Technical Program

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ARS-16: Machine Learning for Object Tracking

Interactive Q&A Time: Wednesday, 28 October, 08:00 - 08:25
Virtual Session: View on Virtual Platform
Session Chair: Li Cheng, University of Alberta
 
 ARS-16.1: VISUAL TRACKING VIA TEMPORALLY-REGULARIZED CONTEXT-AWARE CORRELATION FILTERS
         Jiawen Liao; Xi’an Institute of Optics and Precision Mechanics
         Chun Qi; Xi’an Jiaotong University
         Jianzhong Cao; Xi’an Institute of Optics and Precision Mechanics
         He Bian; Xi’an Institute of Optics and Precision Mechanics
 
 ARS-16.2: END-TO-END TEMPORAL FEATURE AGGREGATION FOR SIAMESE TRACKERS
         Zhenbang Li; Institute of Automation, Chinese Academy of Sciences
         Qiang Wang; Institute of Automation, Chinese Academy of Sciences
         Jin Gao; Institute of Automation, Chinese Academy of Sciences
         Bing Li; Institute of Automation, Chinese Academy of Sciences
         Weiming Hu; Institute of Automation, Chinese Academy of Sciences
 
 ARS-16.3: IOU - SIAMTRACK: IOU GUIDED SIAMESE NETWORK FOR VISUAL OBJECT TRACKING
         Mohana Murali Dasari; Indian Institute of Technology, Tirupati
         Rama Krishna Sai Subrahmanyam Gorthi; Indian Institute of Technology, Tirupati
 
 ARS-16.4: GLOBALLY SPATIAL-TEMPORAL PERCEPTION: A LONG-TERM TRACKING SYSTEM
         Zhenbang Li; Institute of Automation, Chinese Academy of Sciences
         Qiang Wang; Institute of Automation, Chinese Academy of Sciences
         Jin Gao; Institute of Automation, Chinese Academy of Sciences
         Bing Li; Institute of Automation, Chinese Academy of Sciences
         Weiming Hu; Institute of Automation, Chinese Academy of Sciences
 
 ARS-16.5: TRACKING HUNDREDS OF PEOPLE IN DENSELY CROWDED SCENES WITH PARTICLE FILTERING SUPERVISING DEEP CONVOLUTIONAL NEURAL NETWORKS
         Gianni Franchi; Université Paris Saclay
         Emanuel Aldea; Université Paris Saclay
         Séverine Dubuisson; Aix Marseille University
         Isabelle Bloch; Institut polytechnique de Paris
 
 ARS-16.6: AN EFFECTIVE HIERARCHICAL RESOLUTION LEARNING METHOD FOR LOW-RESOLUTION TARGETS TRACKING
         Runqing Zhang; Beijing University of Posts and Telecommunications
         Chunxiao Fan; Beijing University of Posts and Telecommunications
         Yue Ming; Beijing University of Posts and Telecommunications
         Hao Fu; Beijing University of Posts and Telecommunications
         Xuyang Meng; Beijing University of Posts and Telecommunications
 
 ARS-16.7: RELIABLE TEMPORALLY CONSISTENT FEATURE ADAPTATION FOR VISUAL OBJECT TRACKING
         Goutam Yelluru Gopal; Concordia University
         Maria A. Amer; Concordia University
 
 ARS-16.8: HOW INCOMPLETELY SEGMENTED INFORMATION AFFECTS MULTI-OBJECT TRACKING AND SEGMENTATION (MOTS)
         Yu-Sheng Chou; National Taiwan University
         Chien-Yao Wang; Academia Sinica
         Shou-De Lin; National Taiwan University
         Hong-Yuan Mark Liao; Academia Sinica
 
 ARS-16.9: FUSION OF SALIENCY MAP AND DEEP FEATURE-BASED CORRELATION FILTER FOR ENHANCING TRACKING PERFORMANCES
         Hyemin Lee; POSTECH
         Daijin Kim; POSTECH
 
 ARS-16.10: PRIVACY-AWARE EDGE COMPUTING SYSTEM FOR PEOPLE TRACKING
         Jukka Yrjänäinen; Tampere University
         Xingyang Ni; Tampere University
         Bishwo Adhikari; Tampere University
         Heikki Huttunen; Tampere University
 
 ARS-16.11: OBJECT TRACKING VIA IMAGENET CLASSIFICATION SCORES
         Li Wang; Agency for Science, Technology and Research
         Ting Liu; Nanyang Technological University
         Bing Wang; Nanyang Technological University
         Jie Lin; Agency for Science, Technology and Research
         Xulei Yang; Agency for Science, Technology and Research
         Gang Wang; Nanyang Technological University
 
 ARS-16.12: BAE-NET: A BAND ATTENTION AWARE ENSEMBLE NETWORK FOR HYPERSPECTRAL OBJECT TRACKING
         Zhuanfeng Li; Nanjing University of Science and Technology
         Fengchao Xiong; Nanjing University of Science and Technology
         Jun Zhou; Griffith University
         Jing Wang; Griffith University
         Jianfeng Lu; Nanjing University of Science and Technology
         Yuntao Qian; College of Computer Science
 
 ARS-16.13: DUAL-DIRECTION PERCEPTION AND COLLABORATION NETWORK FOR NEAR-ONLINE MULTI-OBJECT TRACKING
         Xian Zhong; Wuhan University of Technology
         Ming Tan; Wuhan University of Technology
         Weijian Ruan; Wuhan University
         Wenxin Huang; Wuhan University
         Liang Xie; Wuhan University of Technology
         Jingling Yuan; Wuhan University of Technology
 
 ARS-16.14: HIGH PERFORMANCE VISUAL TRACKING WITH SIAMESE ACTOR-CRITIC NETWORK
         Dawei Zhang; Zhejiang Normal University
         Zhonglong Zheng; Zhejiang Normal University