Dev
SPC-Kronecker — Dev Tier
(20 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 |
|---|---|---|
| gain_decay_alpha | -0.0015 – 0.0075 | 1/measurement |
| noise_sigma | 0.0 – 0.04 |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PnP-DRUNet + blind cal | 0.736 | 27.02 | 0.828 | 0.94 | ✓ Certified | InverseNet Scenario IV |
| 2 | FISTA-TV (tuned) + blind cal | 0.710 | 25.93 | 0.781 | 0.95 | ✓ Certified | InverseNet Scenario IV |
| 3 | FISTA-TV (paper) + blind cal | 0.704 | 25.75 | 0.767 | 0.96 | ✓ Certified | InverseNet Scenario IV |
| 4 | HATNet + FISTA-TV + blind cal | 0.702 | 25.95 | 0.768 | 0.94 | ✓ Certified | InverseNet Scenario IV |
| 5 | ISTA-Net + blind cal | 0.686 | 26.05 | 0.701 | 0.99 | ✓ Certified | InverseNet Scenario IV |
| 6 | PnP-BM3D + blind cal | 0.550 | 18.36 | 0.511 | 0.99 | ✓ Certified | InverseNet Scenario IV |
Visible Data Fields
y
H_ideal
spec_ranges
Dataset
Format: HDF5
Scenes: 20
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%