Which country is this picture from? New data and methods for DNN-based country recognition
Not on the map. Why?
Abstract (arXiv)
Recognizing the country where a picture has been taken has many potential applications, such as identification of fake news and prevention of disinformation campaigns. Previous works focused on the estimation of the geo-coordinates where a picture has been taken. Yet, recognizing in which country an image was taken could be more critical, from a semantic and forensic point of view, than estimating its spatial coordinates. In the above framework, this paper provides two contributions. First, we introduce the VIPPGeo dataset, containing 3.8 million geo-tagged images. Secondly, we used the dataset to train a model casting the country recognition problem as a classification problem. The experiments show that our model provides better results than the current state of the art. Notably, we found that asking the network to identify the country provides better results than estimating the geo-coordinates and then tracing them back to the country where the picture was taken.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 2 Sep 2022.
Builds on
14 of 31 references.
References · 14
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Built on by
Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2025World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Modelscited by 3
- 2026Cultural Counterfactuals: Evaluating Cultural Biases in Large Vision-Language Models with Counterfactual Examplescited by 2
- 2024Which Country Is This? Automatic Country Ranking of Street View Photoscited by 0
- 2026Cultural Counterfactuals: Evaluating Cultural Biases in Large Vision-Language Models with Counterfactual Examples2 Mar 2026
- 2025World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models27 Nov 2025
- 2024Which Country Is This? Automatic Country Ranking of Street View Photos11 Jun 2024