metadata
license: mit
pretty_name: DiffReg-PBIR — Stanford-ORB submission
tags:
- inverse-rendering
- stanford-orb
- relighting
task_categories:
- image-to-3d
DiffReg-PBIR — Stanford-ORB benchmark submission
Predicted outputs and evaluation scores for DiffReg-PBIR on the Stanford-ORB inverse-rendering benchmark (full 42-scene split).
Paper: Diffusion-Based Material Regularization for Physics-Based Inverse Rendering (ECCV 2026)
- Project page: https://gerwang.github.io/diffusion-regularized-inverse-rendering/
- arXiv: https://arxiv.org/abs/2606.31065
Contents (submission_DiffReg-PBIR.zip, ~6.8 GB uncompressed)
submission_DiffReg-PBIR/
predictions/<scene>/
mesh.obj # reconstructed mesh (shape task)
view/*.exr # HDR novel-view renders
light/*.exr # HDR novel-scene relit renders
geometry/*_image.zbuf.exr, *_image.normal.exr # Z-depth + camera-space normals
material/*_albedo.exr # albedo
test_results.json # paths in the official examples/test/mymethod.json schema
# output_* relative to package root
# target_* relative to orb_data/ (= blender_HDR/ + ground_truth/)
scores.json # evaluation scores (upstream scripts.test output)
Results (full split) vs. previous leaderboard best (Neural-PBIR)
| Metric | DiffReg-PBIR | Neural-PBIR |
|---|---|---|
| Relight PSNR-H ↑ | 27.22 | 26.01 |
| Relight PSNR-L ↑ | 34.98 | 33.26 |
| Relight SSIM ↑ | 0.981 | 0.979 |
| Relight LPIPS ↓ | 0.021 | 0.023 |
| Novel-view PSNR-H ↑ | 29.58 | 28.82 |
| Normal (angular) ↓ | 0.014 | 0.06 |
Reproduce: point orb_data/ at the official Stanford-ORB data root and run
python scripts/test.py -i test_results.json -o scores.json -s full from the
upstream repo. Prediction EXRs are 3-channel RGB, HDR only (the eval derives LDR).