MIT Alliance for Research and Technology, Singapore", "Singapore-MIT Alliance for Research and Technology, Singapore", "Singapore-MIT Alliance for Research and Technology, Singapore", "4 Engineering Drive 3, Singapore 117583", "1.29857500", "103.77220300", "edu", "", "Singapore", "2018"], ["People detection in heavy machines applications", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "Universit\u00e9 de Technologie de Compi\u00e8gne (UTC), France", "rue Roger Coutolenc, 60200 Compi\u00e8gne, France", "49.41522420", "2.81911440", "edu", "", "France", "2013"], ["Crosstalk Cascades for Frame-Rate Pedestrian Detection", "", "California Institute of Technology", "California Institute of Technology", "California Institute of Technology, San Pasqual Walk, Madison Heights, Pasadena, Los Angeles County, California, 91126, USA", "34.13710185", "-118.12527487", "edu", "", "United States", "2012"], ["Person Search in a Scene by Jointly Modeling People Commonness and Person Uniqueness", "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", "", "China", "2014"], ["Real-time pedestrian detection in urban scenarios", "", "Technical University of Cluj Napoca", "Technical University of Cluj Napoca", "Strada Memorandumului 28, Cluj-Napoca 400114, Romania", "46.76929900", "23.58561300", "edu", "", "Romania", "2014"], ["Pose estimation of rigid transparent objects in transparent clutter", "Willow Garage, Inc., 68 Willow Road, Menlo Park, CA 94025, USA", "Willow Garage, Inc.", "Willow Garage, Inc., 68 Willow Road, Menlo Park, CA 94025, USA", "68 Willow Rd, Menlo Park, CA 94025, USA", "37.45234560", "-122.16635620", "company", "", "United States", "2013"], ["An Architecture to Accelerate Convolution in Deep Neural Networks", "Department of Electrical and Computer Engineering, McGill University, Montr\u00e9al, QC, Canada", "McGill University", "McGill University", "McGill University, Rue Sherbrooke Ouest, Quartier des Spectacles, Ville-Marie, Montr\u00e9al, Agglom\u00e9ration de Montr\u00e9al, Montr\u00e9al (06), Qu\u00e9bec, H3A 3P8, Canada", "45.50397610", "-73.57496870", "edu", "", "Canada", "2018"], ["Multi-band Hough Forests for detecting humans with Reflective Safety Clothing from mobile machinery", "Computer Vision Group, RWTH Aachen University, D-52074, 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", "", "Germany", "2015"], ["A cascade framework for unoccluded and occluded pedestrian detection", "Dept. of Electronics Engineering Indian Institute of Technology (BHU), Varanasi", "Varanasi", "Varanasi", "Varanasi, Uttar Pradesh, India", "25.31764520", "82.97391440", "edu", "", "India", "2014"], ["Part-based pedestrian detection using grammar model and ABM-HoG features", "The State Key Laboratory of Management and Control for Complex Systems, 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", "", "China", "2013"], ["Human head detection using Histograms of Oriented optical flow in low quality videos with occlusion", "ISSNIP, Department of Electrical and Electronic Engineering, The University of Melbourne, Victoria - 3010, Australia", "University of Melbourne", "ISSNIP, The University of Melbourne, Victoria - 3010, Australia", "Parkville VIC 3010, Australia", "-37.79636890", "144.96117380", "edu", "", "Australia", "2013"], ["Training an object detector using only positive samples", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy", "Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Italy", "5 Politecnico di Milano, Via Giuseppe Ponzio, 34, 20133 Milano MI, Italy", "45.47866980", "9.23242090", "edu", "", "Italy", "2015"], ["Robust pedestrian detection and tracking with shadow removal in indoor environments", "School of Information Science and Engineering, Xiamen University, Xiamen, China", "Xiamen University", "Xiamen University", "\u53a6\u95e8\u5927\u5b66, \u601d\u660e\u5357\u8def Siming South Road, \u601d\u660e\u533a, \u601d\u660e\u533a (Siming), \u53a6\u95e8\u5e02 / Xiamen, \u798f\u5efa\u7701, 361005, \u4e2d\u56fd", "24.43994190", "118.09301781", "edu", "", "China", "2013"], ["Real-Time Pedestrian Detection for Autonomous Driving", "Shenzhen Institutes of Advanced Technology, The Chinese University of Hong Kong, Chinese Academy of Science, Shenzhen, 518055, China", "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", "", "China", "2018"], ["Multi-Camera Multi-Target Tracking with Space-Time-View Hyper-graph", "School of Computer and Control Engineering, University of the 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", "", "China", "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", "", "United States", "2016"], ["Efficient object detection via structured learning and local classifiers", "", "Oxford Brookes University", "Oxford Brookes University", "Oxford Brookes University, Headington Road, Headington, Oxford, Oxon, South East, England, OX3 0BL, UK", "51.75552050", "-1.22615970", "edu", "", "United Kingdom", "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", "", "United States", "2017"], ["A New Urban Objects Detection Framework Using Weakly Annotated Sets", "", "New York University", "New York University", "NYU, West 4th Street, NoHo Historic District, NoHo, Manhattan, Manhattan Community Board 2, New