Which Country Is This? Automatic Country Ranking of Street View Photos

TL;DR

This paper introduces Country Guesser, a live system that predicts the country of a Street View photo using a federated ranking model combining visual, textual, and language model features, pioneering cross-modal country identification.

Contribution

The paper presents a novel federated ranking approach that integrates visual and textual features for country prediction from Street View images, a first in this domain.

Findings

Effective cross-modal features improve country guessing accuracy.

Text-based features aid in leveraging large pre-trained language models.

The system demonstrates real-time country prediction capabilities.

Abstract

In this demonstration, we present Country Guesser, a live system that guesses the country that a photo is taken in. In particular, given a Google Street View image, our federated ranking model uses a combination of computer vision, machine learning and text retrieval methods to compute a ranking of likely countries of the location shown in a given image from Street View. Interestingly, using text-based features to probe large pre-trained language models can assist to provide cross-modal supervision. We are not aware of previous country guessing systems informed by visual and textual features.