Public

ToF Camera — 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
modulation_freq 19.9 – 20.2 20.05 MHz
multipath -5.0 – 10.0 2.5 %
phase_nonlinearity -2.0 – 4.0 1.0 deg

InverseNet Baseline Scores

Method: CPU_baseline — Mismatch parameter: nominal

Scenario I (Ideal)

5.60 dB

SSIM 0.4704

Scenario II (Mismatch)

5.45 dB

SSIM 0.2015

Scenario III (Oracle)

18.47 dB

SSIM 0.2342

Per-scene breakdown (4 scenes)
Scene PSNR I SSIM I PSNR II SSIM II PSNR III SSIM III
scene_00 5.53 0.4672 5.46 0.1995 18.40 0.2341
scene_01 5.81 0.4796 6.03 0.1934 18.47 0.2267
scene_02 5.66 0.4660 5.08 0.2092 18.61 0.2372
scene_03 5.39 0.4690 5.23 0.2041 18.40 0.2387

Public Tier Leaderboard

# Method Score PSNR SSIM Consistency Trust Source
1 MPI-Former + gradient 0.768 31.5 0.937 0.89 ✓ Certified Multi-path interference correction, 2023
2 DeepToF + gradient 0.749 30.66 0.926 0.86 ✓ Certified Marco et al., ECCV 2018
3 PnP-ToF + gradient 0.690 26.46 0.844 0.94 ✓ Certified PnP with depth prior for ToF
4 Phase Unwrap + gradient 0.595 22.42 0.708 0.94 ✓ Certified Bamji et al., IEEE SSC 2015

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%
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