BEV-CV: A Novel Birds-Eye-View Transform for Efficient Cross-View Geo-Localization
BEV-CV introduces a novel multi-branch architecture that reduces the domain gap between ground-level and aerial images by extracting semantic features at multiple resolutions and projecting them into a shared representation space, enabling efficient cross-view geo-localization.
SDPL: Shifting-Dense Partition Learning for UAV-View Geo-Localization
Proposing shifting-dense partition learning (SDPL) for accurate cross-view geo-localization against position deviations and scale changes.
ConGeo: Robust Cross-View Geo-Localization Study
Enhancing robustness in cross-view geo-localization through ConGeo's contrastive method.
SDPL: Shifting-Dense Partition Learning for UAV-View Geo-Localization
提案されたSDPLは、位置のシフトやスケールの変化に対して堅牢であり、画像検索タスクで競争力のある性能を達成します。
Shifting-Dense Partition Learning for UAV-View Geo-Localization
The author introduces the shifting-dense partition learning (SDPL) framework to address challenges in cross-view geo-localization, focusing on position shifting and scale variations.
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