Classification on BEN MM
65.38Accuracy (Opt.)CoDe-MAE
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CoDe-MAEBackbone=HiViT-B, Pre-training Dataset=OSPretrain-1M, HR=true, Evaluation Protocol=10-shot linear probing2026.04 | 65.38 | 57.97 | |
| MaRSBackbone=Swin V2-B, Pre-training Dataset=MaRS-16M (32M), HR=true, Evaluation Protocol=10-shot linear probing2026.04 | 60.22 | 36.83 | |
| DOFABackbone=DOFA-B, Pre-training Dataset=DOFA-MM (8M), HR=true, Evaluation Protocol=10-shot linear probing2026.04 | 57.94 | 56.5 | |
| SatViTBackbone=ViT-B, Pre-training Dataset=Sentinel-1/2 (2.6M), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 56.55 | 53.42 | |
| DeCURBackbone=ViT-S, Pre-training Dataset=SSL4EO (502K), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 56.22 | 53.2 | |
| CROMABackbone=ViT-B, Pre-training Dataset=SSL4EO (2M), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 55.9 | 54.83 | |
| FG-MAEBackbone=ViT-B, Pre-training Dataset=SSL4EO (2M), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 53.19 | 52.33 | |
| DINO-MMBackbone=ViT-S, Pre-training Dataset=BEN-MM (620K), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 52.02 | 54.54 | |
| SwinSSLBackbone=Swin-T, Pre-training Dataset=SEN12MS (360K), HR=false, Evaluation Protocol=10-shot linear probing2026.04 | 49.17 | 49.85 |