Improve model card: add pipeline tag, library name, paper link, GitHub link, and usage example

README.md

@@ -1,3 +1,64 @@
----
-license: mit
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+---
+license: mit
+pipeline_tag: image-to-image
+library_name: diffusers
+---
+
+# DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models
+
+This model is presented in the paper [DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models](https://huggingface.co/papers/2506.11764).
+
+DiffFuSR is a modular pipeline designed for super-resolving all 12 spectral bands of Sentinel-2 Level-2A imagery to a unified ground sampling distance (GSD) of 2.5 meters. The pipeline operates in two stages:
+1.  A diffusion-based super-resolution (SR) model trained on high-resolution RGB imagery from the NAIP and WorldStrat datasets, harmonized to simulate Sentinel-2 characteristics.
+2.  A learned fusion network that upscales the remaining multispectral bands by utilizing the super-resolved RGB image as a spatial prior.
+
+This approach introduces a robust degradation model and contrastive degradation encoder to support blind SR, outperforming current SOTA baselines in reflectance fidelity, spectral consistency, spatial alignment, and hallucination suppression.
+
+The official implementation, including code and training/evaluation scripts, can be found on GitHub: [https://github.com/NorskRegnesentral/DiffFuSR](https://github.com/NorskRegnesentral/DiffFuSR).
+
+## Sample Usage
+
+To use the DiffFuSR models, you can follow the instructions provided in the official GitHub repository.
+
+First, set up your Python environment and install dependencies:
+
+```bash
+# Create a virtual environment (optional but recommended) Python version used 3.11.4
+python -m venv .venv
+source .venv/bin/activate          # Windows: venv\Scripts\activate
+
+# Install all Python dependencies
+pip install -r requirements.txt
+```
+
+Then, download the pretrained checkpoints from the Hugging Face Hub using `git lfs`:
+
+```bash
+git lfs install
+git clone https://huggingface.co/NorskRegnesentralSTI/DiffFuSR && mv DiffFuSR/logs logs
+```
+
+After downloading, you can run one of the provided test scripts. For example, to test RGB SR for OpenSR metric using the WorldStrat SR model:
+
+```bash
+python 2_test_rgb_for_opensr_metric.py --checkpoint logs/blindsrsnf_aniso_worldstrat_degraded_harmfac_10000_large/version_7/checkpoints/last.ckpt
+```
+You can change the `--checkpoint` flag to test other available models (NAIP-no-harm SR or NAIP-harm SR).
+
+More detailed usage and training instructions are available in the [GitHub repository](https://github.com/NorskRegnesentral/DiffFuSR).
+
+## Citation
+
+If you use this pipeline in your research, please cite our paper:
+
+```bibtex
+@article{,
+      title={DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models},
+      author={{}},
+      year={2025},
+      eprint={2506.11764},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2506.11764},
+}
+```