Skeleton-based human motion prediction via spatio and position encoding transformer network

Abstract

Many transformer modules, have been applied to computer vision. However, the transformer can extract the distal connections of human skeleton points and apply the attention mechanism to the problem of predicting human motion pose. We introduce a transformer module in the joint dimension. In addition, the Encoder module of the transformer is improved. Finally, our method achieves impressive results on benchmark datasets, including short- and long-term predictions of FNTU, confirming its effectiveness and efficiency.