Hidden
CACTI — Hidden Tier
(6 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 |
|---|---|---|
| mask_dx | 0.35 – 0.95 | px |
| mask_dy | 0.2 – 0.6 | px |
| mask_rotation | 0.07 – 0.37 | deg |
| mask_blur | 0.1 – 0.6 | px |
| clock_offset | -0.02 – 0.18 | frames |
| gain_drift | 0.99 – 1.09 | |
| offset_drift | -0.005 – 0.035 |
Hidden Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | ELP-Unfolding + blind cal | 0.000 | 0.0 | 0.0 | 0.0 | ✓ Certified | InverseNet Scenario IV (blind cal, improved hybrid grid search) |
| 2 | EfficientSCI + blind cal | 0.000 | 0.0 | 0.0 | 0.0 | ✓ Certified | InverseNet Scenario IV (blind cal, improved hybrid grid search) |
| 3 | HiSViT-9 + blind cal | 0.000 | 0.0 | 0.0 | 0.0 | ✓ Certified | InverseNet Scenario IV (blind cal, improved hybrid grid search) |
| 4 | GAP-TV + blind cal | 0.000 | 0.0 | 0.0 | 0.0 | ✓ Certified | InverseNet Scenario IV (blind cal, improved hybrid grid search) |
| 5 | PnP-FFDNet + blind cal | 0.000 | 0.0 | 0.0 | 0.0 | ✓ Certified | InverseNet Scenario IV (blind cal, improved hybrid grid search) |
Dataset
Scenes: 6
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%