Segmentation on m-NeonTree
59.22Mean mIoUPrithvi-EO-2.0-600M
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Prithvi-EO-2.0-600MModel=Prithvi-EO-2.0-600M, Parameters=600M2024.12 | 59.22 | 0.78 | 60.47 | 58.33 | |
| DOFA-ViT-300MModel=DOFA-ViT-300M, Backbone=ViT-300M2024.12 | 58.67 | 1.21 | 61.03 | 56.84 | |
| Prithvi-EO-2.0-600M-TLModel=Prithvi-EO-2.0-600M-TL, Parameters=600M, Config=TL2024.12 | 58.07 | 0.49 | 59 | 57.53 | |
| Prithvi-EO-2.0-300MModel=Prithvi-EO-2.0-300M, Parameters=300M2024.12 | 57.63 | 0.55 | 58.14 | 56.43 | |
| DeCUR-Resnet50Model=DeCUR-Resnet50, Backbone=ResNet-502024.12 | 57.47 | 0.55 | 58.47 | 56.41 | |
| Satlas-Swin-100MModel=Satlas-Swin-100M, Backbone=Swin, Parameters=100M2024.12 | 57 | 0.42 | 57.64 | 56.36 | |
| Prithvi-EO-2.0-300M-TLModel=Prithvi-EO-2.0-300M-TL, Parameters=300M, Config=TL2024.12 | 56.95 | 0.61 | 58.13 | 55.89 | |
| Prithvi-EO-2.0-100M-TLModel=Prithvi-EO-2.0-100M-TL, Parameters=100M, Config=TL2024.12 | 56.61 | 0.45 | 57.24 | 55.81 | |
| Prithvi-EO-2.0-100MModel=Prithvi-EO-2.0-100M, Parameters=100M2024.12 | 56.57 | 0.49 | 57.44 | 56.02 | |
| MOCO-Resnet50Model=MOCO-Resnet50, Backbone=ResNet-502024.12 | 56.08 | 0.31 | 56.51 | 55.63 | |
| Prithvi-EO-1.0-100MModel=Prithvi-EO-1.0-100M, Parameters=100M2024.12 | 55.66 | 0.51 | 56.32 | 54.55 | |
| ScaleMAE-ViT-300MModel=ScaleMAE-ViT-300M, Backbone=ViT-300M2024.12 | 54.85 | 1.36 | 55.89 | 51.38 | |
| DINO-Resnet50Model=DINO-Resnet50, Backbone=ResNet-502024.12 | 51.81 | 6.42 | 55.71 | 35.6 |