AI RESEARCH
GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching
arXiv CS.CV
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ArXi:2604.25390v1 Announce Type: cross Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity. Recent generative approaches based on Retrieval-Augmented Generation (RAG) and Large Multimodal Models (LMMs) leverage candidates retrieved from fixed databases for reasoning, but often struggle with scenes that are absent from the reference set. In this work, we propose GeoSearch, an open-world geolocation framework that integrates web-scale reverse image search into the RAG pipeline.