MiDaS

Reported on 4 benchmarks across 2 tasks · 1 paper · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision2 results

Depth EstimationonETH3D
Delta < 1.25· 2019-07-02
0.0752
best: 0.981 (Distill Any Depth)
SOTA
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer arXiv:1907.01341
Depth EstimationonETH3D
absolute relative error· 2019-07-02
0.0184
best: 0.0121 (HDN)
SOTA
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer arXiv:1907.01341

Methodology2 results

3DonETH3D
Delta < 1.25· 2019-07-02
0.0752
best: 0.981 (Distill Any Depth)
SOTA
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer arXiv:1907.01341
3DonETH3D
absolute relative error· 2019-07-02
0.0184
best: 0.0121 (HDN)
SOTA
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer arXiv:1907.01341