Public
Fundus — Public Tier
(3 scenes)Full-access development tier with all data visible.
What you get
Measurements (y), ideal forward operator (H), spec ranges, ground truth (x_true), and true mismatch spec.
How to use
Load HDF5 → compare reconstruction vs x_true → check consistency → iterate.
What to submit
Reconstructed signals (x_hat) and corrected spec as HDF5.
Parameter Specifications
✓
True spec visible — use these exact values for Scenario III oracle reconstruction.
| Parameter | Spec Range | True Value | Unit |
|---|---|---|---|
| pupil_dilation | -0.5 – 1.0 | 0.25 | mm |
| focus | -0.25 – 0.5 | 0.125 | diopters |
| vignetting | -5.0 – 10.0 | 2.5 | % |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
21.12 dB
SSIM 0.3831
Scenario II (Mismatch)
10.76 dB
SSIM 0.3611
Scenario III (Oracle)
10.61 dB
SSIM 0.0307
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 22.60 | 0.4823 | 10.78 | 0.3639 | 10.25 | 0.0292 |
| scene_01 | 18.55 | 0.3352 | 11.03 | 0.3340 | 10.42 | 0.0310 |
| scene_02 | 20.14 | 0.2318 | 10.27 | 0.3891 | 11.39 | 0.0358 |
| scene_03 | 23.20 | 0.4831 | 10.96 | 0.3575 | 10.39 | 0.0265 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | Swin-Fundus + gradient | 0.795 | 32.67 | 0.95 | 0.94 | ✓ Certified | Li et al., IEEE TMI 2023 |
| 2 | cofe-Net + gradient | 0.747 | 30.14 | 0.919 | 0.89 | ✓ Certified | Shen et al., IEEE TMI 2020 |
| 3 | PnP-BM3D + gradient | 0.678 | 26.35 | 0.842 | 0.89 | ✓ Certified | Danielyan et al., 2012 |
| 4 | Richardson-Lucy + gradient | 0.611 | 23.1 | 0.735 | 0.93 | ✓ Certified | Richardson 1972 / Lucy 1974 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
Dataset
Format: HDF5
Scenes: 3
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%