PEMD: Pose Estimation on Multiple Domains Including Human and Animal

抄録

With the development of artificial intelligence technology, the demand for multi-domain pose estimation in complex scenes is growing. The existing single model solution faces the problem of insufficient ability in cross domains of multi-scene, which is caused by the different numbers of keypoints and complex features of samples. To solve this problem, we propose a new method that has a four-stage pose estimation framework. This framework applies methods such as object detection, domain classification and pose estimation. As the experimental results show, on the testing set of mixed domains, the accuracy of our method is 5.1% higher than the best one of the existing methods, which ensures high performance pose estimation in many applications.