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Bridging the Domain Gap for Ground-to-Aerial Image Matching

Bridging the Domain Gap for Ground-to-Aerial Image Matching

The visual entities in cross-view (e.g. ground and aerial) images exhibit drastic domain changes due to the differences in viewpoints each set of images is captured from. Existing state-of-the-art methods address the problem by learning view-invariant images descriptors. We propose a novel method for solving this task by exploiting the …