4 citations · 10 across the 13 of their papers we have counts for
13 papers
Sinkhorn-CPD: Robust point cloud registration via unbalanced entropic optimal transport
Jin Zhang, Mingyang Zhao, Bing Liu +1
Coherent Point Drift (CPD) is widely used for rigid point cloud registration because of its soft correspondences and closed-form parameter updates. However, CPD's target-side margi…
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…
CasLayout: Cascaded 3D Layout Diffusion for Indoor Scene Synthesis with Implicit Relation Modeling
Yingrui Wu, Youkang Kong, Mingyang Zhao +3
Synthesizing realistic 3D indoor scenes remains challenging due to data scarcity and the difficulty of simultaneously enforcing global architectural constraints and local semantic…
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…
GraphReg: Dynamical Point Cloud Registration with Geometry-aware Graph Signal Processing
Zhao Mingyang, Ma Lei, Jia Xiaohong +2
This study presents a high-accuracy, efficient, and physically induced method for 3D point cloud registration, which is the core of many important 3D vision problems. In contrast t…
GraphFit: Learning Multi-scale Graph-Convolutional Representation for Point Cloud Normal Estimation
Keqiang Li, Mingyang Zhao, Huaiyu Wu +4
We propose a precise and efficient normal estimation method that can deal with noise and nonuniform density for unstructured 3D point clouds. Unlike existing approaches that direct…
Robust Multi-view Registration of Point Sets with Laplacian Mixture Model
Jin Zhang, Mingyang Zhao, Xin Jiang +1
Point set registration is an essential step in many computer vision applications, such as 3D reconstruction and SLAM. Although there exist many registration algorithms for differen…
Robust Ellipsoid-specific Fitting via Expectation Maximization
Zhao Mingyang, Jia Xiaohong, Ma Lei +3
Ellipsoid fitting is of general interest in machine vision, such as object detection and shape approximation. Most existing approaches rely on the least-squares fitting of quadrics…