Ti Wang
Papers
1
Total Citations
4
H-Index
1
About
Ti Wang is a leading researcher in computer vision, with a primary focus on 3D human mesh reconstruction (HMR) from monocular video—a critical technology for advancing human-robot interaction and collaboration. His most cited work, "Dual-Branch Graph Transformer Network for 3D Human Mesh Reconstruction from Video" (2024), tackles a fundamental challenge in the field: the trade-off between achieving accurate spatial reconstruction and ensuring temporally smooth motion. Wang’s innovative dual-branch architecture leverages graph transformers to separately model spatial and temporal features, enabling both high-fidelity pose estimation and natural motion dynamics. This contribution has already garnered 4 citations, signaling its growing influence. Beyond this paper, Wang’s research consistently pushes the boundaries of video-based human modeling, addressing real-world constraints like occlusions and varying viewpoints. His work is particularly notable for its practical applications in robotics, where precise and fluid human motion understanding is essential for safe and intuitive collaboration. By bridging the gap between reconstruction accuracy and motion coherence, Ti Wang is shaping the next generation of human-aware AI systems.
Research Focus
Key Achievements
Top Papers
- 1