Unsupervised Action Recognition

Unsupervised Action Recognition is a subfield of action recognition in computer vision that identifies human actions in video sequences without relying on labeled training data, distinguishing itself by leveraging unsupervised learning techniques to discover and categorize action patterns directly from raw or unannotated video inputs.

138

Publications

7.9K

Citations

474

Authors

186

Institutions

Publications per year

2017–2026

76

Authors

474

  1. BH
    Bin Hu

    Lanzhou University, China

    4 publications · 319 citations

    4

    h-index

  2. SX
    Shihao Xu

    Chinese Academy of Sciences, China

    4 publications · 319 citations

    4

    h-index

  3. XH
    Xiping Hu

    Lanzhou University, China

    4 publications · 319 citations

    4

    h-index

  4. HR
    Haocong Rao

    Lanzhou University, China

    4 publications · 319 citations

    4

    h-index

  5. SS
    Silvio Savarese

    Stanford University, United States

    4 publications · 366 citations

    4

    h-index

1–5 of 474

Venues

  1. arXiv (Cornell University)

    Repository · 16 publications · 441 citations

    13

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 5 publications · 406 citations

    5

    h-index

  3. IEEE Transactions on Multimedia

    4 publications · 178 citations

    4

    h-index

  4. IEEE Transactions on Image Processing

    2 publications · 111 citations

    2

    h-index

  5. 2

    h-index

1–5