An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge
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Abstract (arXiv)
For the ECCV 2018 PoseTrack Challenge, we present a 3D human pose estimation system based mainly on the integral human pose regression method. We show a comprehensive ablation study to examine the key performance factors of the proposed system. Our system obtains 47mm MPJPE on the CHALL_H80K test dataset, placing second in the ECCV2018 3D human pose estimation challenge. Code will be released to facilitate future work.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2018.
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.
- 20262D Pre-Training for 3D Pose Estimation19 Apr 2026
- 2025RUMPL: Ray-Based Transformers for Universal Multi-View 2D to 3D Human Pose Lifting17 Dec 2025