3D Pose Estimation

3D Pose Estimation is a computational method within the broader domain of pose estimation that uniquely determines the spatial configuration of a subject's body or object in three-dimensional coordinates from sensory input, distinguishing itself from 2D counterparts by explicitly recovering depth and volumetric structure.

2.8K

Publications

216.3K

Citations

7.7K

Authors

1.5K

Institutions

Publications per year

2017–2026

1.6K

Authors

7.7K

  1. CT
    Christian Theobalt

    Max Planck Institute for Informatics, Germany

    32 publications · 6.9K citations

    26

    h-index

  2. NN
    Nassir Navab

    Technical University of Munich, Germany

    30 publications · 2.2K citations

    24

    h-index

  3. PF
    Pascal Fua

    École Polytechnique Fédérale de Lausanne, Switzerland

    35 publications · 4.4K citations

    23

    h-index

  4. MJ
    Michael J. Black

    Max Planck Institute for Intelligent Systems, Germany

    32 publications · 6.9K citations

    23

    h-index

  5. CS
    Cristian Sminchisescu

    Romanian Academy, Romania

    24 publications · 5.8K citations

    20

    h-index

1–5 of 7.7K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 92 publications · 13.1K citations

    49

    h-index

  2. arXiv (Cornell University)

    Repository · 216 publications · 6.8K citations

    43

    h-index

  3. 32

    h-index

  4. Sensors

    74 publications · 2.8K citations

    31

    h-index

  5. International Journal of Computer Vision

    38 publications · 3.7K citations

    29

    h-index

1–5