5 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…
Text2Sign Diffusion: A Generative Approach for Gloss-Free Sign Language Production
Liqian Feng, Lintao Wang, Kun Hu +2
Sign language production (SLP) aims to translate spoken language sentences into a sequence of pose frames in a sign language, bridging the communication gap and promoting digital i…
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…
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…
DC-PCN: Point Cloud Completion Network with Dual-Codebook Guided Quantization
Qiuxia Wu, Haiyang Huang, Kunming Su +2
Point cloud completion aims to reconstruct complete 3D shapes from partial 3D point clouds. With advancements in deep learning techniques, various methods for point cloud completio…