Researchers Use GeoGuessr Champion to Test Geolocation Accuracy in VLMs

The house in the distance, with a red, hip-shaped roof and white walls, tells Radu Casapu that this place is probably somewhere in Spain or Portugal.

The surrounding trees resemble those of a eucalyptus forest, which could indicate northern Portugal or the Spanish region of Galicia.

It’s the signposts on the road that give it away. They are flat and wide, which is common in Spain but not in Portugal.

Casapu, a master’s student in Georgia Tech’s School of City and Regional Planning, correctly reasons that the picture of a road he’s looking at is in Galicia.

Give Casapu a photo, and he will likely be able to tell you where it was taken.

“I start with infrastructure clues that are specific to a country, region, state or province,” Casapu said. “They include roads or electricity poles, which often remain consistent throughout a country. Once you narrow down the country, you can use more specific factors like vegetation, specific landscapes, or architecture, because these are very nuanced. It’s a top-down approach.”

This is why Casapu is the reigning GeoGussr World Champion — and the ideal expert to test vision-language models (VLMs) on how good they are at geolocation.