H²RSVLM：Towards Helpful and Honest Remote Sensing Large Vision Language Model

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News

• 2024.3.28 Paper available on ArXiv.

TODO

• Release inference code and checkpoints of H²RSVLM.
• Release all data in this work.
• Release the training code of H²RSVLM.

Citation

@misc{pang2024h2rsvlm,
        title={H2RSVLM: Towards Helpful and Honest Remote Sensing Large Vision Language Model}, 
        author={Chao Pang and Jiang Wu and Jiayu Li and Yi Liu and Jiaxing Sun and Weijia Li and Xingxing Weng and Shuai Wang and Litong Feng and Gui-Song Xia and Conghui He},
        year={2024},
        eprint={2403.20213},
        archivePrefix={arXiv},
        primaryClass={cs.CV}

Acknowledgement

We gratefully acknowledge these wonderful works：

• Vicuna
• LLaVA
• ShareGPT4V
• LLaMA

License

Usage and License Notices: The data and checkpoint is intended and licensed for research use only. They are also restricted to uses that follow the license agreement of LLaMA, Vicuna and Gemini. The dataset is CC BY NC 4.0 (allowing only non-commercial use) and models trained using the dataset should not be used outside of research purposes.