Articulated Pose Estimation

Articulated Pose Estimation is a computational method in computer vision that models the spatial configuration of interconnected body parts to estimate the three-dimensional pose of articulated objects, such as human bodies, by distinguishing kinematic constraints and joint flexibility from rigid pose estimation approaches.

1K

Publications

108.2K

Citations

3K

Authors

747

Institutions

Publications per year

2017–2026

639

Authors

3K

  1. CT
    Christian Theobalt

    Max Planck Institute for Informatics, Germany

    23 publications · 4.1K citations

    20

    h-index

  2. MJ
    Michael J. Black

    Max Planck Institute for Intelligent Systems, Germany

    21 publications · 3.9K citations

    19

    h-index

  3. BS
    Bernt Schiele

    Max Planck Institute for Informatics, Germany

    18 publications · 5.1K citations

    17

    h-index

  4. MA
    Mykhaylo Andriluka

    Max Planck Institute for Informatics, Germany

    16 publications · 4.8K citations

    16

    h-index

  5. TK
    Tae‐Kyun Kim

    Imperial College London, United Kingdom

    14 publications · 1.7K citations

    14

    h-index

1–5 of 3K

Venues

  1. arXiv (Cornell University)

    Repository · 109 publications · 6.5K citations

    36

    h-index

  2. International Journal of Computer Vision

    29 publications · 3.4K citations

    25

    h-index

  3. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 31 publications · 3.8K citations

    25

    h-index

  4. Pattern Recognition

    36 publications · 1.4K citations

    22

    h-index

  5. 16

    h-index

1–5