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Models/Panoptic SegFormer (ResNet-50)

Panoptic SegFormer (ResNet-50)

Reported on 9 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.

Medical3 results

Semantic SegmentationonCOCO test-dev
PQ· 2021-09-08
50.2
best: 59.5 (Mask DINO (single scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
Semantic SegmentationonCOCO test-dev
PQst· 2021-09-08
42.4
best: 58.9 (MaskConver (ResNet50, single-scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
Semantic SegmentationonCOCO test-dev
PQth· 2021-09-08
55.3
best: 65.1 (Mask2Former (Swin-L))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814

Audio3 results

10-shot image generationonCOCO test-dev
PQ· 2021-09-08
50.2
best: 59.5 (Mask DINO (single scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
10-shot image generationonCOCO test-dev
PQst· 2021-09-08
42.4
best: 58.9 (MaskConver (ResNet50, single-scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
10-shot image generationonCOCO test-dev
PQth· 2021-09-08
55.3
best: 65.1 (Mask2Former (Swin-L))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814

Computer Vision3 results

Panoptic SegmentationonCOCO test-dev
PQ· 2021-09-08
50.2
best: 59.5 (Mask DINO (single scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
Panoptic SegmentationonCOCO test-dev
PQst· 2021-09-08
42.4
best: 58.9 (MaskConver (ResNet50, single-scale))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814
Panoptic SegmentationonCOCO test-dev
PQth· 2021-09-08
55.3
best: 65.1 (Mask2Former (Swin-L))
Panoptic SegFormer: Delving Deeper into Panoptic Segmentation with Transformers arXiv:2109.03814