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Models/MRCNN + PSPNet (ResNet-101)

MRCNN + PSPNet (ResNet-101)

Reported on 12 benchmarks across 3 tasks · 1 paper · 9 SOTA

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

Medical4 results

  • Semantic SegmentationonCityscapes val
    AP· uses extra data· 2018-01-03
    36.4
    best: 50.6 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Semantic SegmentationonCityscapes val
    PQ· uses extra data· 2018-01-03
    61.2
    best: 70.8 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Semantic SegmentationonCityscapes val
    PQst· uses extra data· 2018-01-03
    66.4
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Semantic SegmentationonCityscapes val
    PQth· uses extra data· 2018-01-03
    54
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Panoptic SegmentationarXiv:1801.00868

Audio4 results

  • 10-shot image generationonCityscapes val
    AP· uses extra data· 2018-01-03
    36.4
    best: 50.6 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • 10-shot image generationonCityscapes val
    PQ· uses extra data· 2018-01-03
    61.2
    best: 70.8 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • 10-shot image generationonCityscapes val
    PQst· uses extra data· 2018-01-03
    66.4
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • 10-shot image generationonCityscapes val
    PQth· uses extra data· 2018-01-03
    54
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Panoptic SegmentationarXiv:1801.00868

Computer Vision4 results

  • Panoptic SegmentationonCityscapes val
    AP· uses extra data· 2018-01-03
    36.4
    best: 50.6 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Panoptic SegmentationonCityscapes val
    PQ· uses extra data· 2018-01-03
    61.2
    best: 70.8 (ViT-P (OneFormer, InternImage-H))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Panoptic SegmentationonCityscapes val
    PQst· uses extra data· 2018-01-03
    66.4
    best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    SOTA
    Panoptic SegmentationarXiv:1801.00868
  • Panoptic SegmentationonCityscapes val
    PQth· uses extra data· 2018-01-03
    54
    best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
    Panoptic SegmentationarXiv:1801.00868