Papers › Integral Human Pose Regression
Integral Human Pose Regression
Xiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen Wei
State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as not differentiable and quantization error. This work shows that a simple integral operation relates and unifies the heat map representation and joint regression, thus avoiding the above issues. It is differentiable, efficient, and compatible with any heat map based methods. Its effectiveness is convincingly validated via comprehensive ablation experiments under various settings, specifically on 3D pose estimation, for the first time.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Pose Estimation | MPII Human Pose | Integral Regression | PCKh-0.5 | 91.0 | #23 of 46 | Archive leaderboard | report |
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