Hi TRELLIS team,
I executed an automated geometry quality evaluation across 2,307 assets from 23 generators (sampled from the 3D Arena dataset).
Comparing both TRELLIS generations in the dataset yielded the following metrics:
- TRELLIS (n=100): 60.0% non-watertight | 0.0% non-manifold | 4.0% > 30k tris
- TRELLIS.2-4B (n=101): 91.1% non-watertight | 14.9% non-manifold | 100% > 30k tris
The higher face density in TRELLIS.2-4B accounts for the triangle budget, but the non-manifold edge rise from 0% to 14.9% stood out during automated QA.
The evaluation runner, manifest files, and raw aggregate reports are published and reproducible via pip install 3dqa:
https://github.com/alza123123/3dqa-benchmark
Hi TRELLIS team,
I executed an automated geometry quality evaluation across 2,307 assets from 23 generators (sampled from the 3D Arena dataset).
Comparing both TRELLIS generations in the dataset yielded the following metrics:
The higher face density in TRELLIS.2-4B accounts for the triangle budget, but the non-manifold edge rise from 0% to 14.9% stood out during automated QA.
The evaluation runner, manifest files, and raw aggregate reports are published and reproducible via
pip install 3dqa:https://github.com/alza123123/3dqa-benchmark