Papers › PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation
PoseBH: Prototypical Multi-Dataset Training Beyond Human Pose Estimation
Uyoung Jeong, Jonathan Freer, Seungryul Baek, Hyung Jin Chang, Kwang In Kim
We study multi-dataset training (MDT) for pose estimation, where skeletal heterogeneity presents a unique challenge that existing methods have yet to address. In traditional domains, \eg regression and classification, MDT typically relies on dataset merging or multi-head supervision. However, the diversity of skeleton types and limited cross-dataset supervision complicate integration in pose estimation. To address these challenges, we introduce PoseBH, a new MDT framework that tackles keypoint heterogeneity and limited supervision through two key techniques. First, we propose nonparametric keypoint prototypes that learn within a unified embedding space, enabling seamless integration across skeleton types. Second, we develop a cross-type self-supervision mechanism that aligns keypoint predictions with keypoint embedding prototypes, providing supervision without relying on teacher-student models or additional augmentations. PoseBH substantially improves generalization across whole-body and animal pose datasets, including COCO-WholeBody, AP-10K, and APT-36K, while preserving performance on standard human pose benchmarks (COCO, MPII, and AIC). Furthermore, our learned keypoint embeddings transfer effectively to hand shape estimation (InterHand2.6M) and human body shape estimation (3DPW). The code for PoseBH is available at: https://github.com/uyoung-jeong/PoseBH.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Pose Estimation | COCO test-dev | PoseBH-H | AP | 79.5 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | PoseBH-H | AP50 | 91.9 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | PoseBH-H | AP75 | 85.8 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | PoseBH-H | APL | 86.5 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | PoseBH-H | APM | 75.9 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | PoseBH-H | AR | 84.5 | #4 of 47 | Archive leaderboard | report |
| Pose Estimation | OCHuman | PoseBH-H | Test AP | 87.0 | #3 of 19 | Archive leaderboard | report |
| Pose Estimation | OCHuman | PoseBH-H | Validation AP | 86.0 | #3 of 19 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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