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Models/SHIFNet

SHIFNet

Reported on 8 benchmarks across 4 tasks · 1 paper · 4 SOTA

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

Medical2 results

  • Semantic SegmentationonPST900
    mIoU· 2025-03-04
    89.8
    SOTA
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581
  • Semantic SegmentationonMFN Dataset
    mIOU· 2025-03-04
    59.2
    best: 62.7 (RoadFormer+ (ConvNeXt-L))
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581

Computer Vision2 results

  • Scene SegmentationonPST900
    mIoU· 2025-03-04
    89.8
    SOTA
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581
  • Scene SegmentationonMFN Dataset
    mIOU· 2025-03-04
    59.2
    best: 62.7 (RoadFormer+ (ConvNeXt-L))
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581

Methodology2 results

  • 2D Object DetectiononPST900
    mIoU· 2025-03-04
    89.8
    SOTA
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581
  • 2D Object DetectiononMFN Dataset
    mIOU· 2025-03-04
    59.2
    best: 62.7 (RoadFormer+ (ConvNeXt-L))
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581

Audio2 results

  • 10-shot image generationonPST900
    mIoU· 2025-03-04
    89.8
    SOTA
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581
  • 10-shot image generationonMFN Dataset
    mIOU· 2025-03-04
    59.2
    best: 62.7 (RoadFormer+ (ConvNeXt-L))
    Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language GuidancearXiv:2503.02581