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Models/MuG-W

MuG-W

Reported on 56 benchmarks across 3 tasks · 1 paper · 12 SOTA

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

Computer Vision56 results

  • VideoonDAVIS 2017 (val)
    F-measure (Decay)· 2020-03-10
    37.4
    best: 85.3 (STCN)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    Jaccard (Decay)· 2020-03-10
    32.5
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    F-measure (Decay)· 2020-03-10
    27.2
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    Jaccard (Decay)· 2020-03-10
    26.4
    best: 28.9 (BVS)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Decay)· 2020-03-10
    37.4
    best: 85.3 (STCN)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Decay)· 2020-03-10
    32.5
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    F-measure (Decay)· 2020-03-10
    27.2
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Decay)· 2020-03-10
    26.4
    best: 28.9 (BVS)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Decay)· 2020-03-10
    37.4
    best: 85.3 (STCN)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Decay)· 2020-03-10
    32.5
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    F-measure (Decay)· 2020-03-10
    27.2
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    Jaccard (Decay)· 2020-03-10
    26.4
    best: 28.9 (BVS)
    SOTA
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    F-measure (Mean)· 2020-03-10
    58
    best: 93.4 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    F-measure (Recall)· 2020-03-10
    62.2
    best: 94.6 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    J&F· 2020-03-10
    56.05
    best: 90.7 (SAM2)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    Jaccard (Mean)· 2020-03-10
    54.1
    best: 87.5 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (val)
    Jaccard (Recall)· 2020-03-10
    60.5
    best: 91.4 (ISVOS (MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    F-measure (Mean)· 2020-03-10
    63.6
    best: 94.7 (SwinB-DeAOT-L)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    F-measure (Recall)· 2020-03-10
    67.7
    best: 97.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    J&F· 2020-03-10
    64.65
    best: 93.4 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    Jaccard (Mean)· 2020-03-10
    65.7
    best: 92.5 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2016
    Jaccard (Recall)· 2020-03-10
    77.7
    best: 98.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    F-measure (Decay)· 2020-03-10
    -1.7
    best: 37.2 (RGMP)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    F-measure (Mean)· 2020-03-10
    44.5
    best: 91.4 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    F-measure (Recall)· 2020-03-10
    46.6
    best: 89.7 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    J&F· 2020-03-10
    41.7
    best: 88.1 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    Jaccard (Decay)· 2020-03-10
    -2.7
    best: 35.7 (RVOS)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    Jaccard (Mean)· 2020-03-10
    38.9
    best: 84.7 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • VideoonDAVIS 2017 (test-dev)
    Jaccard (Recall)· 2020-03-10
    44.3
    best: 85.5 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Mean)· 2020-03-10
    58
    best: 93.4 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Recall)· 2020-03-10
    62.2
    best: 94.6 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    J&F· 2020-03-10
    56.05
    best: 90.7 (SAM2)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Mean)· 2020-03-10
    54.1
    best: 87.5 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Recall)· 2020-03-10
    60.5
    best: 91.4 (ISVOS (MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· 2020-03-10
    63.6
    best: 94.7 (SwinB-DeAOT-L)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    F-measure (Recall)· 2020-03-10
    67.7
    best: 97.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    J&F· 2020-03-10
    64.65
    best: 93.4 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· 2020-03-10
    65.7
    best: 92.5 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Recall)· 2020-03-10
    77.7
    best: 98.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    F-measure (Decay)· 2020-03-10
    -1.7
    best: 37.2 (RGMP)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    F-measure (Mean)· 2020-03-10
    44.5
    best: 91.4 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    F-measure (Recall)· 2020-03-10
    46.6
    best: 89.7 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    J&F· 2020-03-10
    41.7
    best: 88.1 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    Jaccard (Decay)· 2020-03-10
    -2.7
    best: 35.7 (RVOS)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    Jaccard (Mean)· 2020-03-10
    38.9
    best: 84.7 (Cutie+ (base, MEGA))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    Jaccard (Recall)· 2020-03-10
    44.3
    best: 85.5 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Mean)· 2020-03-10
    58
    best: 93.4 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Recall)· 2020-03-10
    62.2
    best: 94.6 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    J&F· 2020-03-10
    56.05
    best: 90.7 (SAM2)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Mean)· 2020-03-10
    54.1
    best: 87.5 (Cutie+ (base))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Recall)· 2020-03-10
    60.5
    best: 91.4 (ISVOS (MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· 2020-03-10
    63.6
    best: 94.7 (SwinB-DeAOT-L)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    F-measure (Recall)· 2020-03-10
    67.7
    best: 97.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    J&F· 2020-03-10
    64.65
    best: 93.4 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· 2020-03-10
    65.7
    best: 92.5 (ISVOS (BL30K, MS))
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    Jaccard (Recall)· 2020-03-10
    77.7
    best: 98.1 (STCN)
    Learning Video Object Segmentation from Unlabeled VideosarXiv:2003.05020