York County, NYC, New York, 10012, USA", "40.72925325", "-73.99625394", "edu", "", "United States", "2017"], ["Deep learning architecture for pedestrian 3-D localization and tracking using multiple cameras", "Perception and Intelligence Lab, Department of Electrical and Computer Engineering, ASRI, Seoul National University, South Korea", "Seoul National University", "Seoul National University", "\uc11c\uc6b8\ub300\ud559\uad50, \uc11c\ud638\ub3d9\ub85c, \uc11c\ub454\ub3d9, \uad8c\uc120\uad6c, \uc218\uc6d0\uc2dc, \uacbd\uae30, 16614, \ub300\ud55c\ubbfc\uad6d", "37.26728000", "126.98411510", "edu", "", "South Korea", "2017"], ["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", "", "China", "2012"], ["Human detection in digital videos using motion features extractors", "Universidade de Pernambuco (UPE), Recife, Brazil", "Universidade de Pernambuco (UPE), Recife, Brazil", "Universidade de Pernambuco (UPE), Recife, Brazil", "Av. Gov. Agamenon Magalh\u00e3es - Santo Amaro, Recife - PE, 50100-010, Brazil", "-8.04406030", "-34.88611670", "edu", "", "Brazil", "2016"], ["Scale Aggregation Network for Accurate and Efficient Crowd Counting", "", "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", "", "China", "2018"], ["Looking at Humans in the Age of Self-Driving and Highly Automated Vehicles", "Laboratory for Intelligent and Safe Automobiles, University of California San Diego, San Diego, CA, USA", "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", "", "United States", "2016"], ["Integrated Pedestrian and Direction Classification Using a Random Decision Forest", "", "University of Auckland", "University of Auckland", "Auckland 1010, New Zealand", "-36.85233780", "174.76910730", "edu", "", "", "2013"], ["Addressing Ambiguity In Object Instance Detection", "", "University of Oxford", "University of Oxford", "Radcliffe Camera, Radcliffe Square, Grandpont, Oxford, Oxon, South East, England, OX1 4AJ, UK", "51.75345380", "-1.25400997", "edu", "", "United Kingdom", "2013"], ["Saliency-Based Deformable Model for Pedestrian Detection", "", "Wuhan University of Technology", "Wuhan University of Technology", "\u6b66\u6c49\u7406\u5de5\u5927\u5b66-\u4f59\u5bb6\u5934\u6821\u533a, \u4ea4\u901a\u4e8c\u8def, \u6768\u56ed\u8857\u9053, \u6b66\u660c\u533a (Wuchang), \u6b66\u6c49\u5e02, \u6e56\u5317\u7701, 430062, \u4e2d\u56fd", "30.60903415", "114.35142840", "edu", "", "China", "2014"], ["Large-Scale Object Discovery and Detector Adaptation from Unlabeled Video", "", "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", "", "Germany", "2017"], ["Vision-based parking-slot detection: A benchmark and a learning-based approach", "School of Software Engineering, Tongji University, Shanghai, China", "Tongji University", "Tongji University", "\u540c\u6d4e\u5927\u5b66, 1239, \u56db\u5e73\u8def, \u6c5f\u6e7e, \u8679\u53e3\u533a, \u4e0a\u6d77\u5e02, 200092, \u4e2d\u56fd", "31.28473925", "121.49694909", "edu", "", "China", "2017"], ["Pedestrian detection with high resolution inertial measurement unit", "Department of Pervasive Computing, Tampere University of Technology, Tampere, Finland", "Tampere University of Technology", "Tampere University of Technology", "TTY, 10, Korkeakoulunkatu, Finninm\u00e4ki, Hervanta, Tampere, Tampereen seutukunta, Pirkanmaa, L\u00e4nsi- ja Sis\u00e4-Suomen aluehallintovirasto, L\u00e4nsi-Suomi, Manner-Suomi, 33720, Suomi", "61.44964205", "23.85877462", "edu", "", "Finland", "2016"], ["Multipoint infrared laser-based detection and tracking for people counting", "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", "", "China", "2017"], ["An incremental anomaly detection model for virtual machines", "", "Chongqing University", "Chongqing University", "\u91cd\u5e86\u5de5\u5546\u5927\u5b66, 19, \u7fe0\u6797\u8def, \u91cd\u5e86\u5e02, \u91cd\u5e86\u5e02\u4e2d\u5fc3, \u5357\u5cb8\u533a (Nan'an), \u91cd\u5e86\u5e02, 400067, \u4e2d\u56fd", "29.50841740", "106.57858552", "edu", "", "China", "2017"], ["Cyclist detection in LIDAR scans using faster R-CNN and synthetic depth images", "Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University, Australia", "Deakin University", "Deakin University", "Deakin University, Pigdons Lane, Waurn Ponds, Geelong, City of Greater Geelong, Barwon South West, Victoria, 3216, Australia", "-38.19928505", "144.30365229", "edu", "", "Australia", "2017"], ["Fast head-shoulder proposal for deformable part model based pedestrian detection", "Department of Electrical and Electronic Engineering, Imperial College London, United Kingdom", "Imperial College London", "Imperial College London", "Imperial College London, Exhibition Road, Brompton, Royal Borough of Kensington and Chelsea, London, Greater London, England, SW7 2AZ, UK", "51.49887085", "-0.17560797", "edu", "", "United Kingdom", "2016"], ["Use of Sparse Representation for Pedestrian Detection in Thermal Images", "", "Toyota Technological Institute", "Toyota Technological Institute", "6045 S Kenwood Ave, Chicago, IL 60637, USA", "41.78469820", "-87.59258480", "edu", "", "", "2014"], ["Pixel-Level Hand Detection with Shape-Aware Structured Forests", "", "Hong Kong", "Hong Kong", "Hong Kong", "22.39642800", "114.10949700", "edu", "", "China", "2014"]]}