Update README.md

README.md

@@ -4,29 +4,40 @@ datasets:
 - DarthReca/crisislandmark
 language:
 - en
-library_name: torchgeo
+library_name: transformers
 tags:
-- climate
+- remote-sensing
+- text-to-image-retrieval
+- multimodal
+- geospatial
+- SAR
+- multispectral
+- crisis-management
+- earth-observation
+- contrastive-learning
+base_model:
+- sentence-transformers/all-MiniLM-L6-v2
+- torchgeo/resnet50_sentinel2_all_moco
+- torchgeo/resnet50_sentinel1_all_moco
 ---
 # CLOSP-RN
 
-<!-- Provide a quick summary of what the model is/does. -->
+CLOSP (Contrastive Language Optical SAR Pretraining) is a multimodal architecture designed for text-to-image retrieval. 
+It creates a unified embedding space for text, Sentinel-2 (MSI), and Sentinel-1 (SAR) data. 
+The CLOSP-RN variant uses a ResNet-50 vision backbone.
 
 ## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
+The model uses three separate encoders: one for text, one for Sentinel-1 (SAR) data, and one for Sentinel-2 (MSI) data. 
+During training, it uses a contrastive objective to align the textual embeddings with the corresponding visual embeddings (either SAR or MSI).
 
 
 - **Developed by:** Daniele Rege Cambrin
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-- **Repository:** [More Information Needed]
-- **Paper:** [More Information Needed]
+- **Model type:** CLOSP
+- **Language(s) (NLP):** english
+- **License:** OpenRAIL
+- **Finetuned from model:** [More Information Needed]
+- **Repository:** [GitHub](https://github.com/DarthReca/closp)
+- **Paper:** [ArXiv](https://arxiv.org/abs/2507.10403)
 
 ## How to Get Started with the Model
 
@@ -34,7 +45,16 @@ Use the code below to get started with the model.
 
 [More Information Needed]
 
-## Training Details
-
-
 ## Citation
+
+```bibtex
+@misc{cambrin2025texttoremotesensingimageretrievalrgbsources,
+      title={Text-to-Remote-Sensing-Image Retrieval beyond RGB Sources}, 
+      author={Daniele Rege Cambrin and Lorenzo Vaiani and Giuseppe Gallipoli and Luca Cagliero and Paolo Garza},
+      year={2025},
+      eprint={2507.10403},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2507.10403}, 
+}
+```