6D Pose Estimation

6D Pose Estimation is a computational task in computer vision that determines the six-dimensional Euclidean transformation—comprising three degrees of freedom for translation and three for orientation—defining the spatial pose of a rigid object relative to a reference coordinate system, distinguishing it from lower-dimensional or partial pose estimation techniques by fully specifying both position and 3D rotation.

1.4K

Publications

100.6K

Citations

3.7K

Authors

919

Institutions

Publications per year

2017–2026

790

Authors

3.7K

  1. MP
    Marc Pollefeys

    ETH Zurich, Switzerland

    23 publications · 3K citations

    21

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  2. NN
    Nassir Navab

    Technical University of Munich, Germany

    18 publications · 1.5K citations

    17

    h-index

  3. TP
    Tomáš Pajdla

    Czech Technical University in Prague, Czechia

    15 publications · 2.1K citations

    15

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  4. PF
    Pascal Fua

    École Polytechnique Fédérale de Lausanne, Switzerland

    15 publications · 2.8K citations

    15

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  5. SI
    Slobodan Ilić

    Technical University of Munich, Germany

    15 publications · 1.2K citations

    14

    h-index

1–5 of 3.7K

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 63 publications · 8.4K citations

    40

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  2. arXiv (Cornell University)

    Repository · 99 publications · 3.4K citations

    34

    h-index

  3. 24

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  4. International Journal of Computer Vision

    23 publications · 2.4K citations

    22

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  5. Pattern Recognition

    25 publications · 798 citations

    20

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