Real-time Human Pose Estimation from Video with Convolutional Neural Networks

Understand

In this paper, we present a method for real-time multi-person human pose estimation from video by utilizing convolutional neural networks.

• Our method is aimed for use case specific applications, where good accuracy is essential and variation of the background and poses is limited.
• This enables us to use a generic network architecture, which is both accurate and fast.
• We divide the problem into two phases: (1) pre-training and (2) finetuning.