Basically a combination of what the game geoguesser does, and public geotagged images to be able to get a decent shot at approximate location for previously unseen areas.
It’s more ominous when automated, but with only a little practice it’s easy enough for a human to get significantly better.
EDIT: yup, looks like this is the guy from the Twitter: https://andrewgao.dev/ and he’s Stanford affiliated with the same department that made the above paper and system.
I am not sure it’s the same software, but it’s a fairly good guess I think. Same software capabilities and same lab, with the same area of research.
Geoguesser is a subset of the skills used for general image geo location for open source intelligence.
In the specific cases of only using the data present in the image and relying on geographic information, it certainly does better.
Humans still do better, and can reach decent skill with minimal training, at placing images that require spatial reasoning or referencing multiple data sources.
AI tools will likely be able to learn those extra skills, but it doesn’t change that it’s the photo that’s the data leak, and not the tool. The tool just makes it vastly more accessible, and part of the task easier for curious human.
https://github.com/LukasHaas/PIGEON
https://arxiv.org/abs/2307.05845
Basically a combination of what the game geoguesser does, and public geotagged images to be able to get a decent shot at approximate location for previously unseen areas.
It’s more ominous when automated, but with only a little practice it’s easy enough for a human to get significantly better.
EDIT: yup, looks like this is the guy from the Twitter: https://andrewgao.dev/ and he’s Stanford affiliated with the same department that made the above paper and system.
Are you sure? The paper you linked mentioned the model beating a top geoguesser player six times in a row.
I am not sure it’s the same software, but it’s a fairly good guess I think. Same software capabilities and same lab, with the same area of research.
Geoguesser is a subset of the skills used for general image geo location for open source intelligence.
In the specific cases of only using the data present in the image and relying on geographic information, it certainly does better.
Humans still do better, and can reach decent skill with minimal training, at placing images that require spatial reasoning or referencing multiple data sources.
AI tools will likely be able to learn those extra skills, but it doesn’t change that it’s the photo that’s the data leak, and not the tool. The tool just makes it vastly more accessible, and part of the task easier for curious human.