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Models/M4Depth-d6 (VMD)

M4Depth-d6 (VMD)

Reported on 8 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 Vision4 results

Depth EstimationonMid-Air Dataset
RMSE· 2021-05-20
8.8641
SOTA
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
Depth EstimationonMid-Air Dataset
RMSE log· 2021-05-20
0.24571
best: 0.188 (M4Depth+U)
SOTA
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
Depth EstimationonMid-Air Dataset
Abs Rel· 2021-05-20
0.1425
best: 0.717 (Monodepth2)
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
Depth EstimationonMid-Air Dataset
SQ Rel· 2021-05-20
3.6798
best: 37.164 (Monodepth2)
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847

Methodology4 results

3DonMid-Air Dataset
RMSE· 2021-05-20
8.8641
SOTA
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
3DonMid-Air Dataset
RMSE log· 2021-05-20
0.24571
best: 0.188 (M4Depth+U)
SOTA
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
3DonMid-Air Dataset
Abs Rel· 2021-05-20
0.1425
best: 0.717 (Monodepth2)
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847
3DonMid-Air Dataset
SQ Rel· 2021-05-20
3.6798
best: 37.164 (Monodepth2)
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments arXiv:2105.09847