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An Integral Pose Regression System for the ECCV2018 PoseTrack Challenge

17 September 2018
Xiao Sun
Chuankang Li
Stephen Lin
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Abstract

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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