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.
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216.3K
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7.7K
Authors
1.5K
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Publications per year
2017–2026
1.6K
Parents
2.8K
Real-time human pose recognition in parts from single depth images
Jamie Shotton, Andrew Fitzgibbon, Mat Cook et al. · 2011 · 3.5K citations
DeepPose: Human Pose Estimation via Deep Neural Networks
Alexander Toshev, Christian Szegedy · 2014 · 3.3K citations · Full text
Shih-En Wei, Varun Ramakrishna, Takeo Kanade et al. · 2016 · 2.8K citations
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Max Planck Institute for Intelligent Systems, Germany
32 publications · 6.9K citations
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1.5K
Carnegie Mellon University
Pittsburgh, United States
37 h-index
184 publications
24.4K citations
ETH Zurich
Zurich, Switzerland
34 h-index
145 publications
14.9K citations
Technical University of Munich
Munich, Germany
33 h-index
164 publications
11.7K citations
École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
33 h-index
152 publications
15.5K citations
Max Planck Institute for Informatics
Saarbrücken, Germany
33 h-index
147 publications
33.6K citations
Tsinghua University
Beijing, China
30 h-index
133 publications
9.6K citations

Shanghai Jiao Tong University
Shanghai, China
29 h-index
190 publications
25.3K citations
Google (United States)
Mountain View, United States
28 h-index
71 publications
15.6K citations
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TPAMI · 92 publications · 13.1K citations
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Repository · 216 publications · 6.8K citations
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Conference · 37 publications · 3.4K citations
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74 publications · 2.8K citations
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38 publications · 3.7K citations
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