Integral Human Pose Regression

Xiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen Wei

2017-11-22ECCV 2018 93D Human Pose Estimation regression Quantization Pose Estimation 3D Pose Estimation

Abstract

State-of-the-art human pose estimation methods are based on heat map representation. In spite of the good performance, the representation has a few issues in nature, such as not differentiable and quantization error. This work shows that a simple integral operation relates and unifies the heat map representation and joint regression, thus avoiding the above issues. It is differentiable, efficient, and compatible with any heat map based methods. Its effectiveness is convincingly validated via comprehensive ablation experiments under various settings, specifically on 3D pose estimation, for the first time.

Results

Task	Dataset	Metric	Value	Model
Pose Estimation	MPII Human Pose	PCKh-0.5	91	Integral Regression
3D	MPII Human Pose	PCKh-0.5	91	Integral Regression
1 Image, 2*2 Stitchi	MPII Human Pose	PCKh-0.5	91	Integral Regression

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