RSP-Swin-T-UperNet

Reported on 4 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.

Medical2 results

Semantic SegmentationoniSAID
mIoU· 2022-04-06
64.1
best: 70.3 (SegNeXt-L)
An Empirical Study of Remote Sensing Pretraining arXiv:2204.02825
Semantic SegmentationonISPRS Potsdam
Overall Accuracy· uses extra data· 2022-04-06
90.78
best: 93.9 (AerialFormer-B)
An Empirical Study of Remote Sensing Pretraining arXiv:2204.02825

Audio2 results

10-shot image generationoniSAID
mIoU· 2022-04-06
64.1
best: 70.3 (SegNeXt-L)
An Empirical Study of Remote Sensing Pretraining arXiv:2204.02825
10-shot image generationonISPRS Potsdam
Overall Accuracy· uses extra data· 2022-04-06
90.78
best: 93.9 (AerialFormer-B)
An Empirical Study of Remote Sensing Pretraining arXiv:2204.02825