Motion Representation Learning

Motion Representation Learning is a methodological framework within action recognition that focuses on extracting and modeling temporal dynamics from video data to distinguish human actions by learning discriminative features that encode motion patterns across consecutive frames.

1.1K

Publications

102.2K

Citations

3.2K

Authors

876

Institutions

Publications per year

2017–2026

719

Authors

3.2K

  1. WL
    Wanqing Li

    University of Wollongong, Australia

    13 publications · 1.9K citations

    13

    h-index

  2. PW
    Pichao Wang

    University of Wollongong, Australia

    12 publications · 1.9K citations

    12

    h-index

  3. CS
    Cordelia Schmid

    Institut national de recherche en sciences et technologies du numérique, France

    11 publications · 4.1K citations

    11

    h-index

  4. TK
    Taku Komura

    University of Edinburgh, United Kingdom

    11 publications · 1.4K citations

    11

    h-index

  5. LS
    Ling Shao

    Inception Institute of Artificial Intelligence, United Arab Emirates

    11 publications · 1.1K citations

    10

    h-index

1–5 of 3.2K

Venues

  1. arXiv (Cornell University)

    Repository · 119 publications · 5K citations

    36

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 25 publications · 8.2K citations

    24

    h-index

  3. 22

    h-index

  4. ACM Transactions on Graphics

    TOG · 24 publications · 3K citations

    22

    h-index

  5. Pattern Recognition

    24 publications · 1.9K citations

    21

    h-index

1–5