A DINOv2-based framework with feature mixing and hard negative sampling achieves state-of-the-art cross-view geo-localization, supported by a new global dataset, CV-Cities.
Spatial-Aware Feature Aggregation for Cross-View Image based Geo-Localization,
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CV-Cities: Advancing Cross-View Geo-Localization in Global Cities
A DINOv2-based framework with feature mixing and hard negative sampling achieves state-of-the-art cross-view geo-localization, supported by a new global dataset, CV-Cities.