Papers › Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals
Shanxin Yuan, Guillermo Garcia-Hernando, Bjorn Stenger, Gyeongsik Moon, Ju Yong Chang, Kyoung Mu Lee, Pavlo Molchanov, Jan Kautz, Sina Honari, Liuhao Ge, Junsong Yuan, Xinghao Chen, Guijin Wang, Fan Yang, Kai Akiyama, Yang Wu, Qingfu Wan, Meysam Madadi, Sergio Escalera, Shile Li, Dongheui Lee, Iason Oikonomidis, Antonis Argyros, Tae-Kyun Kim
Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Hand Pose Estimation | HANDS 2017 | RCN-3D | Average 3D Error | 9.97 | #5 of 9 | Archive leaderboard | report |
| Hand Pose Estimation | HANDS 2017 | Vanora | Average 3D Error | 11.91 | #9 of 9 | Archive leaderboard | report |
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