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Models/Panoptic FPN (ResNet-101)

Panoptic FPN (ResNet-101)

Reported on 18 benchmarks across 3 tasks · 2 papers

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

Medical6 results

Semantic SegmentationonLaRS
PQ· 2023-08-18
38.7
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618
Semantic SegmentationonCityscapes val
AP· 2019-01-08
33
best: 50.6 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Semantic SegmentationonCityscapes val
PQ· 2019-01-08
58.1
best: 70.8 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Semantic SegmentationonCityscapes val
PQst· 2019-01-08
62.5
best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Semantic SegmentationonCityscapes val
PQth· 2019-01-08
52
best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Semantic SegmentationonCityscapes val
mIoU· 2019-01-08
75.7
best: 90.3 (EfficientPS (Cityscapes-fine))
Panoptic Feature Pyramid Networks arXiv:1901.02446

Audio6 results

10-shot image generationonLaRS
PQ· 2023-08-18
38.7
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618
10-shot image generationonCityscapes val
AP· 2019-01-08
33
best: 50.6 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
10-shot image generationonCityscapes val
PQ· 2019-01-08
58.1
best: 70.8 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
10-shot image generationonCityscapes val
PQst· 2019-01-08
62.5
best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
10-shot image generationonCityscapes val
PQth· 2019-01-08
52
best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
10-shot image generationonCityscapes val
mIoU· 2019-01-08
75.7
best: 90.3 (EfficientPS (Cityscapes-fine))
Panoptic Feature Pyramid Networks arXiv:1901.02446

Computer Vision6 results

Panoptic SegmentationonLaRS
PQ· 2023-08-18
38.7
best: 41.7 (Mask2Former (Swin-B))
LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmark arXiv:2308.09618
Panoptic SegmentationonCityscapes val
AP· 2019-01-08
33
best: 50.6 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Panoptic SegmentationonCityscapes val
PQ· 2019-01-08
58.1
best: 70.8 (ViT-P (OneFormer, InternImage-H))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Panoptic SegmentationonCityscapes val
PQst· 2019-01-08
62.5
best: 74.1 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Panoptic SegmentationonCityscapes val
PQth· 2019-01-08
52
best: 64.6 (OneFormer (ConvNeXt-L, single-scale, 512x1024, Mapillary Vistas-pretrained))
Panoptic Feature Pyramid Networks arXiv:1901.02446
Panoptic SegmentationonCityscapes val
mIoU· 2019-01-08
75.7
best: 90.3 (EfficientPS (Cityscapes-fine))
Panoptic Feature Pyramid Networks arXiv:1901.02446