Modern Backbone for Efficient Geo-localization

With the development of autonomous driving technology, vision geo-localization has obtained a consistently growing following. How to match correct image pair from different perspectives is the key technology. Existing geo-localization methods focus on designing complex attention mechanism based on traditional backbone, e.g., VGG, ResNet, but neglect the importance of backbone network. In this article, we propose a modern backbone based geo-localization method (MBEG). MBEG introduces the latest vision fundamental network EVA-02 as backbone, which has been fully trained in large datasets. In addition, the feature rotate encoding strategy is presented to eliminate the effects of image rotation. We also apply the knowledge distillation to squeeze network's parameters for actual application. Our work exhibited excellent performance on the University-1652 dataset, and our solution attained the top-1 ranking in the UAVs in Multimedia Challenge[25] for the University-160k dataset.