Image-to-Image
Diffusers
Safetensors
sar-to-eo
remote-sensing
flow-matching
synthetic-aperture-radar
Instructions to use JeonghyeokDo/ReFlowSET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JeonghyeokDo/ReFlowSET with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JeonghyeokDo/ReFlowSET", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
README: link the paper on IEEE Xplore
Browse files
README.md
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SAR-to-EO image translation with a conditional flow-matching transformer trained
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from scratch inside a frozen high-fidelity autoencoder latent space.
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- **Paper:** IEEE Geoscience and Remote Sensing Letters (GRSL), 2026 ([arXiv:2609.00968](https://arxiv.org/abs/2609.00968))
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- **Code:** https://github.com/KAIST-VICLab/ReFlowSET
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- **Project page:** https://kaist-viclab.github.io/ReFlowSET_site/
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- **Comparison-method weights:** [`baselines/`](https://huggingface.co/JeonghyeokDo/ReFlowSET/tree/main/baselines) in this repository — all fifteen prior methods, both datasets
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SAR-to-EO image translation with a conditional flow-matching transformer trained
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from scratch inside a frozen high-fidelity autoencoder latent space.
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- **Paper:** [IEEE Geoscience and Remote Sensing Letters (GRSL), 2026](https://ieeexplore.ieee.org/document/11780259) ([arXiv:2609.00968](https://arxiv.org/abs/2609.00968))
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- **Code:** https://github.com/KAIST-VICLab/ReFlowSET
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- **Project page:** https://kaist-viclab.github.io/ReFlowSET_site/
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- **Comparison-method weights:** [`baselines/`](https://huggingface.co/JeonghyeokDo/ReFlowSET/tree/main/baselines) in this repository — all fifteen prior methods, both datasets
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