With "NaviClues" and "Navig": Image Geolocalization through AI-Powered Language Analysis

Precisely determining the location where a picture was taken, known as image geolocation, is a complex task requiring an understanding of visual, geographical, and cultural contexts. While Vision Language Models (VLMs) achieve the best results in this area, there's a lack of high-quality datasets and models for analytical reasoning. A new framework called "Navig," combined with the "NaviClues" dataset, promises a solution.

NaviClues: A Dataset for Expert Knowledge

A team of researchers has succeeded in creating "NaviClues," a high-quality dataset based on the popular geography game GeoGuessr. This dataset provides examples of expert knowledge presented in linguistic form. Specifically, gameplay from experienced GeoGuessr players on YouTube was analyzed, and the conclusions they drew were extracted. These range from identifying vegetation and architecture to interpreting road signs and analyzing license plates. "NaviClues" thus offers a valuable foundation for training AI models in the field of image geolocation.

Navig: A Comprehensive Framework for Image Geolocation

Building upon "NaviClues," "Navig" was developed as a comprehensive framework that integrates global and detailed image information. "Navig" uses the linguistic reasoning contained in "NaviClues" to narrow down the location of an image step by step. It considers both global information such as the general landscape and vegetation, as well as fine details like road signs or the architecture of buildings. By combining visual information with linguistic reasoning, "Navig" achieves a significant improvement in accuracy for image geolocation.

The Advantages of Navig

A key advantage of "Navig" lies in its ability to identify and search text within images. For example, street signs, business names, or license plates can be read and used for localization. This targeted search for relevant information can significantly increase the accuracy of position determination. Compared to previous state-of-the-art models, "Navig" reduces the average distance error by 14%, and does so with fewer than 1000 training examples.

Outlook and Significance for the Future

The development of "NaviClues" and "Navig" represents significant progress in the field of image geolocation. The combination of visual information with linguistic reasoning allows for more precise and efficient localization of images. The ability to recognize and interpret text within images also opens up new possibilities for analyzing image content. The research results are promising and could find future applications in various areas, from mapping and navigation to image search and analysis.

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