Ruo-Li Dai

UMR achieves unprecedented motion fidelity by learning dense point cloud correspondences, eliminating the need for manual semantic mappings in humanoid motion retargeting.

Real-world tennis serving by humanoid robots is now possible without motion capture, thanks to a novel adaptive framework that learns directly from video.

HiPHI significantly expands the diversity of human motion data, offering a game-changing resource for training humanoid AI in complex real-world tasks.