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Models/R2VOS (Video-Swin-T)

R2VOS (Video-Swin-T)

Reported on 6 benchmarks across 2 tasks · 1 paper · 6 SOTA

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

Computer Vision6 results

  • Instance SegmentationonRefer-YouTube-VOS (2021 public validation)
    F· uses extra data· 2022-07-04
    63.1
    best: 76.1 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203
  • Instance SegmentationonRefer-YouTube-VOS (2021 public validation)
    J· uses extra data· 2022-07-04
    59.6
    best: 71.7 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203
  • Instance SegmentationonRefer-YouTube-VOS (2021 public validation)
    J&F· uses extra data· 2022-07-04
    61.3
    best: 73.9 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203
  • Referring Expression SegmentationonRefer-YouTube-VOS (2021 public validation)
    F· uses extra data· 2022-07-04
    63.1
    best: 76.1 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203
  • Referring Expression SegmentationonRefer-YouTube-VOS (2021 public validation)
    J· uses extra data· 2022-07-04
    59.6
    best: 71.7 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203
  • Referring Expression SegmentationonRefer-YouTube-VOS (2021 public validation)
    J&F· uses extra data· 2022-07-04
    61.3
    best: 73.9 (MPG-SAM 2)
    SOTA
    Towards Robust Referring Video Object Segmentation with Cyclic Relational ConsensusarXiv:2207.01203