Dev
Active Thermography (IR) — Dev Tier
(3 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 |
|---|---|---|
| emissivity_error | 0.938 – 0.968 | - |
| heat_source_power_drift | 0.976 – 1.036 | - |
| background_temperature | 23.8 – 26.8 | C |
| integration_time_offset | -0.024 – 0.036 | s |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | ThermoFormer + gradient | 0.743 | 30.51 | 0.924 | 0.84 | ✓ Certified | Transformer for thermography reconstruction, 2024 |
| 2 | DiffusionThermo + gradient | 0.678 | 26.45 | 0.844 | 0.88 | ✓ Certified | Score-based diffusion for thermal imaging, 2024 |
| 3 | PINN-Thermo + gradient | 0.658 | 26.27 | 0.839 | 0.8 | ✓ Certified | Raissi et al. 2019; thermography extension 2024 |
| 4 | U-Net Thermo + gradient | 0.623 | 24.83 | 0.797 | 0.78 | ✓ Certified | Fang et al., IEEE Trans. Instrum. Meas. 2023 |
| 5 | ThermoNet + gradient | 0.568 | 22.35 | 0.705 | 0.81 | ✓ Certified | Hu et al., NDT&E Int. 2024 |
| 6 | PnP-ADMM + gradient | 0.564 | 22.38 | 0.706 | 0.79 | ✓ Certified | Venkatakrishnan et al., IEEE GlobalSIP 2013 |
| 7 | PCT + gradient | 0.524 | 20.37 | 0.616 | 0.87 | ✓ Certified | Maldague & Marinetti, J. Appl. Phys. 1996 |
| 8 | TSR + gradient | 0.502 | 20.09 | 0.603 | 0.8 | ✓ Certified | Shepard, Thermosense 2001; Shepard et al., Opt. Eng. 2003 |
Visible Data Fields
y
H_ideal
spec_ranges
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%