AI RESEARCH
Dual-stream Spatio-Temporal GCN-Transformer Network for 3D Human Pose Estimation
arXiv CS.CV
•
ArXi:2604.17688v1 Announce Type: new 3D human pose estimation is a classic and important research direction in the field of computer vision. In recent years, Transformer-based methods have made significant progress in lifting 2D to 3D human pose estimation. However, these methods primarily focus on modeling global temporal and spatial relationships, neglecting local skeletal relationships and the information interaction between different channels. Therefore, we have proposed a novel method,the Dual-stream Spatio-temporal GCN-Transformer Network (MixTGFormer