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S$^3$Geo: Structure-Semantic Synergistic Learning for Cross-View Geo-Localization
Cross-view geo-localization (CVGL) aims to estimate geographic locations by matching images captured from different viewpoints, such as drone and satellite views. Existing methods mainly rely on visual representations, but often fail to jointly model fine-grained structural correspondences and seman
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