Hidden
Photometric Stereo — Hidden Tier
(5 scenes)Fully blind server-side evaluation — no data download.
What you get
No data downloadable. Algorithm runs server-side on hidden measurements.
How to use
Package algorithm as Docker container / Python script. Submit via link.
What to submit
Containerized algorithm accepting y + H, outputting x_hat + corrected spec.
Parameter Specifications
🔒
True spec hidden — blind evaluation, only ranges available.
| Parameter | Spec Range | Unit |
|---|---|---|
| light_direction_error | -0.7 – 2.3 | degpersource |
| light_intensity_calibration | 0.972 – 1.092 | - |
| non_lambertian_surface_fraction | -4.2 – 13.8 | - |
| cast_shadow_fraction | -2.1 – 6.9 | ofpixels |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PS-Transformer + gradient | 0.643 | 24.98 | 0.802 | 0.86 | ✓ Certified | Ikehata, ICCV 2023 |
| 2 | CNN-PS + gradient | 0.631 | 24.83 | 0.797 | 0.82 | ✓ Certified | Ikehata, ECCV 2018 |
| 3 | Robust PCA + gradient | 0.604 | 24.11 | 0.772 | 0.77 | ✓ Certified | Wu et al., ECCV 2010 |
| 4 | LS Normal Est. + gradient | 0.516 | 20.49 | 0.622 | 0.81 | ✓ Certified | Woodham, Opt. Eng. 1980 |
Dataset
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%