Papers › Towards High Performance Human Keypoint Detection
Towards High Performance Human Keypoint Detection
Jing Zhang, Zhe Chen, DaCheng Tao
Human keypoint detection from a single image is very challenging due to occlusion, blur, illumination and scale variance. In this paper, we address this problem from three aspects by devising an efficient network structure, proposing three effective training strategies, and exploiting four useful postprocessing techniques. First, we find that context information plays an important role in reasoning human body configuration and invisible keypoints. Inspired by this, we propose a cascaded context mixer (CCM), which efficiently integrates spatial and channel context information and progressively refines them. Then, to maximize CCM's representation capability, we develop a hard-negative person detection mining strategy and a joint-training strategy by exploiting abundant unlabeled data. It enables CCM to learn discriminative features from massive diverse poses. Third, we present several sub-pixel refinement techniques for postprocessing keypoint predictions to improve detection accuracy. Extensive experiments on the MS COCO keypoint detection benchmark demonstrate the superiority of the proposed method over representative state-of-the-art (SOTA) methods. Our single model achieves comparable performance with the winner of the 2018 COCO Keypoint Detection Challenge. The final ensemble model sets a new SOTA on this benchmark.
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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 | CCM+ | AP | 78.9 | #6 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | CCM+ | AP50 | 93.8 | #6 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | CCM+ | AP75 | 86 | #6 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | CCM+ | APL | 84.5 | #6 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | CCM+ | APM | 75 | #6 of 47 | Archive leaderboard | report |
| Pose Estimation | COCO test-dev | CCM+ | AR | 83.6 | #6 of 47 | 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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