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| | license: apache-2.0 |
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| | |
| | # GeoChat-7B |
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| | 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. |
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| | <!-- Provide a longer summary of what this model is. --> |
| | - **Developed by MBZUAI** |
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| | ### Model Sources |
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| | <!-- Provide the basic links for the model. --> |
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| | - **Repository:** https://github.com/mbzuai-oryx/GeoChat |
| | - **Paper:** https://arxiv.org/abs/2311.15826 |
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| | **BibTeX:** |
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| | ```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 |
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| | ## Contact |
| | kartik.kuckreja@mbzuai.ac.ae |
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