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Models/MaskCLIP

MaskCLIP

Reported on 32 benchmarks across 6 tasks · 2 papers · 29 SOTA

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

Computer Vision14 results

  • Open Vocabulary Semantic SegmentationonADE20K-847
    mIoU· 2022-08-18
    8.2
    best: 17.3 (UMG-CLIP-E/14)
    SOTA
    Open-Vocabulary Universal Image Segmentation with MaskCLIParXiv:2208.08984
  • Open Vocabulary Semantic SegmentationonADE20K-150
    mIoU· 2022-08-18
    23.7
    best: 38.2 (Mask-Adapter)
    SOTA
    Open-Vocabulary Universal Image Segmentation with MaskCLIParXiv:2208.08984
  • Open Vocabulary Panoptic SegmentationonADE20K
    PQ· 2021-12-02
    15.1
    best: 31.6 (UMG-CLIP-E/14)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Zero Shot SegmentationonADE20K training-free zero-shot segmentation
    mIoU· 2021-12-02
    10.2
    best: 17.7 (COSMOS ViT-B/16)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonCOCO-Stuff-171
    mIoU· 2021-12-02
    16.4
    best: 34 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonCOCO-Object
    mIoU· 2021-12-02
    20.6
    best: 49.4 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonADE20K
    Mean IoU (val)· 2021-12-02
    9.8
    best: 30.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonCityscapes val
    mIoU· 2021-12-02
    10
    best: 51.1 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonCityscapes val
    pixel accuracy· 2021-12-02
    35.9
    best: 83.7 (ReCo+)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonPASCAL Context-59
    mIoU· 2021-12-02
    26.4
    best: 50.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonPascalVOC-20
    mIoU· 2021-12-02
    74.9
    best: 91.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Unsupervised Semantic SegmentationonPASCAL VOC
    mIoU· 2021-12-02
    29.3
    best: 76.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Open Vocabulary Semantic SegmentationonPASCAL Context-459
    mIoU· 2021-12-02
    10
    best: 25.8 (SILC)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Open Vocabulary Semantic SegmentationonPASCAL Context-59
    mIoU· 2022-08-18
    45.9
    best: 64.6 (HyperSeg)
    Open-Vocabulary Universal Image Segmentation with MaskCLIParXiv:2208.08984

Medical9 results

  • Semantic SegmentationonCC3M-TagMask
    mIoU· 2021-12-02
    41
    best: 65.5 (TTD (TCL))
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonCOCO-Stuff-171
    mIoU· 2021-12-02
    16.4
    best: 34 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonCOCO-Object
    mIoU· 2021-12-02
    20.6
    best: 49.4 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonADE20K
    Mean IoU (val)· 2021-12-02
    9.8
    best: 30.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonCityscapes val
    pixel accuracy· 2021-12-02
    35.9
    best: 83.7 (ReCo+)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonPASCAL Context-59
    mIoU· 2021-12-02
    26.4
    best: 50.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonPascalVOC-20
    mIoU· 2021-12-02
    74.9
    best: 91.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonPASCAL VOC
    mIoU· 2021-12-02
    29.3
    best: 76.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • Semantic SegmentationonCityscapes val
    mIoU· 2021-12-02
    10
    best: 90.3 (EfficientPS (Cityscapes-fine))
    Extract Free Dense Labels from CLIParXiv:2112.01071

Audio9 results

  • 10-shot image generationonCC3M-TagMask
    mIoU· 2021-12-02
    41
    best: 65.5 (TTD (TCL))
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonCOCO-Stuff-171
    mIoU· 2021-12-02
    16.4
    best: 34 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonCOCO-Object
    mIoU· 2021-12-02
    20.6
    best: 49.4 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonADE20K
    Mean IoU (val)· 2021-12-02
    9.8
    best: 30.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonCityscapes val
    pixel accuracy· 2021-12-02
    35.9
    best: 83.7 (ReCo+)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonPASCAL Context-59
    mIoU· 2021-12-02
    26.4
    best: 50.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonPascalVOC-20
    mIoU· 2021-12-02
    74.9
    best: 91.8 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonPASCAL VOC
    mIoU· 2021-12-02
    29.3
    best: 76.7 (CorrCLIP)
    SOTA
    Extract Free Dense Labels from CLIParXiv:2112.01071
  • 10-shot image generationonCityscapes val
    mIoU· 2021-12-02
    10
    best: 90.3 (EfficientPS (Cityscapes-fine))
    Extract Free Dense Labels from CLIParXiv:2112.01071