2 citations · 3 across the 5 of their papers we have counts for
5 papers
Rethinking 3D Shape Generation: Diffusion over Superquadrics
Zhiyang Liu, Wanze Li, Yuwei Wu +4
Diffusion models have advanced 3D shape generation, yet most methods still denoise in high-cardinality spaces (e.g., voxel/SDF grids, meshes, or point clouds), which is computation…
Patchwork: A compact representation for 3D polygonal shapes
Ruichen Zheng, Biao Zhang, Michael Birsak +2
We introduce Patchwork, a new general-purpose shape representation capable of modeling 2D and 3D geometry with a small number of parameters. Patchwork is grounded in a rigorous mat…
Neural Octahedral Field: Octahedral prior for simultaneous smoothing and sharp edge regularization
Ruichen Zheng, Tao Yu, Ruizhen Hu
Neural implicit representation, the parameterization of a continuous distance function as a Multi-Layer Perceptron (MLP), has emerged as a promising lead in tackling surface recons…
HACK: Learning a Parametric Head and Neck Model for High-fidelity Animation
Longwen Zhang, Zijun Zhao, Xinzhou Cong +7
Significant advancements have been made in developing parametric models for digital humans, with various approaches concentrating on parts such as the human body, hand, or face. Ne…
Learning Visibility Field for Detailed 3D Human Reconstruction and Relighting
Ruichen Zheng, Peng Li, Haoqian Wang +1
Detailed 3D reconstruction and photo-realistic relighting of digital humans are essential for various applications. To this end, we propose a novel sparse-view 3d human reconstruct…