TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/Panoptic FCN* (Swin-L, Cityscapes-fine)

Panoptic FCN* (Swin-L, Cityscapes-fine)

Reported on 6 benchmarks across 3 tasks · 1 paper · 3 SOTA

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

Medical2 results

  • Semantic SegmentationonCityscapes val
    PQst· 2020-12-01
    70.6
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720
  • Semantic SegmentationonCityscapes val
    PQth· 2020-12-01
    59.5
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720

Audio2 results

  • 10-shot image generationonCityscapes val
    PQst· 2020-12-01
    70.6
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720
  • 10-shot image generationonCityscapes val
    PQth· 2020-12-01
    59.5
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720

Computer Vision2 results

  • Panoptic SegmentationonCityscapes val
    PQst· 2020-12-01
    70.6
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720
  • Panoptic SegmentationonCityscapes val
    PQth· 2020-12-01
    59.5
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Fully Convolutional Networks for Panoptic SegmentationarXiv:2012.00720