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Models/ClawCraneNet

ClawCraneNet

Reported on 28 benchmarks across 2 tasks · 1 paper · 28 SOTA

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

Computer Vision28 results

  • Instance SegmentationonA2D Sentences
    IoU mean· 2021-03-19
    0.655
    best: 0.725 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    IoU overall· 2021-03-19
    0.644
    best: 0.807 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    Precision@0.5· 2021-03-19
    0.704
    best: 0.851 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    Precision@0.6· 2021-03-19
    0.677
    best: 0.827 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    Precision@0.7· 2021-03-19
    0.617
    best: 0.767 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    Precision@0.8· 2021-03-19
    0.489
    best: 0.617 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonA2D Sentences
    Precision@0.9· 2021-03-19
    0.171
    best: 0.259 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    IoU mean· 2021-03-19
    0.655
    best: 0.725 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    IoU overall· 2021-03-19
    0.644
    best: 0.737 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    Precision@0.5· 2021-03-19
    0.88
    best: 0.972 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    Precision@0.6· 2021-03-19
    0.796
    best: 0.917 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    Precision@0.7· 2021-03-19
    0.566
    best: 0.714 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    Precision@0.8· 2021-03-19
    0.147
    best: 0.225 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Instance SegmentationonJ-HMDB
    Precision@0.9· 2021-03-19
    0.002
    best: 0.4 (HINet)
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    IoU mean· 2021-03-19
    0.655
    best: 0.725 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    IoU overall· 2021-03-19
    0.644
    best: 0.807 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    Precision@0.5· 2021-03-19
    0.704
    best: 0.851 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    Precision@0.6· 2021-03-19
    0.677
    best: 0.827 (SOC (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    Precision@0.7· 2021-03-19
    0.617
    best: 0.767 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    Precision@0.8· 2021-03-19
    0.489
    best: 0.617 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonA2D Sentences
    Precision@0.9· 2021-03-19
    0.171
    best: 0.259 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    IoU mean· 2021-03-19
    0.655
    best: 0.725 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    IoU overall· 2021-03-19
    0.644
    best: 0.737 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    Precision@0.5· 2021-03-19
    0.88
    best: 0.972 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    Precision@0.6· 2021-03-19
    0.796
    best: 0.917 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    Precision@0.7· 2021-03-19
    0.566
    best: 0.714 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    Precision@0.8· 2021-03-19
    0.147
    best: 0.225 (SgMg (Video-Swin-B))
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702
  • Referring Expression SegmentationonJ-HMDB
    Precision@0.9· 2021-03-19
    0.002
    best: 0.4 (HINet)
    SOTA
    ClawCraneNet: Leveraging Object-level Relation for Text-based Video SegmentationarXiv:2103.10702