geochat

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.

• Developed by MBZUAI

Model Sources

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

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