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Integral Human Pose Regression

2018-09-18 08:29:46
Xiao Sun, Bin Xiao, Fangyin Wei, Shuang Liang, Yichen Wei

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.

Abstract (translated)

最先进的人体姿势估计方法基于热图表示。尽管表现良好,但表示本质上存在一些问题,例如不可微分和量化误差。这项工作表明,简单的积分运算关联并统一了热图表示和联合回归,从而避免了上述问题。它是可区分的,高效的,并且与任何基于热图的方法兼容。它的有效性通过各种设置下的综合消融实验,特别是3D姿态估计,首次得到了令人信服的验证。

URL

https://arxiv.org/abs/1711.08229

PDF

https://arxiv.org/pdf/1711.08229.pdf


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