# Faceforensics: This AI Detects DeepFakes!

## Метаданные

- **Канал:** Two Minute Papers
- **YouTube:** https://www.youtube.com/watch?v=Te0L5_u_wIg
- **Дата:** 26.06.2018
- **Длительность:** 2:23
- **Просмотры:** 30,539
- **Источник:** https://ekstraktznaniy.ru/video/14451

## Описание

The paper "FaceForensics: A Large-scale Video Dataset for Forgery Detection in Human Faces " is available here:
http://niessnerlab.org/projects/roessler2018faceforensics.html

Pick up cool perks on our Patreon page: https://www.patreon.com/TwoMinutePapers

We would like to thank our generous Patreon supporters who make Two Minute Papers possible:
313V, Andrew Melnychuk, Brian Gilman, Christian Ahlin, Christoph Jadanowski, Dennis Abts, Emmanuel, Eric Haddad, Esa Turkulainen, Geronimo Moralez, Kjartan Olason, Lorin Atzberger, Malek Cellier, Marten Rauschenberg, Michael Albrecht, Michael Jensen, Morten Punnerud Engelstad, Nader Shakerin, Rafael Harutyuynyan, Raul Araújo da Silva, Rob Rowe, Robin Graham, Ryan Monsurate, Shawn Azman, