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- ---
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- license: cc-by-nc-sa-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ language:
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+ - zh
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+ tags:
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+ - Remote Sensing
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+ size_categories:
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+ - n<1K
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+ ---
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+ # 🐙GitHub
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+ Information or evaluatation on this dataset can be found in this repo: **https://github.com/AI9Stars/XLRS-Bench**
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+
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+ # 📜Dataset License
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+
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+ Annotations of this dataset is released under a [Creative Commons Attribution-NonCommercial 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0). For images from:
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+
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+ - **[DOTA](https://captain-whu.github.io/DOTA)**
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+ RGB images from Google Earth and CycloMedia (for academic use only; commercial use is prohibited, and Google Earth terms of use apply).
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+
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+ - **[ITCVD](https://phys-techsciences.datastations.nl/dataset.xhtml?persistentId=doi:10.17026/dans-xnc-h2fu)**
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+ Licensed under [CC-BY-NC-SA-4.0](http://creativecommons.org/licenses/by-nc-sa/4.0).
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+
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+ - **[MiniFrance](https://ieee-dataport.org/open-access/minifrance), [HRSCD](https://ieee-dataport.org/open-access/hrscd-high-resolution-semantic-change-detection-dataset)**
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+ Released under [IGN’s "licence ouverte"](https://web.archive.org/web/20200717042533/http://www.ign.fr/institut/activites/lign-lopen-data).
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+
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+ - **[Toronto, Potsdam](https://www.isprs.org/education/benchmarks/UrbanSemLab/default.aspx):**
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+ The Toronto test data images are derived from the Downtown Toronto dataset provided by Optech Inc., First Base Solutions Inc., GeoICT Lab at York University, and ISPRS WG III/4, and are subject to the following conditions:
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+ 1. The data must not be used for other than research purposes. Any other use is prohibited.
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+ 2. The data must not be used outside the context of this test project, in particular while the project is still on-going (i.e. until September 2012). Whether the data will be available for other research purposes after the end of this project is still under discussion.
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+ 3. The data must not be distributed to third parties. Any person interested in the data may obtain them via ISPRS WG III/4.
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+ 4. The data users should include the following acknowledgement in any publication resulting from the datasets:
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+ “*The authors would like to acknowledge the provision of the Downtown Toronto data set by Optech Inc., First Base Solutions Inc., GeoICT Lab at York University, and ISPRS WG III/4.*”
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+
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+ **Disclaimer:**
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+ If any party believes their rights are infringed, please contact us immediately at **[wfx23@nudt.edu.cn](mailto:wfx23@nudt.edu.cn)**. We will promptly remove any infringing content.
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+
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+
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+ # 📖Citation
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+
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+ If you find our work helpful, please consider citing:
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+
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+ ```tex
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+ @inproceedings{wang2025xlrs,
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+ title={Xlrs-bench: Could your multimodal llms understand extremely large ultra-high-resolution remote sensing imagery?},
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+ author={Wang, Fengxiang and Wang, Hongzhen and Guo, Zonghao and Wang, Di and Wang, Yulin and Chen, Mingshuo and Ma, Qiang and Lan, Long and Yang, Wenjing and Zhang, Jing and others},
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+ booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference},
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+ pages={14325--14336},
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+ year={2025}
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+ }
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+
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+ @article{wang2025geollava,
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+ title={GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution},
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+ author={Wang, Fengxiang and Chen, Mingshuo and Li, Yueying and Wang, Di and Wang, Haotian and Guo, Zonghao and Wang, Zefan and Shan, Boqi and Lan, Long and Wang, Yulin and others},
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+ journal={arXiv preprint arXiv:2505.21375},
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+ year={2025}
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+ }
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+ ```