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Models/SFA-Net

SFA-Net

Reported on 12 benchmarks across 2 tasks

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

Medical6 results

  • Semantic SegmentationonFine-Grained Grass Segmentation Dataset
    mIoU
    51.21
    best: 51.96 (D2LS)
  • Semantic SegmentationonLoveDA
    Category mIoU
    54.9
    best: 56.16 (U-Net (MaxViT-S))
  • Semantic SegmentationonFine-Grained Cloud Segmentation Dataset
    mIoU
    74.88
    best: 82.16 (D2LS)
  • Semantic SegmentationonISPRS Vaihingen
    Average F1
    91.2
    best: 93.7 (EfficientUNets and Transformers)
  • Semantic SegmentationonISPRS Potsdam
    Mean F1
    93.5
    best: 94.7 (D2LS)
  • Semantic SegmentationonUAVid
    Mean IoU
    70.4
    best: 73.34 (U-Net Ensemble)

Audio6 results

  • 10-shot image generationonFine-Grained Grass Segmentation Dataset
    mIoU
    51.21
    best: 51.96 (D2LS)
  • 10-shot image generationonLoveDA
    Category mIoU
    54.9
    best: 56.16 (U-Net (MaxViT-S))
  • 10-shot image generationonFine-Grained Cloud Segmentation Dataset
    mIoU
    74.88
    best: 82.16 (D2LS)
  • 10-shot image generationonISPRS Vaihingen
    Average F1
    91.2
    best: 93.7 (EfficientUNets and Transformers)
  • 10-shot image generationonISPRS Potsdam
    Mean F1
    93.5
    best: 94.7 (D2LS)
  • 10-shot image generationonUAVid
    Mean IoU
    70.4
    best: 73.34 (U-Net Ensemble)