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Models/FGRN

FGRN

Reported on 248 benchmarks across 8 tasks

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

Computer Vision124 results

  • VideoonDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • VideoonDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • VideoonDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • VideoonDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • VideoonFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • VideoonFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • VideoonFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • VideoonFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • VideoonUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • VideoonUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • VideoonUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • VideoonVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • VideoonVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • VideoonVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • VideoonDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • VideoonDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • VideoonDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • VideoonDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • VideoonDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • VideoonDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • VideoonDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • VideoonViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • VideoonViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • VideoonViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • VideoonDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • VideoonDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • VideoonDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • VideoonMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • VideoonMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • VideoonMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • VideoonMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • Object DetectiononDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • Object DetectiononDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • Object DetectiononDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • Object DetectiononDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • Object DetectiononFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • Object DetectiononFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • Object DetectiononFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • Object DetectiononFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • Object DetectiononUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • Object DetectiononUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • Object DetectiononUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • Object DetectiononVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • Object DetectiononVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • Object DetectiononVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • Object DetectiononDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • Object DetectiononDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • Object DetectiononDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • Object DetectiononDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • Object DetectiononDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • Object DetectiononDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • Object DetectiononDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • Object DetectiononViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • Object DetectiononViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • Object DetectiononViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • Object DetectiononDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • Object DetectiononDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • Object DetectiononDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • Object DetectiononMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • Object DetectiononMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • Object DetectiononMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • Object DetectiononMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • Video Object SegmentationonDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • Video Object SegmentationonDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • Video Object SegmentationonDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • Video Object SegmentationonDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • Video Object SegmentationonFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • Video Object SegmentationonFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • Video Object SegmentationonFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • Video Object SegmentationonFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • Video Object SegmentationonUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • Video Object SegmentationonUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • Video Object SegmentationonUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • Video Object SegmentationonVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • Video Object SegmentationonVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • Video Object SegmentationonVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • Video Object SegmentationonDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • Video Object SegmentationonDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • Video Object SegmentationonDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • Video Object SegmentationonDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • Video Object SegmentationonDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • Video Object SegmentationonDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • Video Object SegmentationonDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • Video Object SegmentationonViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • Video Object SegmentationonViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • Video Object SegmentationonViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • Video Object SegmentationonDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • Video Object SegmentationonDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • Video Object SegmentationonDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • Video Object SegmentationonMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • Video Object SegmentationonMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • Video Object SegmentationonMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • Video Object SegmentationonMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • RGB Salient Object DetectiononDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • RGB Salient Object DetectiononDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • RGB Salient Object DetectiononDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • RGB Salient Object DetectiononDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • RGB Salient Object DetectiononFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • RGB Salient Object DetectiononFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • RGB Salient Object DetectiononFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • RGB Salient Object DetectiononFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • RGB Salient Object DetectiononUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • RGB Salient Object DetectiononUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • RGB Salient Object DetectiononUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • RGB Salient Object DetectiononVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • RGB Salient Object DetectiononVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • RGB Salient Object DetectiononVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • RGB Salient Object DetectiononDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • RGB Salient Object DetectiononDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • RGB Salient Object DetectiononDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • RGB Salient Object DetectiononDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • RGB Salient Object DetectiononDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • RGB Salient Object DetectiononDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • RGB Salient Object DetectiononDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • RGB Salient Object DetectiononViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • RGB Salient Object DetectiononViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • RGB Salient Object DetectiononViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • RGB Salient Object DetectiononDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • RGB Salient Object DetectiononDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • RGB Salient Object DetectiononDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • RGB Salient Object DetectiononMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • RGB Salient Object DetectiononMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • RGB Salient Object DetectiononMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • RGB Salient Object DetectiononMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)

