Pose-based Action Recognition

Pose-Based Action Recognition is a method within the field of action recognition that identifies human actions by analyzing the spatial and temporal configurations of body joints and limb movements derived from pose estimation, distinguishing itself from appearance-based or trajectory-based methods through its reliance on skeletal or pose representations as the primary source of discriminative features.

426

Publications

30K

Citations

1.2K

Authors

477

Institutions

Publications per year

2017–2026

251

Authors

1.2K

  1. JM
    Jitendra Malik

    University of California, Berkeley, United States

    9 publications · 1.3K citations

    9

    h-index

  2. LS
    Ling Shao

    Inception Institute of Artificial Intelligence, United Arab Emirates

    6 publications · 361 citations

    6

    h-index

  3. PD
    Pınar Duygulu

    Bilkent University, Türkiye

    6 publications · 348 citations

    6

    h-index

  4. TH
    Thien Huynh‐The

    Kumoh National Institute of Technology, South Korea

    6 publications · 295 citations

    6

    h-index

  5. YW
    Yizhou Wang

    Peking University, China

    5 publications · 743 citations

    5

    h-index

1–5 of 1.2K

Venues

  1. arXiv (Cornell University)

    Repository · 22 publications · 518 citations

    14

    h-index

  2. IEEE Access

    7 publications · 215 citations

    10

    h-index

  3. Pattern Recognition

    8 publications · 1.3K citations

    9

    h-index

  4. Multimedia Tools and Applications

    9 publications · 608 citations

    9

    h-index

  5. Sensors

    7 publications · 230 citations

    7

    h-index

1–5