Visual Geo-Localization is the problem of estimating the geographical coordinates of an image given a database of geo-tagged pictures from known places. This task carries out as an image matching and retrieval problem. Where the picture to be localised compares itself against all the images in the database and a shortlist of possible matches retrieved with a k-Nearest Neighbor (kNN) search. The matching operation uses global image descriptors. The task poses some concerns related to the centralised maintenance of the images and privacy. (e.g. A violation of users' privacy is done if we collect their photographs. Due to photos loaded on a central server, they will be available for everyone.) These issues are at the foundation of the Federated Learning paradigm.