6 citations · 18 across the 20 of their papers we have counts for
18 papers · 1 filter
UniMate: One Unified Model to Animate Diverse Skeletons
Linzhan Mou, Jiahui Lei, Zhiyang Dou +4
Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are to…
Surflo: Consistent 3D Surface Flow Model with Global State
Antoine Guédon, Shu Nakamura, Nicolas Dufour +3
Geometry is invariant to viewpoint, which makes any collection of images a redundant encoding of a single 3D state. Existing feed-forward reconstruction models fail to exploit this…
DIMO: Diverse 3D Motion Generation for Arbitrary Objects
Linzhan Mou, Jiahui Lei, Chen Wang +2
We present DIMO, a generative approach capable of generating diverse 3D motions for arbitrary objects from a single image. The core idea of our work is to leverage the rich priors…
MoMaps: Semantics-Aware Scene Motion Generation with Motion Maps
Jiahui Lei, Kyle Genova, George Kopanas +2
This paper addresses the challenge of learning semantically and functionally meaningful 3D motion priors from real-world videos, in order to enable prediction of future 3D scene mo…
StereoDiff: Stereo-Diffusion Synergy for Video Depth Estimation
Haodong Li, Chen Wang, Jiahui Lei +2
Recent video depth estimation methods achieve great performance by following the paradigm of image depth estimation, i.e., typically fine-tuning pre-trained video diffusion models…
Zero-1-to-G: Taming Pretrained 2D Diffusion Model for Direct 3D Generation
Xuyi Meng, Chen Wang, Jiahui Lei +3
Recent advances in 2D image generation have achieved remarkable quality,largely driven by the capacity of diffusion models and the availability of large-scale datasets. However, di…