3D human pose estimation describes estimating 3D articulation structure of a person from an image or a video. The technology has massive potential because it can enable tracking people and analyzing motion in real time. Recently, much research has been conducted to optimize human pose estimation, but few works have focused on reviewing 3D human pose estimation. In this paper, we offer a comprehensive survey of the state-of-the-art methods for 3D human pose estimation, referred to as pose estimation solutions, implementations on images or videos that contain different numbers of people and advanced 3D human pose estimation techniques. Furthermore, different kinds of algorithms are further subdivided into sub-categories and compared in light of different methodologies. To the best of our knowledge, this is the first such comprehensive survey of the recent progress of 3D human pose estimation and will hopefully facilitate the completion, refinement and applications of 3D human pose estimation.
Exploiting Temporal Contexts with Strided Transformer for 3D Human Pose Estimation