2-D Human Pose Estimation from Images Based on Deep Learning: A Review

H150 pose estimation is an important research topic in the field of computer vision and artificial intelligence. This paper focuses on the state-of-art progress of 2-D human pose estimation methods based on deep learning. According to the neural network structure, these methods are classified as single CNN method, Multi-stage CNN method, Multi-branch CNN method, Recurrent Neural Network (RNN) method and Generative Adversarial Networks (GAN) method. We summarize and analyze their attributes and performance. The future development direction is also prospected.