264 citations · 282 across the 5 of their papers we have counts for
5 papers
StableMotion: Training Motion Cleanup Models with Unpaired Corrupted Data
Yuxuan Mu, Hung Yu Ling, Yi Shi +5
Motion capture (mocap) data often exhibits visually jarring artifacts due to inaccurate sensors and post-processing. Cleaning this corrupted data can require substantial manual eff…
InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions
Sirui Xu, Hung Yu Ling, Yu-Xiong Wang +1
Achieving realistic simulations of humans interacting with a wide range of objects has long been a fundamental goal. Extending physics-based motion imitation to complex human-objec…
Learning to Brachiate via Simplified Model Imitation
Daniele Reda, Hung Yu Ling, Michiel van de Panne
Brachiation is the primary form of locomotion for gibbons and siamangs, in which these primates swing from tree limb to tree limb using only their arms. It is challenging to contro…
Character Controllers Using Motion VAEs
Hung Yu Ling, Fabio Zinno, George Cheng +1
A fundamental problem in computer animation is that of realizing purposeful and realistic human movement given a sufficiently-rich set of motion capture clips. We learn data-driven…
ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills
Zhaoming Xie, Hung Yu Ling, Nam Hee Kim +1
Humans are highly adept at walking in environments with foot placement constraints, including stepping-stone scenarios where the footstep locations are fully constrained. Finding g…