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Models/XMem (MS)

XMem (MS)

Reported on 57 benchmarks across 3 tasks · 1 paper

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

Computer Vision57 results

  • VideoonDAVIS 2017 (val)
    F-measure (Mean)· uses extra data· 2022-07-14
    91
    best: 93.4 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2017 (val)
    J&F· uses extra data· 2022-07-14
    88.2
    best: 90.7 (SAM2)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2017 (val)
    Jaccard (Mean)· uses extra data· 2022-07-14
    85.4
    best: 87.5 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2016
    F-measure (Mean)· uses extra data· 2022-07-14
    93.5
    best: 94.7 (SwinB-DeAOT-L)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2016
    J&F· uses extra data· 2022-07-14
    92.7
    best: 93.4 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2016
    Jaccard (Mean)· uses extra data· 2022-07-14
    92
    best: 92.5 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2019
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.2
    best: 90.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2019
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.8
    best: 90.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2019
    Jaccard (Seen)· uses extra data· 2022-07-14
    84.9
    best: 86.3 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2019
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.8
    best: 754.8 (R50-AOST (L'=1))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2019
    Overall· uses extra data· 2022-07-14
    86.4
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2017 (test-dev)
    F-measure (Mean)· uses extra data· 2022-07-14
    86.4
    best: 91.4 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2017 (test-dev)
    J&F· uses extra data· 2022-07-14
    83.1
    best: 88.1 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonDAVIS 2017 (test-dev)
    Jaccard (Mean)· uses extra data· 2022-07-14
    79.7
    best: 84.7 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2018
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.9
    best: 91 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2018
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.9
    best: 90.2 (XMem (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2018
    Jaccard (Seen)· uses extra data· 2022-07-14
    85.3
    best: 86.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2018
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.7
    best: 82.2 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • VideoonYouTube-VOS 2018
    Overall· uses extra data· 2022-07-14
    86.7
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Mean)· uses extra data· 2022-07-14
    91
    best: 93.4 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (val)
    J&F· uses extra data· 2022-07-14
    88.2
    best: 90.7 (SAM2)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Mean)· uses extra data· 2022-07-14
    85.4
    best: 87.5 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· uses extra data· 2022-07-14
    93.5
    best: 94.7 (SwinB-DeAOT-L)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2016
    J&F· uses extra data· 2022-07-14
    92.7
    best: 93.4 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· uses extra data· 2022-07-14
    92
    best: 92.5 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2019
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.2
    best: 90.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2019
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.8
    best: 90.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2019
    Jaccard (Seen)· uses extra data· 2022-07-14
    84.9
    best: 86.3 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2019
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.8
    best: 754.8 (R50-AOST (L'=1))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2019
    Overall· uses extra data· 2022-07-14
    86.4
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    F-measure (Mean)· uses extra data· 2022-07-14
    86.4
    best: 91.4 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    J&F· uses extra data· 2022-07-14
    83.1
    best: 88.1 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonDAVIS 2017 (test-dev)
    Jaccard (Mean)· uses extra data· 2022-07-14
    79.7
    best: 84.7 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2018
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.9
    best: 91 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2018
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.9
    best: 90.2 (XMem (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2018
    Jaccard (Seen)· uses extra data· 2022-07-14
    85.3
    best: 86.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2018
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.7
    best: 82.2 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Video Object SegmentationonYouTube-VOS 2018
    Overall· uses extra data· 2022-07-14
    86.7
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    F-measure (Mean)· uses extra data· 2022-07-14
    91
    best: 93.4 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    J&F· uses extra data· 2022-07-14
    88.2
    best: 90.7 (SAM2)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (val)
    Jaccard (Mean)· uses extra data· 2022-07-14
    85.4
    best: 87.5 (Cutie+ (base))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· uses extra data· 2022-07-14
    93.5
    best: 94.7 (SwinB-DeAOT-L)
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    J&F· uses extra data· 2022-07-14
    92.7
    best: 93.4 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· uses extra data· 2022-07-14
    92
    best: 92.5 (ISVOS (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2019
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.2
    best: 90.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2019
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.8
    best: 90.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2019
    Jaccard (Seen)· uses extra data· 2022-07-14
    84.9
    best: 86.3 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2019
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.8
    best: 754.8 (R50-AOST (L'=1))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2019
    Overall· uses extra data· 2022-07-14
    86.4
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (test-dev)
    F-measure (Mean)· uses extra data· 2022-07-14
    86.4
    best: 91.4 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (test-dev)
    J&F· uses extra data· 2022-07-14
    83.1
    best: 88.1 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonDAVIS 2017 (test-dev)
    Jaccard (Mean)· uses extra data· 2022-07-14
    79.7
    best: 84.7 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2018
    F-Measure (Seen)· uses extra data· 2022-07-14
    89.9
    best: 91 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2018
    F-Measure (Unseen)· uses extra data· 2022-07-14
    89.9
    best: 90.2 (XMem (BL30K, MS))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2018
    Jaccard (Seen)· uses extra data· 2022-07-14
    85.3
    best: 86.6 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2018
    Jaccard (Unseen)· uses extra data· 2022-07-14
    81.7
    best: 82.2 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115
  • Semi-Supervised Video Object SegmentationonYouTube-VOS 2018
    Overall· uses extra data· 2022-07-14
    86.7
    best: 87.5 (Cutie+ (base, MEGA))
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory ModelarXiv:2207.07115