UAV Satellite-Thermal Geo-localization Dataset
Captured using Boson thermal cameras, this dataset is specifically designed for research on nighttime UAV satellite-thermal geo-localization and satellite-thermal image translation. It has been utilized in the following works:
Long-range UAV Thermal Geo-localization with Satellite Imagery
This study focuses on long-range geo-localization by leveraging UAV thermal imagery and satellite data through image retrieval techniques.STHN: Deep Homography Estimation for UAV Thermal Geo-localization with Satellite Imagery
The STHN model introduces deep homography estimation to enhance the accuracy of UAV thermal geo-localization using satellite imagery.
Citation
If you use the dataset in your research, please consider citing the following publication:
- For satellite-thermal-dataset-v1:
@INPROCEEDINGS{xiao2023stgl,
author={Xiao, Jiuhong and Tortei, Daniel and Roura, Eloy and Loianno, Giuseppe},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={Long-Range UAV Thermal Geo-Localization with Satellite Imagery},
year={2023},
volume={},
number={},
pages={5820-5827},
doi={10.1109/IROS55552.2023.10342068}}
- For satellite-thermal-dataset-v3:
@ARTICLE{xiao2024sthn,
author={Xiao, Jiuhong and Zhang, Ning and Tortei, Daniel and Loianno, Giuseppe},
journal={IEEE Robotics and Automation Letters},
title={STHN: Deep Homography Estimation for UAV Thermal Geo-Localization With Satellite Imagery},
year={2024},
volume={9},
number={10},
pages={8754-8761},
keywords={Estimation;Location awareness;Satellites;Satellite images;Autonomous aerial vehicles;Accuracy;Iterative methods;Deep learning for visual perception;aerial systems: applications;localization},
doi={10.1109/LRA.2024.3448129}}
Copyright Notice for Bing Satellite Imagery
Please note that our dataset is based on Bing satellite imagery. For detailed copyright information, please refer to the Bing Maps Print Rights page.
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