3 citations · 7 across the 19 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…
Filmsticking++: Rapid Film Sticking for Explicit Surface Reconstruction
Pengfei Wang, Jian Liu, Qiujie Dong +5
Explicit surface reconstruction aims to generate a surface mesh that exactly interpolates a given point cloud. This requirement is crucial when the point cloud must lie non-negotia…
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…
MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assembly
Rui Xu, Tianyang Xue, Qiujie Dong +9
Scaling artist-designed meshes to high triangle numbers remains challenging for autoregressive generative models. Existing transformer-based methods suffer from long-sequence bottl…
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…
NeuVAS: Neural Implicit Surfaces for Variational Shape Modeling
Pengfei Wang, Qiujie Dong, Fangtian Liang +11
Neural implicit shape representation has drawn significant attention in recent years due to its smoothness, differentiability, and topological flexibility. However, directly modeli…
CrossGen: Learning and Generating Cross Fields for Quad Meshing
Qiujie Dong, Jiepeng Wang, Rui Xu +10
Cross fields play a critical role in various geometry processing tasks, especially for quad mesh generation. Existing methods for cross field generation often struggle to balance c…
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…
SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors
Rui Xu, Wenyue Chen, Jiepeng Wang +7
Gaussian Splatting demonstrates impressive results in multi-view reconstruction based on Gaussian explicit representations. However, the current Gaussian primitives only have a sin…
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…
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…
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…
D3Former: Jointly Learning Repeatable Dense Detectors and Feature-enhanced Descriptors via Saliency-guided Transformer
Junjie Gao, Pengfei Wang, Qiujie Dong +3
Establishing accurate and representative matches is a crucial step in addressing the point cloud registration problem. A commonly employed approach involves detecting keypoints wit…
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…