Update README.md

README.md

@@ -6,31 +6,43 @@ license: cc-by-4.0
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+What is DOFA: DOFA is a unified multimodal foundation model for different data modalities in remote sensing and Earth observation.
 
 ## Model Details
+Differences with existing foundation models: DOFA is pre-trained using five different data modalities in remote sensing and Earth observation. It can handle images with any number of input channels.
+
+DOFA is inspired by neuroplasticity Neuroplasticity is an important brain mechanism for adjusting to new experiences or environmental shifts. Inspired by this concept, we design DOFA to emulate this mechanism for processing multimodal EO data.
+
+For more details, please take a look at the paper [Neural Plasticity-Inspired Foundation Model for Observing the Earth Crossing Modalities](https://arxiv.org/abs/2403.15356).
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+**Why develop DOFA**
 
+The learned multimodal representation may not effectively capture such an intersensor relationship.
 
+The performance of foundation models will degrade when downstream tasks require the utilization of data from unseen sensors with varying numbers of spectral bands and spatial resolutions or different wavelength regimes.
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+The development of individual, customized foundation models requires considerably more computing resources and human efforts.
 
-### Model Sources [optional]
+The increasing number of specialized foundation models makes it difficult to select the most appropriate one for a specific downstream task.
+
+DOFA supports input images with any number of channels using our pre-trained foundation models.
+The examples in the Github repo [DOFA](https://github.com/zhu-xlab/DOFA) show how to use DOFA for Sentinel-1 (SAR), Sentinel-2, NAIP RGB. 
+We will add example usage for Gaofen Multispectral, and Hyperspectral data soon.
+
+---
+
+- **Developed by:** Techinical University of Munich, [Chair of Data Science in Earth Observation](https://www.asg.ed.tum.de/en/sipeo/home/)
+- **Funded by:** Ekapex, ML4Earth
+- **Model type:** Multimodal Foundation Model for Remote Sensing and Earth Observation
+- **License:** CC-BY-4.0
 
-<!-- Provide the basic links for the model. -->
+### Model Sources [optional]
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** https://github.com/zhu-xlab/DOFA
+- **Paper [optional]:** https://arxiv.org/abs/2403.15356
+- **Demo [optional]:** https://github.com/ShadowXZT/DOFA-pytorch/blob/master/demo.ipynb
 
 ---
 Table 1: Linear probing results on six classification tasks. All models are trained
@@ -80,4 +92,14 @@ this domain.
 
 ## Uses
 
-Please refer to the Github repo [DOFA](https://github.com/zhu-xlab/DOFA) for more details.
+Please refer to the Github repo [DOFA](https://github.com/zhu-xlab/DOFA) for more details.
+
+
+```
+@article{xiong2024neural,
+  title={Neural Plasticity-Inspired Foundation Model for Observing the {Earth} Crossing Modalities},
+  author={Xiong, Zhitong and Wang, Yi and Zhang, Fahong and Stewart, Adam J and Hanna, Jo{\"e}lle and Borth, Damian and Papoutsis, Ioannis and Saux, Bertrand Le and Camps-Valls, Gustau and Zhu, Xiao Xiang},
+  journal={arXiv preprint arXiv:2403.15356},
+  year={2024}
+}
+```