4 posts tagged “geoguessing”
Guessing the location of an image based on visual clues.
2025
o3 Beats a Master-Level Geoguessr Player—Even with Fake EXIF Data. Sam Patterson (previously) puts his GeoGuessr ELO of 1188 (just short of the top champions division) to good use, exploring o3's ability to guess the location from a photo in a much more thorough way than my own experiment.
Over five rounds o3 narrowly beat him, guessing better than Sam in only 2/5 but with a higher score due to closer guesses in the ones that o3 won.
Even more interestingly, Sam experimented with feeding images with fake EXIF GPS locations to see if o3 (when reminded to use Python to read those tags) would fall for the trick. It spotted the ruse:
Those coordinates put you in suburban Bangkok, Thailand—obviously nowhere near the Andean coffee-zone scene in the photo. So either the file is a re-encoded Street View frame with spoofed/default metadata, or the camera that captured the screenshot had stale GPS information.
We've been seeing if the latest versions of LLMs are any better at geolocating and chronolocating images, and they've improved dramatically since we last tested them in 2023. [...]
Before anyone worries about it taking our job, I see it more as the difference between a hand whisk and an electric whisk, just the same job done quicker, and either way you've got to check if your peaks are stiff at the end of it.
— Eliot Higgins, Bellingcat
My post on o3 guessing locations from photos made it to Hacker News and by far the most interesting comments are from SamPatt, a self-described competitive GeoGuessr player.
In a thread about meta-knowledge of the StreetView card uses in different regions:
The photography matters a great deal - they're categorized into "Generations" of coverage. Gen 2 is low resolution, Gen 3 is pretty good but has a distinct car blur, Gen 4 is highest quality. Each country tends to have only one or two categories of coverage, and some are so distinct you can immediately know a location based solely on that (India is the best example here). [...]
Nigeria and Tunisia have follow cars. Senegal, Montenegro and Albania have large rifts in the sky where the panorama stitching software did a poor job. Some parts of Russia had recent forest fires and are very smokey. One road in Turkey is in absurdly thick fog. The list is endless, which is why it's so fun!
Sam also has his own custom Obsidian flashcard deck "with hundreds of entries to help me remember road lines, power poles, bollards, architecture, license plates, etc".
I asked Sam how closely the GeoGuessr community track updates to street view imagery, and unsurprisingly those are a big deal. Sam pointed me to this 10 minute video review by zi8gzag of the latest big update from three weeks ago:
This is one of the biggest updates in years in my opinion. It could be the biggest update since the 2022 update that gave Gen 4 to Nigeria, Senegal, and Rwanda. It's definitely on the same level as the Kazakhstan update or the Germany update in my opinion.
Watching o3 guess a photo’s location is surreal, dystopian and wildly entertaining
Watching OpenAI’s new o3 model guess where a photo was taken is one of those moments where decades of science fiction suddenly come to life. It’s a cross between the Enhance Button and Omniscient Database TV Tropes.
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