collaborators

13 papers

cs.CV2026

WAT3R: Feedforward Underwater 3D Reconstruction

Jiayi Xu, Jiahao Lu, Ziqiang Zheng +4

Reliable feedforward underwater 3D reconstruction remains challenging due to severe light attenuation and backscattering, which degrade visual quality and disrupt feature consisten…

cs.GR2026

QuadLink: Autoregressive Quad-Dominant Mesh Generation via Point-Relation Learning

Yiheng Zhang, Zhe Zhu, Tingrui Shen +11

The generation of production-ready quad-dominant meshes is a cornerstone of modern 3D content creation. Generating anisotropic quad-dominant meshes from point clouds is challenging…

cs.CV2026

CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos

Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7

In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…

cs.CV2026

RecGen3D: Reconstruction-Guided 3D Generation in a Shared Canonical Space

Zhisheng Huang, Jiahao Chen, Cheng Lin +10

Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruction excels in efficiency and inp…

cs.CV2026

HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images

Yumeng Liu, Xiao-Xiao Long, Marc Habermann +6

Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics, animation and VR/AR. Crucially,…

cs.CV2026

GO-Renderer: Generative Object Rendering with 3D-aware Controllable Video Diffusion Models

Zekai Gu, Shuoxuan Feng, Yansong Wang +6

Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently…