| title | LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow |
|---|---|
| authors | Hang Long, Tianhao Zhao, Junkai Lin, Youjia Zhang, Huipeng Guo, Rendong Liang, Jiale Xu, Jozef Hladký, Matthias Nießner, Wei Yang |
| date | 2026-07-12 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2607.10623 |
| upvotes | 9 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf |
| abstract | Flow matching over carefully designed latent representations has recently emerged as a powerful paradigm for topology-aware mesh generation. Existing approaches, however, model vertices and connectivity jointly in a joint latent space, entangling continuous vertex geometry with discrete combinatorial structure; this complicates flow learning and manifests as drifting vertices and broken surfaces. We present LATO.2, a factorized flow matching framework that decomposes mesh generation into a vertex flow followed by a connectivity flow conditioned on the realized vertices, with both stages anchored to a shared coarse voxel scaffold. Dedicated VAEs underpin the two stages, recovering vertices at sub-voxel precision and embedding discrete connectivity into a continuous latent space. We demonstrate two advantages unique to this factorization: (i) part-wise generation, in which the scaffold is partitioned and each part synthesized at full latent capacity, yielding substantially higher-resolution meshes than a monolithic latent permits; and (ii) topology-adaptive editing, in which manipulating first-stage vertices induces the corresponding connectivity without re-optimization. Experiments show that LATO.2 surpasses state-of-the-art topology-aware mesh generators in geometric fidelity and connectivity quality. |
cite
@misc{long2026lato,
title={LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow},
author={Hang Long and Tianhao Zhao and Junkai Lin and Youjia Zhang and Huipeng Guo and Rendong Liang and Jiale Xu and Jozef Hladký and Matthias Nießner and Wei Yang},
year={2026},
eprint={2607.10623},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2607.10623}
}