【CVPR2019正式公布】行人重识别论文 附下载链接

2019 年 4 月 26 日 极市平台

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前段时间,计算机视觉顶会CVPR 2019 官方已公布了全部接收论文列表,极市已汇总目前公开的所有论文链接及code(目前已更新510篇):https://github.com/extreme-assistant/cvpr2019 ,本文是作者整理的CVPR2019中的行人重识别论文汇总,含部分论文下载链接。


原创整理 | 酱油妹

来源 | https://zhuanlan.zhihu.com/p/62843442


正式接收的论文名单 (已更新下载链接)

Oral:

  1. Joint Discriminative and Generative Learning for Person Re-identification

    作者:Zhedong Zheng; Xiaodong Yang; Zhiding Yu; Liang Zheng ; Yi Yang ; Jan Kautz

    链接:arxiv.org/abs/1904.0722


  2. Unsupervised Person Re-identification by Soft Multilabel Learning

    作者:Hong-Xing Yu ; WEI-SHI ZHENG ; Ancong Wu ; Xiaowei Guo ; Shaogang Gong ; Jian-Huang Lai

    链接:arxiv.org/abs/1903.0632


  3. Learning Context Graph for Person Search

    作者:Yichao Yan ; Qiang Zhang Bingbing Ni; Wendong Zhang ; Minghao Xu; Xiaokang Yang 

    链接:arxiv.org/abs/1904.0183


  4. Progressive Pose Attention Transfer for Person Image Generation

    作者:Zhen Zhu (Huazhong University of Science and Technology)*; Tengteng Huang (Huazhong University of Science and Technology); Baoguang Shi (Microsoft); Miao Yu (Huazhong University of Science and Technology); Bofei Wang (ZTE Corporation); Xiang Bai (Huazhong University of Science and Technology)

    链接:arxiv.org/abs/1904.0334


Poster:

  1. Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification 

    作者:Yifan Sun (Tsinghua University); Ya-Li Li (THU); Qin Xu (Tsinghua University); Chi Zhang (Megvii Inc.); Yikang Li (CUHK); Shengjin Wang (Tsinghua University)*; Jian Sun (Megvii Technology)

    链接:arxiv.org/abs/1904.0053


  2. Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification

    作者:Zhun Zhong (Xiamen University)*; Liang Zheng (Australian National University); Zhiming Luo (Xiamen University); Shaozi Li (Xiamen University, China); Yi Yang (UTS)

    链接:arxiv.org/abs/1904.0199


  3. Dissecting Person Re-identification from the Viewpoint of Viewpoint

    作者:Xiaoxiao Sun (Singapore University of Technology and Design)*; Liang Zheng (Australian National University)

    链接:arxiv.org/abs/1812.0216


  4. Densely Semantically Aligned Person Re-Identification

    作者:Zhizheng Zhang (University of Science and Technology of China); Cuiling Lan (Microsoft Research)*; Wenjun Zeng (Microsoft Research); Zhibo Chen (University of Science and Technology of China)

    链接:arxiv.org/abs/1812.0896


  5. Generalizable Person Re-identification by Domain-Invariant Mapping Network

    作者:Jifei Song (Queen Mary, University of London)*; Yongxin Yang (University of Edinburgh ); Yi-Zhe Song (Queen Mary University of London); Tao Xiang (University of Surrey); Timothy Hospedales (Edinburgh University)

    链接:

    http://www.eecs.qmul.ac.uk/~js327/Doc/Publication/2019/cvpr2019_dimn.pdf


  6. Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification

    作者:Song Bai (University of Oxford)*; Peng Tang (Huazhong University of Science and Technology); Longin Jan Latecki (Temple University); Philip Torr (University of Oxford)

    链接:https://cis.temple.edu/~latecki/Papers/SongCVPR2019.pdf


  7. Weakly Supervised Person Re-Identification 

    作者:Jingke Meng (Sun Yat-Sun University); Sheng Wu (Sen Yat-Sun University); WEI-SHI ZHENG (Sun Yat-sen University, China)*

    链接:arxiv.org/abs/1904.0383


  8. Query-guided End-to-End Person Search

    作者:Bharti Munjal (OSRAM)*; Sikandar Amin (OSRAM GmbH); Federico Tombari (Technical University of Munich, Germany); Fabio Galasso (OSRAM)

     

  9. Distilled Person Re-identification: Towards a More Scalable System 

    作者:Ancong Wu (Sun Yat-sen University); WEI-SHI ZHENG (Sun Yat-sen University, China)*; Xiaowei Guo (Tencent Youtu Lab); Jian-Huang Lai (Sun Yat-sen University)

    链接:

    https://www.researchgate.net/publication/332267080_Distilled_Person_Re-identification_Towards_a_More_Scalable_System


