6 papers
NeuMesh++: Towards Versatile and Efficient Volumetric Editing with Disentangled Neural Mesh-based Implicit Field
Chong Bao, Yuan Li, Bangbang Yang +5
Recently neural implicit rendering techniques have evolved rapidly and demonstrated significant advantages in novel view synthesis and 3D scene reconstruction. However, existing ne…
Long-tail Internet photo reconstruction
Yuan Li, Yuanbo Xiangli, Hadar Averbuch-Elor +2
Internet photo collections exhibit an extremely long-tailed distribution: a few famous landmarks are densely photographed and easily reconstructed in 3D, while most real-world site…
IM-Portrait: Learning 3D-aware Video Diffusion for Photorealistic Talking Heads from Monocular Videos
Yuan Li, Ziqian Bai, Feitong Tan +3
We propose a novel 3D-aware diffusion-based method for generating photorealistic talking head videos directly from a single identity image and explicit control signals (e.g., expre…
HiScene: Creating Hierarchical 3D Scenes with Isometric View Generation
Wenqi Dong, Bangbang Yang, Zesong Yang +5
Scene-level 3D generation represents a critical frontier in multimedia and computer graphics, yet existing approaches either suffer from limited object categories or lack editing f…
CADDreamer: CAD Object Generation from Single-view Images
Yuan Li, Cheng Lin, Yuan Liu +6
Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand i…
Neural Gaffer: Relighting Any Object via Diffusion
Haian Jin, Yuan Li, Fujun Luan +6
Single-image relighting is a challenging task that involves reasoning about the complex interplay between geometry, materials, and lighting. Many prior methods either support only…