4 papers
Pb4U-GNet: Resolution-Adaptive Garment Simulation via Propagation-before-Update Graph Network
Aoran Liu, Kun Hu, Clinton Ansun Mo +3
Garment simulation is fundamental to various applications in computer vision and graphics, from virtual try-on to digital human modelling. However, conventional physics-based metho…
PUMPS: Skeleton-Agnostic Point-based Universal Motion Pre-Training for Synthesis in Human Motion Tasks
Clinton Ansun Mo, Kun Hu, Chengjiang Long +3
Motion skeletons drive 3D character animation by transforming bone hierarchies, but differences in proportions or structure make motion data hard to transfer across skeletons, posi…
Motion Keyframe Interpolation for Any Human Skeleton via Temporally Consistent Point Cloud Sampling and Reconstruction
Clinton Mo, Kun Hu, Chengjiang Long +2
In the character animation field, modern supervised keyframe interpolation models have demonstrated exceptional performance in constructing natural human motions from sparse pose d…
Extended Short- and Long-Range Mesh Learning for Fast and Generalized Garment Simulation
Aoran Liu, Kun Hu, Clinton Mo +2
3D garment simulation is a critical component for producing cloth-based graphics. Recent advancements in graph neural networks (GNNs) offer a promising approach for efficient garme…