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Models/Monodepth2

Monodepth2

Reported on 19 benchmarks across 3 tasks · 2 papers · 10 SOTA

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

Computer Vision11 results

  • Depth EstimationonMid-Air Dataset
    Abs Rel· 2018-06-04
    0.717
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonMid-Air Dataset
    SQ Rel· 2018-06-04
    37.164
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonMake3D
    Abs Rel· 2018-06-04
    0.322
    best: 0.424 (GCNDepth)
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonMake3D
    RMSE· 2018-06-04
    7.417
    best: 0.232 (AnyNet [88])
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonMake3D
    Sq Rel· 2018-06-04
    3.589
    best: 4.9 (SharinGAN)
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonSCARED-C
    mDERS· 2024-09-30
    0.2608
    best: 0.3134 (AF-SfMLearner )
    EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionarXiv:2409.19930
  • Depth EstimationonMid-Air Dataset
    RMSE· 2018-06-04
    74.552
    best: 8.8641 (M4Depth-d6 (VMD))
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Depth EstimationonMid-Air Dataset
    RMSE log· 2018-06-04
    0.882
    best: 0.188 (M4Depth+U)
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Camera Pose EstimationonKITTI Odometry Benchmark
    Absolute Trajectory Error [m]· 2018-06-04
    93.04
    best: 20.83 (SCIPaD)
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Camera Pose EstimationonKITTI Odometry Benchmark
    Average Rotational Error er[%]· 2018-06-04
    20.72
    best: 2.205 (Manydepth2)
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • Camera Pose EstimationonKITTI Odometry Benchmark
    Average Translational Error et[%]· 2018-06-04
    43.21
    best: 7.15 (Manydepth2)
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260

Methodology8 results

  • 3DonMid-Air Dataset
    Abs Rel· 2018-06-04
    0.717
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonMid-Air Dataset
    SQ Rel· 2018-06-04
    37.164
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonMake3D
    Abs Rel· 2018-06-04
    0.322
    best: 0.424 (GCNDepth)
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonMake3D
    RMSE· 2018-06-04
    7.417
    best: 0.232 (AnyNet [88])
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonMake3D
    Sq Rel· 2018-06-04
    3.589
    best: 4.9 (SharinGAN)
    SOTA
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonSCARED-C
    mDERS· 2024-09-30
    0.2608
    best: 0.3134 (AF-SfMLearner )
    EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth PredictionarXiv:2409.19930
  • 3DonMid-Air Dataset
    RMSE· 2018-06-04
    74.552
    best: 8.8641 (M4Depth-d6 (VMD))
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260
  • 3DonMid-Air Dataset
    RMSE log· 2018-06-04
    0.882
    best: 0.188 (M4Depth+U)
    Digging Into Self-Supervised Monocular Depth EstimationarXiv:1806.01260