  10. Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification 

    Wenjie Yang (Institute of Automation, Chinese Academy of Sciences)*; Houjing Huang (CASIA); Zhang Zhang (Institute of Automation, Chinese Academy of Sciences); Xiaotang Chen (Institute of Automation, Chinese Academy of Sciences); Kaiqi Huang (Institute of Automation, Chinese Academy of Sciences); Shu Zhang (Deepwise AI Lab)

     

  11. Patch Based Discriminative Feature Learning for Unsupervised Person Re-identification 

    作者:Qize Yang (Sun Yat-sen University); Hong-Xing Yu (Sun Yat-Sen University); Ancong Wu (Sun Yat-sen University); WEI-SHI ZHENG (Sun Yat-sen University, China)*

    链接:https://kovenyu.com/publication/2019-cvpr-pedal/


  12. Unsupervised Person Image Generation with Semantic Parsing Transformation

    作者:Sijie Song (Peking University)*; Wei Zhang (JD AI Research); Jiaying Liu (Peking University); Tao Mei (AI Research JD)

    链接:arxiv.org/abs/1904.0337


  13. Text Guided Person Image Synthesis 

    作者:Xingran Zhou (Zhejiang University); Siyu Huang (Zhejiang University)*; Bin Li (Zhejiang University); Yingming Li (Zhejiang University); Jiachen Li (Nanjing University); Zhongfei Zhang (Zhejiang University)

    链接:arxiv.org/abs/1904.0511


  14. Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification 

    作者:Yiru Zhao (Shanghai Jiao Tong University)*; Xu Shen (Alibaba Group); Zhongming Jin (Alibaba Group); Hongtao Lu (Shanghai Jiao Tong University); Xiansheng Hua (Damo Academy, Alibaba Group)

     

  15. AANet: Attribute Attentio Network for Person Re-Identification 

    作者:Chiat Pin Tay (Nanyang Technological University)*; Sharmili Roy (Nanyang Technological University); Kim Yap (Nanyang Technological University)

     

  16. VRSTC: Occlusion-Free Video Person Re-Identification 

    作者:Ruibing Hou (Institute of Computing Technology,Chinese Academy); Bingpeng MA (UCAS)*; Hong Chang (Chinese Academy of Sciences); Xinqian Gu (University of Chinese Academy of Sciences); Shiguang Shan (Chinese Academy of Sciences); Xilin Chen (China)

     

  17. Adaptive Transfer Network for Cross-Domain Person Re-Identification 

    作者:Jiawei Liu (University of Science and Technology of China); Zheng-Jun Zha (University of Science and Technology of China)*; Di Chen (University of Science and Technology of China); Richang Hong (HeFei University of Technology); Meng Wang (Hefei University of Technology)

     

  18. Interaction-and-Aggregation Network for Person Re-identification 

    作者:Ruibing Hou (Institute of Computing Technology,Chinese Academy); Bingpeng MA (UCAS)*; Hong Chang (Chinese Academy of Sciences); Xinqian Gu (University of Chinese Academy of Sciences); Shiguang Shan (Chinese Academy of Sciences); Xilin Chen (China)

     

  19. Re-Identification with Consistent Attentive Siamese Networks 

    作者:Meng Zheng (Rensselaer Polytechnic Institute); Srikrishna Karanam (Siemens Corporate Technology, Princeton)*; Ziyan Wu (Siemens Corporation); Richard Radke (Rensselaer Polytechnic Institute)

    链接:arxiv.org/abs/1811.0748


  20. Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training 

    作者:Feng Zheng (Southern University of Science and Technology)*; Rongrong Ji (Xiamen University, China); Cheng Deng (Xidian University); Xing Sun (Tencent); Xinyang Jiang (Tencent); Xiaowei Guo (Tencent Youtu Lab); Zongqiao Yu (Tencent); Feiyue Huang (Tencent)

     

  21. CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification 

    作者:ZHENG TANG (University of Washington)*; Milind Naphade (NVidia); Ming-Yu Liu (NVIDIA); Xiaodong Yang (NVIDIA Research); Stan Birchfield (NVIDIA); Shuo Wang (NVidia); Ratnesh Kumar (NVIDIA); David Anastasiu (SJSU); Jenq-Neng Hwang (University of Washinton)

    链接:arxiv.org/abs/1903.0925


  22. Re-Identification Supervised 3D Texture Generation 

    作者:Jian Wang (State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences)*; Yunshan Zhong (Peking University); Yachun Li (Zhejiang University); Chi Zhang (Megvii Inc.); Yichen Wei (Megvii Research Shanghai)





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行人重识别(Person re-identification)也称行人再识别,是利用计算机视觉技术判断图像或者视频序列中是否存在特定行人的技术。广泛被认为是一个图像检索的子问题。给定一个监控行人图像,检索跨设备下的该行人图像。旨在弥补目前固定的摄像头的视觉局限,并可与行人检测/行人跟踪技术相结合,可广泛应用于智能视频监控、智能安保等领域。 由于不同摄像设备之间的差异,同时行人兼具刚性和柔性的特性 ,外观易受穿着、尺

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