Self-supervised Action Recognition

Self-Supervised Action Recognition is a machine learning approach within video understanding that belongs to the category of action recognition methods, distinguished by its use of automatically generated supervisory signals from unlabeled video data to learn discriminative action representations without manual annotation.

154

Publications

14.6K

Citations

447

Authors

173

Institutions

Publications per year

2017–2026

151

Authors

447

  1. AZ
    Andrew Zisserman

    University of Oxford, United Kingdom

    7 publications · 1.7K citations

    8

    h-index

  2. YZ
    Yu Zhou

    Harbin Institute of Technology, China

    6 publications · 410 citations

    6

    h-index

  3. DL
    Dezhao Luo

    University of Chinese Academy of Sciences, China

    6 publications · 410 citations

    6

    h-index

  4. ML
    Mengyuan Liu

    Peking University, China

    3 publications · 226 citations

    5

    h-index

  5. TH
    Tengda Han

    University of Oxford, United Kingdom

    5 publications · 801 citations

    5

    h-index

1–5 of 447

Venues

  1. arXiv (Cornell University)

    Repository · 32 publications · 2.2K citations

    20

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 8 publications · 899 citations

    9

    h-index

  3. 9

    h-index

  4. 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

    Conference · 8 publications · 331 citations

    8

    h-index

  5. 4

    h-index

1–5