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Models/SINet

SINet

Reported on 42 benchmarks across 7 tasks

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

Methodology24 results

  • 3DonCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • 3DonCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • 3DonCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • 3DonCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • 3DonCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • 3DonCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)
  • 2D ClassificationonCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • 2D ClassificationonCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • 2D ClassificationonCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • 2D ClassificationonCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • 2D ClassificationonCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • 2D ClassificationonCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)
  • 2D Object DetectiononCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • 2D Object DetectiononCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • 2D Object DetectiononCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • 2D Object DetectiononCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • 2D Object DetectiononCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • 2D Object DetectiononCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)
  • 16konCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • 16konCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • 16konCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • 16konCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • 16konCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • 16konCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)

Computer Vision18 results

  • Object DetectiononCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • Object DetectiononCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • Object DetectiononCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • Object DetectiononCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • Object DetectiononCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • Object DetectiononCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)
  • Camouflaged Object SegmentationonCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • Camouflaged Object SegmentationonCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • Camouflaged Object SegmentationonCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • Camouflaged Object SegmentationonCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • Camouflaged Object SegmentationonCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • Camouflaged Object SegmentationonCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)
  • Object SegmentationonCOD
    MAE
    0.092
    best: 0.013 (FOCUS)
  • Object SegmentationonCOD
    S-Measure
    0.685
    best: 0.913 (BiRefNet)
  • Object SegmentationonCOD
    Weighted F-Measure
    0.352
    best: 0.883 (FOCUS)
  • Object SegmentationonCAMO
    MAE
    0.1
    best: 0.025 (FOCUS)
  • Object SegmentationonCAMO
    S-Measure
    0.751
    best: 0.912 (FOCUS)
  • Object SegmentationonCAMO
    Weighted F-Measure
    0.606
    best: 0.904 (FOCUS)