Deep Learning-Based 2D and 3D Human Pose Estimation: A Survey

Abstract

In the real world, estimation of human pose has gained considerable consideration owed to its diverse application. Here, 2D pose estimation has remarkable research and achieves targeted output however challenges still remain in 3D pose estimation. As deep learning can improve the presentation of human pose estimation, it also brings very closest result. A literature review of deep learning methods for human pose estimation presented and analyzes the methodology used by this paper. It also includes real-world video with crowded scene pose estimation with latest research information. With a methodology-based taxonomy, we sum up and discuss recent works. It also addresses and compares the datasets used in this function. Thus, this survey makes interpretable each phase in the approximation pipeline and help to reader with easy comprehensive information. Future work and Challenges are detected.