Remote sensing pretrained models easy loading using huggingface -- PyTorch (for fast benchmarking)
from rshf.satmae import SatMAE
model = SatMAE.from_pretrained("MVRL/satmae-vitlarge-fmow-pretrain-800")
print(model.forward_encoder(torch.randn(1, 3, 224, 224), mask_ratio=0.0)[0].shape)
| Model Type |
Venue |
Citation |
| BioCLIP |
CVPR'24 |
link |
| CLIP |
ICML'21 |
link |
| CROMA |
NeurIPS'23 |
link |
| GeoCLAP |
BMVC'23 |
link |
| GeoCLIP |
NeurIPS'23 |
link |
| Presto |
|
link |
| Prithvi |
|
link |
| RemoteCLIP |
TGRS'23 |
link |
| RVSA |
TGRS'22 |
link |
| SatClip |
|
link |
| SatMAE |
NeurIPS'22 |
link |
| SatMAE++ |
CVPR'24 |
link |
| ScaleMAE |
ICCV'23 |
link |
| SINR |
ICML'23 |
link |
List of models available here: Link