Dev
CACTI — Dev Tier
(6 scenes)Blind evaluation tier — no ground truth available.
What you get
Measurements (y), ideal forward operator (H), and spec ranges only.
How to use
Apply your pipeline from the Public tier. Use consistency as self-check.
What to submit
Reconstructed signals and corrected spec. Scored server-side.
Parameter Specifications
🔒
True spec hidden — estimate parameters from spec ranges below.
| Parameter | Spec Range | Unit |
|---|---|---|
| mask_dx | 0.05 – 0.65 | px |
| mask_dy | 0.0 – 0.4 | px |
| mask_rotation | -0.07 – 0.23 | deg |
| mask_blur | -0.15 – 0.35 | px |
| clock_offset | -0.13 – 0.07 | frames |
| gain_drift | 0.93 – 1.03 | |
| offset_drift | -0.03 – 0.01 |
Dev 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) |
Visible Data Fields
y
H_ideal
spec_ranges
Dataset
Format: HDF5
Scenes: 6
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%