The authors define a canonical, parallelizable mesh hierarchy using dyadic spatial grid resolutions.
Spatial resolution hierarchy enables parallel mesh generation with explicit topology
MeshOctave uses dyadic grid coarsening and per-face split-and-rewire tokens to generate meshes scale by scale, outperforming baselines in fidelity and validity.
AI Startup
Junkai Lin · Tianhao Zhao · Hang Long · Huipeng Guo · Jielei Zhang · Youjia Zhang · +7 more
Huazhong University of Science and Technology · Meshy AI · Independent Researcher · Technical University of Munich
Research Digest··2 min read
The authors propose MeshOctave, a discrete diffusion model that generates artist-quality meshes by defining scale through spatial grid resolution.
Why this paper
From Meshy AI and 3 others
In one line
MeshOctave generates native meshes with parallel discrete split-and-rewire tokens across grid-resolution scales, beating autoregressive and flow-matching baselines in fidelity and validity.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ✓Limitations stated by the authors (2 noted)
- ·No benchmark numbers found
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
§