2 citations · 3 across the 6 of their papers we have counts for
6 papers
Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy
Mingyang Zhao, Gaofeng Meng, Dong-Ming Yan
Non-rigid alignment of point clouds is crucial for scene understanding, reconstruction, and various computer vision and robotics tasks. Recent advancements in implicit deformation…
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…
Correspondence-Free Non-Rigid Point Set Registration Using Unsupervised Clustering Analysis
Mingyang Zhao, Jingen Jiang, Lei Ma +3
This paper presents a novel non-rigid point set registration method that is inspired by unsupervised clustering analysis. Unlike previous approaches that treat the source and targe…
E-Net: Efficient E(3)-Equivariant Normal Estimation Network
Hanxiao Wang, Mingyang Zhao, Weize Quan +3
Point cloud normal estimation is a fundamental task in 3D geometry processing. While recent learning-based methods achieve notable advancements in normal prediction, they often ove…
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…