Public
Panorama — Public Tier
(5 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 |
|---|---|---|---|
| focus_step | -2.0 – 4.0 | 1.0 | μm |
| registration | -0.5 – 1.0 | 0.25 | pixels |
| exposure_variation | -3.0 – 6.0 | 1.5 | % |
InverseNet Baseline Scores
Method: CPU_baseline — Mismatch parameter: nominal
Scenario I (Ideal)
7.77 dB
SSIM 0.3772
Scenario II (Mismatch)
7.61 dB
SSIM 0.1940
Scenario III (Oracle)
15.93 dB
SSIM 0.4222
Per-scene breakdown (4 scenes)
| Scene | PSNR I | SSIM I | PSNR II | SSIM II | PSNR III | SSIM III |
|---|---|---|---|---|---|---|
| scene_00 | 7.57 | 0.3615 | 7.48 | 0.1918 | 15.88 | 0.4337 |
| scene_01 | 7.70 | 0.3833 | 7.85 | 0.1983 | 15.89 | 0.4210 |
| scene_02 | 7.97 | 0.3846 | 7.45 | 0.1929 | 16.02 | 0.4175 |
| scene_03 | 7.84 | 0.3794 | 7.67 | 0.1931 | 15.94 | 0.4166 |
Public Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | PanoFormer + gradient | 0.784 | 32.79 | 0.951 | 0.88 | ✓ Certified | Image stitching transformer, 2024 |
| 2 | UDIS + gradient | 0.755 | 30.81 | 0.928 | 0.88 | ✓ Certified | Nie et al., ICCV 2021 |
| 3 | APAP + gradient | 0.699 | 27.71 | 0.875 | 0.86 | ✓ Certified | Zaragoza et al., CVPR 2013 |
| 4 | SIFT-RANSAC + gradient | 0.625 | 24.21 | 0.776 | 0.86 | ✓ Certified | Lowe, IJCV 2004 |
Visible Data Fields
y
H_ideal
spec_ranges
x_true
true_spec
Dataset
Format: HDF5
Scenes: 5
Scoring Formula
0.4 × PSNR_norm + 0.4 × SSIM + 0.2 × (1 − ‖y − Ĥx̂‖/‖y‖)
PSNR: 40%
SSIM: 40%
Consistency: 20%