Dev
Flash LiDAR — Dev Tier
(5 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 |
|---|---|---|
| spad_jitter | -24.0 – 36.0 | ps |
| ambient_photon_rate | -2.4 – 3.6 | - |
| pile_up_distortion | -4.8 – 7.2 | athighflux |
| pixel_cross_talk | -1.2 – 1.8 | - |
Dev Tier Leaderboard
| # | Method | Score | PSNR | SSIM | Consistency | Trust | Source |
|---|---|---|---|---|---|---|---|
| 1 | DiffLiDAR + gradient | 0.775 | 33.0 | 0.953 | 0.82 | ✓ Certified | Gao et al., NeurIPS 2024 |
| 2 | PhysLiDAR + gradient | 0.759 | 31.02 | 0.931 | 0.88 | ✓ Certified | Chen et al., CVPR 2024 |
| 3 | SwinLiDAR + gradient | 0.755 | 31.06 | 0.932 | 0.86 | ✓ Certified | Wang et al., ICCV 2023 |
| 4 | TransLiDAR + gradient | 0.748 | 30.48 | 0.924 | 0.87 | ✓ Certified | Li et al., CVPR 2022 |
| 5 | NL-Means-LiDAR + gradient | 0.641 | 25.46 | 0.816 | 0.8 | ✓ Certified | Rapp & Goyal, IEEE TCI 2017 |
| 6 | SPADnet + gradient | 0.551 | 21.3 | 0.659 | 0.87 | ✓ Certified | Lindell et al., SIGGRAPH 2018 |
| 7 | Coates-Hist + gradient | 0.551 | 21.61 | 0.673 | 0.83 | ✓ Certified | Coates, J. Phys. E 1968 |
| 8 | DnCNN-LiDAR + gradient | 0.537 | 21.37 | 0.662 | 0.79 | ✓ Certified | Peng et al., ECCV 2020 |
| 9 | MLE-SPAD + gradient | 0.483 | 19.25 | 0.562 | 0.83 | ✓ Certified | Kirmani et al., Science 2014 |
Visible Data Fields
y
H_ideal
spec_ranges
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%