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posted by chromas on Thursday April 12 2018, @01:31PM   Printer-friendly
from the deeplearn-vs-deeplearn dept.

Submitted via IRC for SoyCow9228

We all know that AI can be used to swap faces in photos and videos. People have, of course, taken advantage of this tool for some disturbing uses, including face-swapping people into pornographic videos -- the ultimate revenge porn. But if AI can be used to face swap, can't it also be used to detect when such a practice occurs? According to a new paper on arXiv.org, a new algorithm promises to do just that, identifying forged videos as soon as they are posted online.

Source: https://www.engadget.com/2018/04/11/machine-learning-face-swaps-xceptionnet/

Technology Review continues:

But the work also has sting in the tail. The same deep-learning technique that can spot face-swap videos can also be used to improve the quality of face swaps in the first placeā€”and that could make them harder to detect.

The new technique relies on a deep-learning algorithm that [Andreas] Rossler and co have trained to spot face swaps. These algorithms can only learn from huge annotated data sets of good examples, which simply have not existed until now.

So the team began by creating a large data set of face-swap videos and their originals.


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  • (Score: 2) by takyon on Thursday April 12 2018, @02:30PM

    by takyon (881) <takyonNO@SPAMsoylentnews.org> on Thursday April 12 2018, @02:30PM (#665936) Journal

    YouTube and other video sites will use algorithms like this to slap a "Fake Video" tag on faceswapped videos, like Google News and Facebook are trying to do with fact-checking news items. People will promptly ignore it and believe in the faked footage. Everyone else will reap the benefits of 5% less uncanny looking faceswapped porn.

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