Single Person Pose Estimation: A Survey

• URL: http://arxiv.org/abs/2109.10056v1
• Date: Tue, 21 Sep 2021 09:53:15 GMT
• Title: Single Person Pose Estimation: A Survey
• Authors: Feng Zhang, Xiatian Zhu, and Chen Wang
• Abstract summary: Human pose estimation in unconstrained images and videos is a fundamental computer vision task. We summarize representative human pose methods in a structured taxonomy, with a particular focus on deep learning models and single-person image setting. We examine and survey all the components of a typical human pose estimation pipeline, including data augmentation, model architecture and backbone.
• Score: 45.144269986277365
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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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