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Models/OneFormer (ConvNeXt-XL, single-scale)

OneFormer (ConvNeXt-XL, single-scale)

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 SegmentationonCityscapes val
AP· 2022-11-10
46.7
best: 50.6 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
Semantic SegmentationonCityscapes val
PQ· 2022-11-10
68.4
best: 70.8 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
Semantic SegmentationonCityscapes val
mIoU· 2022-11-10
83.6
best: 90.3 (EfficientPS (Cityscapes-fine))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220

Audio3 results

10-shot image generationonCityscapes val
AP· 2022-11-10
46.7
best: 50.6 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
10-shot image generationonCityscapes val
PQ· 2022-11-10
68.4
best: 70.8 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
10-shot image generationonCityscapes val
mIoU· 2022-11-10
83.6
best: 90.3 (EfficientPS (Cityscapes-fine))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220

Computer Vision3 results

Panoptic SegmentationonCityscapes val
AP· 2022-11-10
46.7
best: 50.6 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
Panoptic SegmentationonCityscapes val
PQ· 2022-11-10
68.4
best: 70.8 (ViT-P (OneFormer, InternImage-H))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220
Panoptic SegmentationonCityscapes val
mIoU· 2022-11-10
83.6
best: 90.3 (EfficientPS (Cityscapes-fine))
OneFormer: One Transformer to Rule Universal Image Segmentation arXiv:2211.06220