5 papers
A Holistic Method for Superquadric Fitting Using Unsupervised Clustering Analysis
Mingyang Zhao, Sipu Ruan, Xiaohong Jia
This work presents a novel method for fitting superquadrics to point clouds under the contamination of noise and outliers, which has many applications for shape modeling across div…
OCMG-Net: Neural Oriented Normal Refinement for Unstructured Point Clouds
Yingrui Wu, Mingyang Zhao, Weize Quan +3
We present a robust refinement method for estimating oriented normals from unstructured point clouds. In contrast to previous approaches that either suffer from high computational…
A Bayesian Approach Toward Robust Multidimensional Ellipsoid-Specific Fitting
Zhao Mingyang, Jia Xiaohong, Ma Lei +5
This work presents a novel and effective method for fitting multidimensional ellipsoids to scattered data in the contamination of noise and outliers. We approach the problem as a B…
NeurCADRecon: Neural Representation for Reconstructing CAD Surfaces by Enforcing Zero Gaussian Curvature
Qiujie Dong, Rui Xu, Pengfei Wang +5
Despite recent advances in reconstructing an organic model with the neural signed distance function (SDF), the high-fidelity reconstruction of a CAD model directly from low-quality…
CMG-Net: Robust Normal Estimation for Point Clouds via Chamfer Normal Distance and Multi-scale Geometry
Yingrui Wu, Mingyang Zhao, Keqiang Li +5
This work presents an accurate and robust method for estimating normals from point clouds. In contrast to predecessor approaches that minimize the deviations between the annotated…