366 citations · 395 across the 11 of their papers we have counts for
11 papers · 1 filter
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Yilin Wang, Chuan Guo, Yuxuan Mu +5
Generative masked transformers have demonstrated remarkable success across various content generation tasks, primarily due to their ability to effectively model large-scale dataset…
RegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation
Yilin Wang, Chuan Guo, Li Cheng +1
Can machine automatically generate multiple distinct and natural hand grasps, given specific contact region of an object in 3D? This motivates us to consider a novel task of \texti…
InterMask: 3D Human Interaction Generation via Collaborative Masked Modeling
Muhammad Gohar Javed, Chuan Guo, Li Cheng +1
Generating realistic 3D human-human interactions from textual descriptions remains a challenging task. Existing approaches, typically based on diffusion models, often produce resul…
GSD: View-Guided Gaussian Splatting Diffusion for 3D Reconstruction
Yuxuan Mu, Xinxin Zuo, Chuan Guo +7
We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view. Prior works suffer from inconsistent 3D…
Generative Human Motion Stylization in Latent Space
Chuan Guo, Yuxuan Mu, Xinxin Zuo +4
Human motion stylization aims to revise the style of an input motion while keeping its content unaltered. Unlike existing works that operate directly in pose space, we leverage the…
MoMask: Generative Masked Modeling of 3D Human Motions
Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed +2
We introduce MoMask, a novel masked modeling framework for text-driven 3D human motion generation. In MoMask, a hierarchical quantization scheme is employed to represent human moti…