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Models/maYOLACT ResNet50

maYOLACT ResNet50

Reported on 12 benchmarks across 1 task · 1 paper · 1 SOTA

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

Computer Vision12 results

  • Instance SegmentationonPASCAL VOC 2012
    Frame (fps)· 2023-08-15
    81.27
    SOTA
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonPASCAL VOC 2012
    FLOPs (G)· 2023-08-15
    48.26
    best: 100.85 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonPASCAL VOC 2012
    Size (M)· 2023-08-15
    30.41
    best: 40.32 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonPASCAL VOC 2012
    avgAP (mask AP + box AP)· 2023-08-15
    37.39
    best: 42.69 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonPASCAL VOC 2012
    boxAP· 2023-08-15
    37.5
    best: 42.96 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonPASCAL VOC 2012
    maskAP· 2023-08-15
    37.27
    best: 42.42 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    FLOPs (G)· 2023-08-15
    0.4826
    best: 100.85 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    Frame (fps)· 2023-08-15
    36.13
    best: 52.22 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    Size (M)· 2023-08-15
    30.38
    best: 40.28 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    avgAP (mask AP + box AP)· 2023-08-15
    46.29
    best: 47.15 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    boxAP· 2023-08-15
    49.59
    best: 51.2 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717
  • Instance SegmentationonMEIS
    maskAP· 2023-08-15
    42.99
    best: 43.09 (RAMEM UPANet80 V2)
    Real-time Automatic M-mode Echocardiography Measurement with Panel Attention from Local-to-Global PixelsarXiv:2308.07717