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arXiv cs.GR
arXiv cs.GR Research
· 9 months, 1 week ago • Jiayin Lu, Ying Jiang, Yumeng He, Yin Yang, Chenfanfu Jiang

VoroLight: Learning Voronoi Surface Meshes via Sphere Intersection

Briefing

The VoroLight framework revolutionizes the way Voronoi surface meshes are constructed by promoting controlled degeneracy, which leads to smoother and more geometrically regular surfaces. By associating each Voronoi vertex with a trainable sphere and implementing a sphere-intersection loss, developers can achieve higher-order equidistance among generators, significantly improving surface quality.

This advancement is crucial for graphics programmers and artists who require high fidelity in 3D shape reconstruction. With support for multimodal shape supervision, VoroLight allows for the integration of diverse data sources, enhancing the flexibility and effectiveness of 3D modeling workflows. As the framework extends to volumetric Voronoi meshes, it opens new avenues for creating complex geometries in game development.

“VoroLight achieves competitive reconstruction fidelity while producing smoother surfaces.”

— Jiayin Lu · Describing the framework's capabilities.
Original source
Read on arXiv cs.GR
At a glance
what
Introduction of VoroLight framework for Voronoi surface meshes
who
Developed by Jiayin Lu and collaborators
when
First submitted on 15 Dec 2025, revised on 22 Mar 2026
impact
Improves surface regularity and reconstruction fidelity for 3D shapes
Signal Positive

The framework offers significant improvements for 3D modeling.

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