23 citations · 64 across the 20 of their papers we have counts for
22 papers
Structural MAT: Clean and Scalable Medial Axis Simplification via Explicit Surface Correspondence
Pengfei Wang, Shuangmin Chen, Dongming Yan +4
The Medial Axis Transform (MAT) is a complete shape descriptor capable of reconstructing the geometry of the original domain. A high-quality MAT should not only facilitate high-fid…
Manifold k-NN: Accelerated k-NN Queries for Manifold Point Clouds
Pengfei Wang, Qinghao Guo, Haisen Zhao +4
k-nearest neighbor (k-NN) search is a fundamental primitive in geometry processing and computer graphics. While spatial partitioning structures such as kd-trees are standard, they…
P2M++: Enhanced Solver for Point-to-Mesh Distance Queries
Qinghao Guo, Pengfei Wang, Chen Zong +5
Point-to-mesh distance queries are fundamental in computer graphics and geometric modeling. While the state-of-the-art P2M method achieves high-speed queries via Voronoi-based loca…
Toward Precise Curve Offsetting Constrained to Parametric Surfaces
Jin Zhao, Pengfei Wang, Shuangmin Chen +4
Computing offsets of curves on parametric surfaces is a fundamental yet challenging operation in computer aided design and manufacturing. Traditional analytical approaches suffer f…
Swept Volume Computation with Enhanced Geometric Detail Preservation
Pengfei Wang, Yuexin Yang, Shuangmin Chen +3
Swept volume computation, the determination of regions occupied by moving objects, is essential in graphics, robotics, and manufacturing. Existing approaches either explicitly trac…
Power Diagram Enhanced Adaptive Isosurface Extraction from Signed Distance Fields
Pengfei Wang, Ziyang Zhang, Wensong Wang +4
Extracting high-fidelity mesh surfaces from Signed Distance Fields has become a fundamental operation in geometry processing. Despite significant progress over the past decades, ke…
Towards Voronoi Diagrams of Surface Patches
Pengfei Wang, Jiantao Song, Lei Wang +5
Extraction of a high-fidelity 3D medial axis is a crucial operation in CAD. When dealing with a polygonal model as input, ensuring accuracy and tidiness becomes challenging due to…
ITS: Implicit Thin Shell for Polygonal Meshes
Huibiao Wen, Lei Wang, Yunxiao Zhang +6
In computer graphics, simplifying a polygonal mesh surface~ into a geometric proxy that maintains close conformity to~ is crucial, as it can significantly…
Efficient Nearest Neighbor Search Using Dynamic Programming
Pengfei Wang, Jiantao Song, Shiqing Xin +4
Given a collection of points in R^3, KD-Tree and R-Tree are well-known nearest neighbor search (NNS) algorithms that rely on space partitioning and spatial indexing techniques. How…
Deep-PE: A Learning-Based Pose Evaluator for Point Cloud Registration
Junjie Gao, Chongjian Wang, Zhongjun Ding +4
In the realm of point cloud registration, the most prevalent pose evaluation approaches are statistics-based, identifying the optimal transformation by maximizing the number of con…
NeurCross: A Neural Approach to Computing Cross Fields for Quad Mesh Generation
Qiujie Dong, Huibiao Wen, Rui Xu +6
Quadrilateral mesh generation plays a crucial role in numerical simulations within Computer-Aided Design and Engineering (CAD/E). Producing high-quality quadrangulation typically r…
ComboStoc: Combinatorial Stochasticity for Diffusion Generative Models
Rui Xu, Jiepeng Wang, Hao Pan +6
In this paper, we study an under-explored but important factor of diffusion generative models, i.e., the combinatorial complexity. Data samples are generally high-dimensional, and…
CWF: Consolidating Weak Features in High-quality Mesh Simplification
Rui Xu, Longdu Liu, Ningna Wang +7
In mesh simplification, common requirements like accuracy, triangle quality, and feature alignment are often considered as a trade-off. Existing algorithms concentrate on just one…
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…
OAAFormer: Robust and Efficient Point Cloud Registration Through Overlapping-Aware Attention in Transformer
Junjie Gao, Qiujie Dong, Ruian Wang +4
In the domain of point cloud registration, the coarse-to-fine feature matching paradigm has received substantial attention owing to its impressive performance. This paradigm involv…
Neural-Singular-Hessian: Implicit Neural Representation of Unoriented Point Clouds by Enforcing Singular Hessian
Zixiong Wang, Yunxiao Zhang, Rui Xu +6
Neural implicit representation is a promising approach for reconstructing surfaces from point clouds. Existing methods combine various regularization terms, such as the Eikonal and…
P2M: A Fast Solver for Querying Distance from Point to Mesh Surface
Chen Zong, Jiacheng Xu, Jiantao Song +4
Most of the existing point-to-mesh distance query solvers, such as Proximity Query Package (PQP), Embree and Fast Closest Point Query (FCPW), are based on bounding volume hierarchy…
NeuroGF: A Neural Representation for Fast Geodesic Distance and Path Queries
Qijian Zhang, Junhui Hou, Yohanes Yudhi Adikusuma +2
Geodesics are essential in many geometry processing applications. However, traditional algorithms for computing geodesic distances and paths on 3D mesh models are often inefficient…
Globally Consistent Normal Orientation for Point Clouds by Regularizing the Winding-Number Field
Rui Xu, Zhiyang Dou, Ningna Wang +6
Estimating normals with globally consistent orientations for a raw point cloud has many downstream geometry processing applications. Despite tremendous efforts in the past decades,…
SurfaceVoronoi: Efficiently Computing Voronoi Diagrams over Mesh Surfaces with Arbitrary Distance Solvers
Shiqing Xin, Pengfei Wang, Rui Xu +5
In this paper, we propose to compute Voronoi diagrams over mesh surfaces driven by an arbitrary geodesic distance solver, assuming that the input is a triangle mesh as well as a co…
GeoUDF: Surface Reconstruction from 3D Point Clouds via Geometry-guided Distance Representation
Siyu Ren, Junhui Hou, Xiaodong Chen +2
We present a learning-based method, namely GeoUDF,to tackle the long-standing and challenging problem of reconstructing a discrete surface from a sparse point cloud.To be specific,…
Neural-IMLS: Self-supervised Implicit Moving Least-Squares Network for Surface Reconstruction
Zixiong Wang, Pengfei Wang, Pengshuai Wang +6
Surface reconstruction is very challenging when the input point clouds, particularly real scans, are noisy and lack normals. Observing that the Multilayer Perceptron (MLP) and the…