1 citations · 1 across the 4 of their papers we have counts for
9 papers
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
Yunhan Yang, Yufan Zhou, Yuan-Chen Guo +7
The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, lim…
DreamComposer++: Empowering Diffusion Models with Multi-View Conditions for 3D Content Generation
Yunhan Yang, Shuo Chen, Yukun Huang +6
Recent advancements in leveraging pre-trained 2D diffusion models achieve the generation of high-quality novel views from a single in-the-wild image. However, existing works face c…
AnimaX: Animating the Inanimate in 3D with Joint Video-Pose Diffusion Models
Zehuan Huang, Haoran Feng, Yangtian Sun +3
We present AnimaX, a feed-forward 3D animation framework that bridges the motion priors of video diffusion models with the controllable structure of skeleton-based animation. Tradi…
UniGeo: Taming Video Diffusion for Unified Consistent Geometry Estimation
Yang-Tian Sun, Xin Yu, Zehuan Huang +5
Recently, methods leveraging diffusion model priors to assist monocular geometric estimation (e.g., depth and normal) have gained significant attention due to their strong generali…
HoloPart: Generative 3D Part Amodal Segmentation
Yunhan Yang, Yuan-Chen Guo, Yukun Huang +5
3D part amodal segmentation--decomposing a 3D shape into complete, semantically meaningful parts, even when occluded--is a challenging but crucial task for 3D content creation and…
MV-Adapter: Multi-view Consistent Image Generation Made Easy
Zehuan Huang, Yuan-Chen Guo, Haoran Wang +4
Existing multi-view image generation methods often make invasive modifications to pre-trained text-to-image (T2I) models and require full fine-tuning, leading to (1) high computati…