AI RESEARCH

DualGeo: A Dual-View Framework for Worldwide Image Geo-localization

arXiv CS.CV

ArXi:2604.25533v1 Announce Type: new Worldwide image geo-localization aims to infer the geographic location of an image captured anywhere on Earth, spanning street, city, regional, national, and continental scales. Existing methods rely on visual features that are sensitive to environmental variations (e.g., lighting, season, and weather) and lack effective post-processing to filter outlier candidates, limiting localization accuracy. To address these limitations, we propose DualGeo, a two-stage framework for worldwide image geo-localization.