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---
license: apache-2.0
---

# GeoChat-7B

GeoChat is the first grounded Large Vision Language Model, specifically tailored to Remote Sensing(RS) scenarios. Unlike general-domain models, GeoChat excels in handling high-resolution RS imagery, employing region-level reasoning for comprehensive scene interpretation. Leveraging a newly created RS multimodal dataset, GeoChat is fine-tuned using the LLaVA-1.5 architecture. This results in robust zero-shot performance across various RS tasks, including image and region captioning, visual question answering, scene classification, visually grounded conversations, and referring object detection.

<!-- Provide a longer summary of what this model is. -->
- **Developed by MBZUAI**

### Model Sources

<!-- Provide the basic links for the model. -->

- **Repository:** https://github.com/mbzuai-oryx/GeoChat
- **Paper:** https://arxiv.org/abs/2311.15826

**BibTeX:**

```bibtex
@misc{kuckreja2023geochat,
      title={GeoChat: Grounded Large Vision-Language Model for Remote Sensing}, 
      author={Kartik Kuckreja and Muhammad Sohail Danish and Muzammal Naseer and Abhijit Das and Salman Khan and Fahad Shahbaz Khan},
      year={2023},
      eprint={2311.15826},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}  
```
## Authors
Kartik Kuckreja, Muhammad Sohail

## Contact
kartik.kuckreja@mbzuai.ac.ae