English

Geometry in Style: 3D Stylization via Surface Normal Deformation

Graphics 2025-04-04 v2 Computer Vision and Pattern Recognition

Abstract

We present Geometry in Style, a new method for identity-preserving mesh stylization. Existing techniques either adhere to the original shape through overly restrictive deformations such as bump maps or significantly modify the input shape using expressive deformations that may introduce artifacts or alter the identity of the source shape. In contrast, we represent a deformation of a triangle mesh as a target normal vector for each vertex neighborhood. The deformations we recover from target normals are expressive enough to enable detailed stylizations yet restrictive enough to preserve the shape's identity. We achieve such deformations using our novel differentiable As-Rigid-As-Possible (dARAP) layer, a neural-network-ready adaptation of the classical ARAP algorithm which we use to solve for per-vertex rotations and deformed vertices. As a differentiable layer, dARAP is paired with a visual loss from a text-to-image model to drive deformations toward style prompts, altogether giving us Geometry in Style. Our project page is at https://threedle.github.io/geometry-in-style.

Keywords

Cite

@article{arxiv.2503.23241,
  title  = {Geometry in Style: 3D Stylization via Surface Normal Deformation},
  author = {Nam Anh Dinh and Itai Lang and Hyunwoo Kim and Oded Stein and Rana Hanocka},
  journal= {arXiv preprint arXiv:2503.23241},
  year   = {2025}
}

Comments

CVPR 2025. Our project page is at https://threedle.github.io/geometry-in-style

R2 v1 2026-06-28T22:39:14.722Z