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Models/MS-PCNN

MS-PCNN

Reported on 6 benchmarks across 3 tasks · 1 paper

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

Medical2 results

  • Semantic SegmentationonToronto-3D
    OA· 2020-03-18
    91.53
    best: 95.5 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284
  • Semantic SegmentationonToronto-3D
    mIoU· 2020-03-18
    58.01
    best: 73.6 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284

Computer Vision2 results

  • 3D Semantic SegmentationonToronto-3D
    OA· 2020-03-18
    91.53
    best: 95.5 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284
  • 3D Semantic SegmentationonToronto-3D
    mIoU· 2020-03-18
    58.01
    best: 73.6 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284

Audio2 results

  • 10-shot image generationonToronto-3D
    OA· 2020-03-18
    91.53
    best: 95.5 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284
  • 10-shot image generationonToronto-3D
    mIoU· 2020-03-18
    58.01
    best: 73.6 (SCF-Net)
    Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban RoadwaysarXiv:2003.08284