English

MeshTailor: Cutting Seams via Generative Mesh Traversal

Graphics 2026-05-21 v2 Computer Vision and Pattern Recognition

Abstract

We present MeshTailor, the first mesh-native generative framework for synthesizing edge-aligned seams on 3D surfaces. Unlike prior optimization-based or extrinsic learning-based methods, MeshTailor operates directly on the mesh graph, eliminating projection artifacts and fragile snapping heuristics. We introduce ChainingSeams, a hierarchical serialization of the seam graph that orders chains from global structural cuts down to local details in a coarse-to-fine manner, and a dual-stream encoder that fuses topological and geometric context. Leveraging this hierarchical representation and dual-stream vertex embeddings, our MeshTailor Transformer utilizes an autoregressive pointer layer to trace seams vertex-by-vertex within local neighborhoods. Extensive evaluations show that MeshTailor produces more coherent and structurally regular seam layouts compared to recent optimization-based and learning-based baselines.

Keywords

Cite

@article{arxiv.2603.27309,
  title  = {MeshTailor: Cutting Seams via Generative Mesh Traversal},
  author = {Xueqi Ma and Xingguang Yan and Congyue Zhang and Hui Huang},
  journal= {arXiv preprint arXiv:2603.27309},
  year   = {2026}
}
R2 v1 2026-07-01T11:42:21.315Z