MeshFlow: Mesh Generation with Equivariant Flow Matching
Meshes are among the most common 3D scene representations, but directly generating meshes is challenging because the representation contains important symmetries, including permutation invariance of faces and vertices. MeshFlow learns to generate triangle meshes directly as triangle soups, avoiding the need to serialize meshes into long autoregressive sequences. We adopt equivariant optimal-transport flow matching models that respect the key symmetries of triangle soups: arbitrary permutations of faces and permutations of the vertices within each face. Toward this goal, we propose a simple yet effective modification to the Diffusion Transformer architecture, resulting in a scalable networ...
| Authors | Qi Sun, Kiyohiro Nakayama, Jing Nathan Yan et al. |
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| Primary category | cs.GR |
| Published | 22 June 2026 |
| Last updated at source | 21 August 2026 |
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