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.
Titel | Which Country Is This? Automatic Country Ranking of Street View Photos |
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Medien | Advances in Information Retrieval: Proceedings of the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2-6, 2023 |
Verlag | Springer |
Heft | --- |
Band | 3 |
ISBN | 978-3-031-28240-9 |
Verfasser/Herausgeber | T. Menzner, Prof. Dr. Florian Mittag, Prof. Dr. Jochen L. Leidner |
Seiten | 275–280 |
Veröffentlichungsdatum | 16.03.2023 |
Projekttitel | --- |
Zitation | Menzner, T.; Mittag, Florian; Leidner, Jochen L. (2023): Which Country Is This? Automatic Country Ranking of Street View Photos. Advances in Information Retrieval: Proceedings of the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2-6, 2023 3, S. 275–280. DOI: 10.1007/978-3-031-28241-6_26 |