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Models/EGNet

EGNet

Reported on 133 benchmarks across 9 tasks

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

Methodology76 results

  • 3DonCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • 3DonCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • 3DonCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • 3DonCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • 3DonCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • 3DonCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • 3DonCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • 3DonCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • 3DonCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • 3DonCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • 3DonCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • 3DonCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • 3DonCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • 3DonCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • 3DonCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • 3DonPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • 3DonCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • 3DonCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • 3DonCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)
  • 2D ClassificationonCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • 2D ClassificationonCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • 2D ClassificationonCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • 2D ClassificationonCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • 2D ClassificationonCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • 2D ClassificationonCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • 2D ClassificationonCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • 2D ClassificationonCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • 2D ClassificationonCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • 2D ClassificationonCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • 2D ClassificationonCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • 2D ClassificationonCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • 2D ClassificationonCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • 2D ClassificationonCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • 2D ClassificationonCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • 2D ClassificationonPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • 2D ClassificationonCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • 2D ClassificationonCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • 2D ClassificationonCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)
  • 2D Object DetectiononCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • 2D Object DetectiononCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • 2D Object DetectiononCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • 2D Object DetectiononCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • 2D Object DetectiononCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • 2D Object DetectiononCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • 2D Object DetectiononCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • 2D Object DetectiononCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • 2D Object DetectiononCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • 2D Object DetectiononCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • 2D Object DetectiononCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • 2D Object DetectiononCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • 2D Object DetectiononCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • 2D Object DetectiononCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • 2D Object DetectiononCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • 2D Object DetectiononPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • 2D Object DetectiononCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • 2D Object DetectiononCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • 2D Object DetectiononCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)
  • 16konCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • 16konCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • 16konCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • 16konCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • 16konCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • 16konCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • 16konCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • 16konCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • 16konCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • 16konCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • 16konCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • 16konCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • 16konCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • 16konCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • 16konCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • 16konPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • 16konCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • 16konCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • 16konCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)

Computer Vision57 results

  • Saliency DetectiononCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • Saliency DetectiononCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • Saliency DetectiononCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • Saliency DetectiononCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • Saliency DetectiononCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • Saliency DetectiononCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • Saliency DetectiononCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • Saliency DetectiononCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • Saliency DetectiononCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • Saliency DetectiononCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • Saliency DetectiononCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • Saliency DetectiononCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • Object DetectiononCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • Object DetectiononCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • Object DetectiononCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • Object DetectiononCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • Object DetectiononCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • Object DetectiononCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • Object DetectiononCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • Object DetectiononCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • Object DetectiononCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • Object DetectiononCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • Object DetectiononCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • Object DetectiononCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • Object DetectiononCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • Object DetectiononCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • Object DetectiononCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • Object DetectiononPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • Object DetectiononCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • Object DetectiononCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • Object DetectiononCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)
  • RGB Salient Object DetectiononCoSOD3k
    MAE
    0.119
    best: 0.062 (GCoNet+)
  • RGB Salient Object DetectiononCoSOD3k
    S-measure
    0.7619
    best: 0.851 (DMT)
  • RGB Salient Object DetectiononCoSOD3k
    max E-measure
    0.793
    best: 0.901 (GCoNet+)
  • RGB Salient Object DetectiononCoSOD3k
    max F-measure
    0.702
    best: 0.835 (DMT)
  • RGB Salient Object DetectiononCoCA
    Mean F-measure
    0.391
    best: 0.612 (GCoNet+)
  • RGB Salient Object DetectiononCoCA
    S-measure
    0.603
    best: 0.738 (GCoNet+)
  • RGB Salient Object DetectiononCoCA
    max F-measure
    0.404
    best: 0.637 (GCoNet+)
  • RGB Salient Object DetectiononCoCA
    mean E-measure
    0.622
    best: 0.783 (GCoNet+)
  • RGB Salient Object DetectiononCoSal2015
    MAE
    0.099
    best: 0.045 (DMT)
  • RGB Salient Object DetectiononCoSal2015
    S-measure
    0.818
    best: 0.897 (DMT)
  • RGB Salient Object DetectiononCoSal2015
    max E-measure
    0.843
    best: 0.936 (DMT)
  • RGB Salient Object DetectiononCoSal2015
    max F-measure
    0.786
    best: 0.905 (DMT)
  • Camouflaged Object SegmentationonCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • Camouflaged Object SegmentationonCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • Camouflaged Object SegmentationonCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • Camouflaged Object SegmentationonPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • Camouflaged Object SegmentationonCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • Camouflaged Object SegmentationonCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • Camouflaged Object SegmentationonCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)
  • Object SegmentationonCOD
    MAE
    0.056
    best: 0.013 (FOCUS)
  • Object SegmentationonCOD
    S-Measure
    0.737
    best: 0.913 (BiRefNet)
  • Object SegmentationonCOD
    Weighted F-Measure
    0.509
    best: 0.883 (FOCUS)
  • Object SegmentationonPCOD_1200
    S-Measure
    0.861
    best: 0.922 (CMX)
  • Object SegmentationonCAMO
    MAE· uses extra data
    0.104
    best: 0.025 (FOCUS)
  • Object SegmentationonCAMO
    S-Measure· uses extra data
    0.732
    best: 0.912 (FOCUS)
  • Object SegmentationonCAMO
    Weighted F-Measure· uses extra data
    0.583
    best: 0.904 (FOCUS)