Collaborative Visual Place Recognition through Federated Learning

arXiv:2404.13324v1 Announce Type: new
Abstract: Visual Place Recognition (VPR) aims to estimate the location of an image by treating it as a retrieval problem. VPR uses a database of geo-tagged images and leverages deep neural networks to extract a global representation, called descriptor, from each image. While the training data for VPR models often originates from diverse, geographically scattered sources (geo-tagged images), the training process itself is typically assumed to be centralized. This research revisits the task of VPR through …

abstract arxiv collaborative cs.cv data database extract federated learning geo global image images location networks neural networks recognition representation retrieval through training training data type visual