12 papers
Autoregressive B-Rep Shape Generation with Parametric Surfaces
Dafei Qin, Rui Xu, Zeyu Shen +8
Generative CAD modeling has broad design and application potential. Despite significant advances in Boundary Representation (B-Rep) generation, the dominant representation in CAD,…
Learning a Delighting Prior for Facial Appearance Capture in the Wild
Yuxuan Han, Xin Ming, Tianxiao Li +4
High-quality facial appearance capture has traditionally required costly studio recording. Recent works consider an in-the-wild smartphone-based setup; however, their model-based i…
Strips as Tokens: Artist Mesh Generation with Native UV Segmentation
Rui Xu, Dafei Qin, Kaichun Qiao +8
Recent advancements in autoregressive transformers have demonstrated remarkable potential for generating artist-quality meshes. However, the token ordering strategies employed by e…
TAPESTRY: From Geometry to Appearance via Consistent Turntable Videos
Yan Zeng, Haoran Jiang, Kaixin Yao +4
Automatically generating photorealistic and self-consistent appearances for untextured 3D models is a critical challenge in digital content creation. The advancement of large-scale…
ManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K
Kaixuan Wang, Tianxing Chen, Jiawei Liu +13
Learning in simulation provides a useful foundation for scaling robotic manipulation capabilities. However, this paradigm often suffers from a lack of data-generation-ready digital…
WildCap: Facial Albedo Capture in the Wild via Hybrid Inverse Rendering
Yuxuan Han, Xin Ming, Tianxiao Li +4
Existing methods achieve high-quality facial albedo capture under controllable lighting, which increases capture cost and limits usability. We propose WildCap, a novel method for h…