RADmesh: Remesh-Aware Mesh Deformation

• URL: http://arxiv.org/abs/2608.17182v1
• Date: Mon, 17 Aug 2026 22:46:13 GMT
• Title: RADmesh: Remesh-Aware Mesh Deformation
• Abstract summary: We propose a remeshing-enhanced method for generatively deforming shapes with visual losses.<n>Our method is localizable, able to grow new features on a base shape with expressive detail, leaving the rest unchanged.
• Score: 16.876375037183436
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a remeshing-enhanced method for generatively deforming shapes with visual losses. It is intuitive that sufficiently drastic deformations of a mesh without changing its triangulation can easily compromise element quality, even if such large geometry changes may be semantically desired. Shape deformation methods could thus benefit from changing the triangulation; however, this is not done by most generative, text-based, visually-supervised mesh deformation methods. Remeshing is a discrete operation, proven to be especially challenging to couple with the notoriously noisy supervision signal provided by visual losses. We propose a vertex-based deformation optimization quantity capable of large deformations and robustness to such noise; we periodically remesh using an isotropic remesher that interpolates and carries forward the deformation optimization state. This enables continuous, geometry-informed progress in coarse-to-fine addition of resolution. The resulting shapes' triangulations fit their optimized geometry and have neat isotropic elements. Further, our method is localizable, able to grow new features on a base shape with expressive detail, leaving the rest unchanged. We showcase the effectiveness of our method on a variety of shapes and prompts, both local and global deformations, and demonstrate its superior visual quality and triangle efficiency. Our project page is at https://threedle.github.io/radmesh.

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