2 citations · 4 across the 5 of their papers we have counts for
6 papers
Learning Manifolds in High-D Point Embedding for Anisotropic Surface Approximation from Unstructured Point Clouds
Hongbo Li, Haikuan Zhu, Xiaohu Guo +3
Dense 3D sensors in various real-world fields produce point clouds that are geometrically redundant for real-time processing. In this paper, we propose an efficient and scalable le…
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,…
MATStruct: High-Quality Medial Mesh Computation via Structure-aware Variational Optimization
Ningna Wang, Rui Xu, Yibo Yin +4
We propose a novel optimization framework for computing the medial axis transform that simultaneously preserves the medial structure and ensures high medial mesh quality. The media…
NASM: Neural Anisotropic Surface Meshing
Hongbo Li, Haikuan Zhu, Sikai Zhong +7
This paper introduces a new learning-based method, NASM, for anisotropic surface meshing. Our key idea is to propose a graph neural network to embed an input mesh into a high-dimen…
MATTopo: Topology-preserving Medial Axis Transform with Restricted Power Diagram
Ningna Wang, Hui Huang, Shibo Song +3
We present a novel topology-preserving 3D medial axis computation framework based on volumetric restricted power diagram (RPD), while preserving the medial features and geometric c…
Winding Clearness for Differentiable Point Cloud Optimization
Dong Xiao, Yueji Ma, Zuoqiang Shi +4
We propose to explore the properties of raw point clouds through the \emph{winding clearness}, a concept we first introduce for measuring the clarity of the interior/exterior relat…