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20242026
most citedMATStruct: High-Quality Medial Mesh Computation via Structure-aware Variational Optimization

2 citations · 4 across the 9 of their papers we have counts for

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cs.GR2026

Dual Contouring of Signed Distance Data

Xiana Carrera, Ningna Wang, Christopher Batty +2

We propose an algorithm to reconstruct explicit polygonal meshes from discretely sampled Signed Distance Function (SDF) data, which is especially effective at recovering sharp feat…

cs.GR2026

SpUDD: Superpower Contouring of Unsigned Distance Data

Ningna Wang, Xiana Carrera, Christopher Batty +2

Unsigned distance functions offer a powerful and flexible implicit surface representation that, unlike their signed counterparts, allow for surfaces that are open, non-orientable,…

cs.GR2026

VoroUDF: Meshing Unsigned Distance Fields with Voronoi Optimization

Ningna Wang, Zilong Wang, Xiana Carrera +2

We present VoroUDF, an algorithm for reconstructing high-quality triangle meshes from Unsigned Distance Fields (UDFs). Our algorithm supports non-manifold geometry, sharp features,…

cs.GR20252 cited

MATStruct: High-Quality Medial Mesh Computation via Structure-aware Variational Optimization

Ningna Wang, Rui Xu, Yibo Yin +4

We propose a novel optimization framework for computing the medial axis transform that simultaneously preserves the medial structure and ensures high medial mesh quality. The media…

cs.GR20241 cited

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…

cs.GR2024

MATTopo: Topology-preserving Medial Axis Transform with Restricted Power Diagram

Ningna Wang, Hui Huang, Shibo Song +3

We present a novel topology-preserving 3D medial axis computation framework based on volumetric restricted power diagram (RPD), while preserving the medial features and geometric c…