Mesh Processing Non-Meshes via Neural Displacement Fields
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Date
2026
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Mesh processing pipelines are mature, but adapting them to newer non-mesh surface representations—which enable fast rendering with compact file size—requires costly meshing or transmitting bulky meshes, negating their core benefits for streaming applications. We present a compact neural field that enables common geometry processing tasks across diverse surface representations. Given an input surface, our method learns a neural map from its coarse mesh approximation to the surface. The full representation totals only a few hundred kilobytes, making it ideal for lightweight transmission. Our method enables fast extraction of manifold and Delaunay meshes for intrinsic shape analysis, and compresses scalar fields for efficient delivery of costly precomputed results. Experiments and applications show that our fast, compact, and accurate approach opens up new possibilities for interactive geometry processing.
Description
@article{10.1111:cgf.70354,
journal = {Computer Graphics Forum},
title = {{Mesh Processing Non-Meshes via Neural Displacement Fields}},
author = {Noma, Yuta and Wang, Zhecheng and Liu, Chenxi and Singh, Karan and Jacobson, Alec},
year = {2026},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.70354}
}