Lost in the Tail: Addressing Geographic Imbalance in Urban Visual Place Recognition
arXiv cs.CV1mo4 min read
arXiv:2607.00090v1 Announce Type: new Abstract: Urban-scale Visual Place Recognition (VPR) aims to identify the geographic location of a query image by matching it against a geo-tagged database. While recent methods achieve impressive performance, they overlook a serious long-tailed problem hidden in urban-scale datasets, which biases the model towards locations with abundant images and ignores less-visited areas, causing models to systematically favor frequently photographed locations while failing in sparsely covered areas. In this paper, we systematically characterize this imbalance challen
