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Models/F2DNet

F2DNet

Reported on 10 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Robots5 results

  • Autonomous VehiclesonCaltech
    Heavy MR^-2· 2022-03-04
    38.7
    SOTA
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Autonomous VehiclesonCaltech
    Reasonable Miss Rate· 2022-03-04
    2.2
    best: 24.8 (LDCF)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Autonomous VehiclesonCityPersons
    Heavy MR^-2· 2022-03-04
    32.6
    best: 56.9 (RepLoss)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Autonomous VehiclesonCityPersons
    Reasonable MR^-2· 2022-03-04
    8.7
    best: 15.5 (TLL)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Autonomous VehiclesonCityPersons
    Small MR^-2· 2022-03-04
    11.3
    best: 25.6 (FRCNN)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331

Computer Vision5 results

  • Pedestrian DetectiononCaltech
    Heavy MR^-2· 2022-03-04
    38.7
    SOTA
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Pedestrian DetectiononCaltech
    Reasonable Miss Rate· 2022-03-04
    2.2
    best: 24.8 (LDCF)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Pedestrian DetectiononCityPersons
    Heavy MR^-2· 2022-03-04
    32.6
    best: 56.9 (RepLoss)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Pedestrian DetectiononCityPersons
    Reasonable MR^-2· 2022-03-04
    8.7
    best: 15.5 (TLL)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331
  • Pedestrian DetectiononCityPersons
    Small MR^-2· 2022-03-04
    11.3
    best: 25.6 (FRCNN)
    F2DNet: Fast Focal Detection Network for Pedestrian DetectionarXiv:2203.02331