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Models/ViT-B + RVSA-UperNet

ViT-B + RVSA-UperNet

Reported on 6 benchmarks across 2 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 SegmentationonLoveDA
Category mIoU· 2022-08-08
51.95
best: 56.16 (U-Net (MaxViT-S))
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987
Semantic SegmentationoniSAID
mIoU· 2022-08-08
63.85
best: 70.3 (SegNeXt-L)
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987
Semantic SegmentationonISPRS Potsdam
Overall Accuracy· uses extra data· 2022-08-08
90.77
best: 93.9 (AerialFormer-B)
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987

Audio3 results

10-shot image generationonLoveDA
Category mIoU· 2022-08-08
51.95
best: 56.16 (U-Net (MaxViT-S))
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987
10-shot image generationoniSAID
mIoU· 2022-08-08
63.85
best: 70.3 (SegNeXt-L)
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987
10-shot image generationonISPRS Potsdam
Overall Accuracy· uses extra data· 2022-08-08
90.77
best: 93.9 (AerialFormer-B)
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model arXiv:2208.03987