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Models/PVT-CASCADE

PVT-CASCADE

Reported on 15 benchmarks across 3 tasks

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

Medical13 results

  • Medical Image SegmentationonKvasir-SEG
    mIoU
    0.8776
    best: 0.9065 (EffiSegNet-B5)
  • Medical Image SegmentationonKvasir-SEG
    mean Dice
    0.9258
    best: 0.9502 (DUCK-Net)
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mIoU
    0.7258
    best: 0.9179 (RAPUNet)
  • Medical Image SegmentationonETIS-LARIBPOLYPDB
    mean Dice
    0.8007
    best: 0.9572 (RAPUNet)
  • Medical Image SegmentationonCVC-ColonDB
    mIoU
    0.7453
    best: 0.9096 (RAPUNet)
  • Medical Image SegmentationonCVC-ColonDB
    mean Dice
    0.8254
    best: 0.9526 (RAPUNet)
  • Medical Image SegmentationonMICCAI 2015 Multi-Atlas Abdomen Labeling Challenge
    Avg DSC
    81.06
    best: 84.9 (MERIT)
  • Medical Image SegmentationonMICCAI 2015 Multi-Atlas Abdomen Labeling Challenge
    Avg HD
    20.23
  • Medical Image SegmentationonAutomatic Cardiac Diagnosis Challenge (ACDC)
    Avg DSC
    91.46
    best: 94.26 (FCT)
  • Medical Image SegmentationonCVC-ClinicDB
    mIoU
    0.8998
    best: 0.9343 (DUCK-Net)
  • Medical Image SegmentationonCVC-ClinicDB
    mean Dice
    0.9434
    best: 0.9684 (DUCK-Net)
  • Semantic SegmentationonKvasir-SEG
    mDice
    0.9258
  • Semantic SegmentationonKvasir-SEG
    mIoU
    0.8776
    best: 0.891 (SSFormer-S + PRN)

Audio2 results

  • 10-shot image generationonKvasir-SEG
    mDice
    0.9258
  • 10-shot image generationonKvasir-SEG
    mIoU
    0.8776
    best: 0.891 (SSFormer-S + PRN)