Optimal Transport Aggregation for Visual Place Recognition

The task of Visual Place Recognition (VPR) aims to match a query image against references from an extensive database of images from different places, relying solely on visual cues. State-of-the-art pipelines focus on the aggre-gation offeatures extractedfrom a deep backbone, in order to form a global descriptor for each image. In this con-text, we introduce SALAD (Sinkhorn Algorithm for Locally Aggregated Descriptors), which reformulates NetVLAD's soft-assignment of local features to clusters as an optimal transport problem. In SALAD, we consider both feature-to-cluster and cluster-to-feature relations and we also in-troduce a ‘dustbin’ cluster, designed to selectively discard features deemed non-informative,…