5 papers
GRASE: Geometry-native Real-to-sim Agentic Scene Modeling from Video
Zhaorui Lin, Haohan Liu, Zhen Chen +1
Real-to-sim conversion aims to turn a captured video of a real environment into an editable 3D scene while preserving the geometry and layout of what was observed. Existing methods…
ARAPDiffusion: Geometry-Distribution Feedback for Deformable 3D Shape Generation
Haibo Liu, Jinghan Ke, Haitao Yang +3
Deformable 3D shapes can undergo large changes in pose and morphology while still preserving plausible local geometry, yet generative models often produce samples with unnatural st…
Interact3D: Compositional 3D Generation of Interactive Objects
Hui Shan, Keyang Luo, Ming Li +4
Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional objects from single images--particularly u…
GenAnalysis: Joint Shape Analysis by Learning Man-Made Shape Generators with Deformation Regularizations
Yuezhi Yang, Haitao Yang, Kiyohiro Nakayama +3
We present GenAnalysis, an implicit shape generation framework that allows joint analysis of man-made shapes, including shape matching and joint shape segmentation. The key idea is…
Instance-aware 3D Semantic Segmentation powered by Shape Generators and Classifiers
Bo Sun, Qixing Huang, Xiangru Huang
Existing 3D semantic segmentation methods rely on point-wise or voxel-wise feature descriptors to output segmentation predictions. However, these descriptors are often supervised a…