Improvement Multi-Stage Model for Human Pose Estimation

Multi-stage methods are widely used in detection task, and become more competitive than single-stage. This paper studed the improvement both in single and multi stage model. Training methods is also metioned in this paper, like multi {\sigma} of kernel sizes for different stages, and training steps to improve the stability of convergance. The resulting multi-stage network outperforms all previous works and obtains the best performance on single person task of MPII.