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Models/DSS (Res2Net-50)

DSS (Res2Net-50)

Reported on 48 benchmarks across 6 tasks · 1 paper · 48 SOTA

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

Methodology32 results

  • 3DonECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 3DonDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D ClassificationonDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 2D Object DetectiononDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • 16konDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169

Computer Vision16 results

  • Object DetectiononECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • Object DetectiononDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononECSSD
    F-measure· 2019-04-02
    0.926
    best: 0.961 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononECSSD
    MAE· 2019-04-02
    0.056
    best: 0.021 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononPASCAL-S
    F-measure· 2019-04-02
    0.841
    best: 0.909 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononPASCAL-S
    MAE· 2019-04-02
    0.099
    best: 0.039 (CFDN)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononHKU-IS
    F-measure· 2019-04-02
    0.905
    best: 0.955 (InSPyReNet)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononHKU-IS
    MAE· 2019-04-02
    0.05
    best: 0.019 (M3Net-S)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononDUT-OMRON
    F-measure· 2019-04-02
    0.8
    best: 0.849 (TRACER-TE7)
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169
  • RGB Salient Object DetectiononDUT-OMRON
    MAE· 2019-04-02
    0.071
    best: 0.036 (BiRefNet (DUTS, UHRSD))
    SOTA
    Res2Net: A New Multi-scale Backbone ArchitecturearXiv:1904.01169