Methodology124 results

  • 3DonDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • 3DonDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • 3DonDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • 3DonDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • 3DonFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • 3DonFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • 3DonFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • 3DonFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • 3DonUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • 3DonUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • 3DonUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • 3DonVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • 3DonVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • 3DonVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • 3DonDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • 3DonDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • 3DonDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • 3DonDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • 3DonDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • 3DonDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • 3DonDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • 3DonViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • 3DonViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • 3DonViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • 3DonDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • 3DonDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • 3DonDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • 3DonMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • 3DonMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • 3DonMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • 3DonMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • 2D ClassificationonDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • 2D ClassificationonDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • 2D ClassificationonDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • 2D ClassificationonDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • 2D ClassificationonFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • 2D ClassificationonFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • 2D ClassificationonFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • 2D ClassificationonFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • 2D ClassificationonUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • 2D ClassificationonUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • 2D ClassificationonUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • 2D ClassificationonVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • 2D ClassificationonVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • 2D ClassificationonVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • 2D ClassificationonDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • 2D ClassificationonDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • 2D ClassificationonDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • 2D ClassificationonDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • 2D ClassificationonDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • 2D ClassificationonDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • 2D ClassificationonDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • 2D ClassificationonViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • 2D ClassificationonViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • 2D ClassificationonViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • 2D ClassificationonDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • 2D ClassificationonDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • 2D ClassificationonDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • 2D ClassificationonMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • 2D ClassificationonMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • 2D ClassificationonMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • 2D ClassificationonMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • 2D Object DetectiononDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • 2D Object DetectiononDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • 2D Object DetectiononDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • 2D Object DetectiononDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • 2D Object DetectiononFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • 2D Object DetectiononFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • 2D Object DetectiononFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • 2D Object DetectiononFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • 2D Object DetectiononUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • 2D Object DetectiononUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • 2D Object DetectiononUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • 2D Object DetectiononVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • 2D Object DetectiononVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • 2D Object DetectiononVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • 2D Object DetectiononDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • 2D Object DetectiononDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • 2D Object DetectiononDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • 2D Object DetectiononDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • 2D Object DetectiononDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • 2D Object DetectiononDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • 2D Object DetectiononDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • 2D Object DetectiononViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • 2D Object DetectiononViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • 2D Object DetectiononViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • 2D Object DetectiononDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • 2D Object DetectiononDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • 2D Object DetectiononDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • 2D Object DetectiononMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • 2D Object DetectiononMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • 2D Object DetectiononMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • 2D Object DetectiononMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)
  • 16konDAVSOD-easy35
    Average MAE· uses extra data
    0.095
    best: 0.066 (RealFlow)
  • 16konDAVSOD-easy35
    S-Measure· uses extra data
    0.701
    best: 0.803 (RealFlow)
  • 16konDAVSOD-easy35
    max E-Measure· uses extra data
    0.765
    best: 0.806 (SSAV)
  • 16konDAVSOD-easy35
    max F-Measure· uses extra data
    0.589
    best: 0.732 (RealFlow)
  • 16konFBMS-59
    AVERAGE MAE· uses extra data
    0.088
    best: 0.028 (RealFlow)
  • 16konFBMS-59
    MAX E-MEASURE· uses extra data
    0.863
    best: 0.926 (SSAV)
  • 16konFBMS-59
    MAX F-MEASURE· uses extra data
    0.767
    best: 0.906 (RealFlow)
  • 16konFBMS-59
    S-Measure· uses extra data
    0.809
    best: 0.926 (RealFlow)
  • 16konUVSD
    Average MAE· uses extra data
    0.042
    best: 0.018 (PDB)
  • 16konUVSD
    S-Measure· uses extra data
    0.745
    best: 0.901 (PDB)
  • 16konUVSD
    max E-measure· uses extra data
    0.887
    best: 0.975 (PDB)
  • 16konVOS-T
    Average MAE· uses extra data
    0.097
    best: 0.049 (RCRNet+NER)
  • 16konVOS-T
    S-Measure· uses extra data
    0.715
    best: 0.872 (RCRNet+NER)
  • 16konVOS-T
    max E-measure· uses extra data
    0.797
    best: 0.856 (RCRNet+NER)
  • 16konDAVSOD-Difficult20
    Average MAE· uses extra data
    0.131
    best: 0.107 (PDB)
  • 16konDAVSOD-Difficult20
    S-Measure· uses extra data
    0.608
    best: 0.619 (SSAV)
  • 16konDAVSOD-Difficult20
    max E-measure· uses extra data
    0.698
  • 16konDAVIS-2016
    AVERAGE MAE· uses extra data
    0.043
    best: 0.01 (RealFlow)
  • 16konDAVIS-2016
    MAX E-MEASURE· uses extra data
    0.917
    best: 0.966 (MBNM)
  • 16konDAVIS-2016
    MAX F-MEASURE· uses extra data
    0.783
    best: 0.939 (RealFlow)
  • 16konDAVIS-2016
    S-Measure· uses extra data
    0.838
    best: 0.945 (RealFlow)
  • 16konViSal
    Average MAE· uses extra data
    0.045
    best: 0.01 (RealFlow)
  • 16konViSal
    S-Measure· uses extra data
    0.861
    best: 0.962 (RealFlow)
  • 16konViSal
    max E-measure· uses extra data
    0.945
    best: 0.987 (UFO)
  • 16konDAVSOD-Normal25
    Average MAE· uses extra data
    0.126
    best: 0.117 (SSAV)
  • 16konDAVSOD-Normal25
    S-Measure· uses extra data
    0.638
    best: 0.661 (SSAV)
  • 16konDAVSOD-Normal25
    max E-measure· uses extra data
    0.7
    best: 0.723 (SSAV)
  • 16konMCL
    AVERAGE MAE· uses extra data
    0.044
    best: 0.021 (PDB)
  • 16konMCL
    MAX E-MEASURE· uses extra data
    0.817
    best: 0.911 (PDB)
  • 16konMCL
    MAX F-MEASURE· uses extra data
    0.625
    best: 0.773 (SSAV)
  • 16konMCL
    S-Measure· uses extra data
    0.709
    best: 0.856 (PDB)