WIDER Face and Pedestrian Challenge 2018: Methods and Results

Chen Change Loy , Dahua Lin , Wanli Ouyang , Yuanjun Xiong , Shuo Yang , Qingqiu Huang , Dongzhan Zhou , Wei Xia

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Quanquan Li Ping Luo Junjie Yan Jianfeng Wang Zuoxin Li Ye Yuan Boxun Li Shuai Shao Gang Yu Fangyun Wei Xiang Ming Dong Chen Shifeng Zhang Cheng Chi Zhen Lei Stan Z. Li Hongkai Zhang Bingpeng Ma Hong Chang Shiguang Shan Xilin Chen Wu Liu Boyan Zhou Huaxiong Li Peng Cheng Tao Mei Artem Kukharenko Artem Vasenin Nikolay Sergievskiy Hua Yang Liangqi Li Qiling Xu Yuan Hong Lin Chen Mingjun Sun Yirong Mao Shiying Luo Yongjun Li Ruiping Wang Qiaokang Xie Ziyang Wu Lei Lu Yiheng Liu Wengang Zhou

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classification 💻 cs.CV

keywords challengewiderfacepedestriantracksaimsapproachesdetection

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This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of three tracks: (i) WIDER Face which aims at soliciting new approaches to advance the state-of-the-art in face detection, (ii) WIDER Pedestrian which aims to find effective and efficient approaches to address the problem of pedestrian detection in unconstrained environments, and (iii) WIDER Person Search which presents an exciting challenge of searching persons across 192 movies. In total, 73 teams made valid submissions to the challenge tracks. We summarize the winning solutions for all three tracks. and present discussions on open problems and potential research directions in these topics.

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WIDER Face and Pedestrian Challenge 2018: Methods and Results

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