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🐙GitHub
Information or evaluatation on this dataset can be found in this repo: https://github.com/AI9Stars/XLRS-Bench
📜Dataset License
Annotations of this dataset is released under a Creative Commons Attribution-NonCommercial 4.0 International License. For images from:
DOTA
RGB images from Google Earth and CycloMedia (for academic use only; commercial use is prohibited, and Google Earth terms of use apply).ITCVD
Licensed under CC-BY-NC-SA-4.0.MiniFrance, HRSCD
Released under IGN’s "licence ouverte".Toronto, Potsdam:
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:- The data must not be used for other than research purposes. Any other use is prohibited.
- 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.
- The data must not be distributed to third parties. Any person interested in the data may obtain them via ISPRS WG III/4.
- The data users should include the following acknowledgement in any publication resulting from the datasets: “*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.*”
Disclaimer:
If any party believes their rights are infringed, please contact us immediately at [email protected]. We will promptly remove any infringing content.
📖Citation
If you find our work helpful, please consider citing:
@article{wang2025xlrsbench,
title={XLRS-Bench: Could Your Multimodal LLMs Understand Extremely Large Ultra-High-Resolution Remote Sensing Imagery?},
author={Wang, Fengxiang and Wang, Hongzhen and Chen, Mingshuo and Wang, Di and Wang, Yulin and Guo, Zonghao and Ma, Qiang and Lan, Long and Yang, Wenjing and Zhang, Jing and others},
journal={arXiv preprint arXiv:2503.23771},
year={2025}
}
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