Style Alignment based Dynamic Observation Method for UAV-View Geo-localization
<|reference_start|>Style Alignment based Dynamic Observation Method for UAV-View Geo-localization: The task of UAV-view geo-localization is to estimate the localization of a query satellite/drone image by matching it against a reference dataset consisting of drone/satellite images. Though tremendous strides have been made in feature alignment between satellite and drone views, vast differences in both inter and intra-class due to changes in viewpoint, altitude, and lighting remain a huge challenge. In this paper, a style alignment based dynamic observation method for UAV-view geo-localization is proposed to meet the above challenges from two perspectives: visual style transformation and surrounding noise control. Specifically, we introduce a style alignment strategy to transfrom the diverse visual style of drone-view images into a unified satellite images visual style. Then a dynamic observation module is designed to evaluate the spatial distribution of images by mimicking human observation habits. It is featured by the hierarchical attention block (HAB) with a dual-square-ring stream structure, to reduce surrounding noise and geographical deformation. In addition, we propose a deconstruction loss to push away features of different geo-tags and squeeze knowledge from unmatched images by correlation calculation. The experimental results demonstrate the state-of-the-art performance of our model on benchmarked datasets. In particular, when compared to the prior art on University-1652, our results surpass the best of them (FSRA), while only requiring 2x fewer parameters. Code will be released at https://github.com/Xcco1/SA\_DOM<|reference_end|>
@article{shao2024style,
    title={Style Alignment based Dynamic Observation Method for UAV-View
  Geo-localization},
    author={Jie Shao and LingHao Jiang},
    journal={arXiv preprint arXiv:2407.02832},
    year={2024},
    doi={10.1109/TGRS.2023.3337383},
    archivePrefix={arXiv},
    eprint={2407.02832},
    primaryClass={cs.CV}
}