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arXiv · 2109.10056

Single Person Pose Estimation: A Survey

Feng Zhang·Xiatian Zhu·Chen Wang
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Abstract

Human pose estimation in unconstrained images and videos is a fundamental computer vision task. To illustrate the evolutionary path in technique, in this survey we summarize representative human pose methods in a structured taxonomy, with a particular focus on deep learning models and single-person image setting. Specifically, we examine and survey all the components of a typical human pose estimation pipeline, including data augmentation, model architecture and backbone, supervision representation, post-processing, standard datasets, evaluation metrics. To envisage the future directions, we finally discuss the key unsolved problems and potential trends for human pose estimation.

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Feng Zhang, Xiatian Zhu, Chen Wang. 2021-09-21. Single Person Pose Estimation: A Survey. https://arxiv.org/abs/2109.10056

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