Papers › An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge
An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge
Xiao Sun, Chuankang Li, Stephen Lin
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.
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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 |
|---|---|---|---|---|---|---|---|
| 3D Human Pose Estimation | CHALL H80K | ResNet | MPJPE | 55.3 | #1 of 1 | Archive leaderboard | report |
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Methods
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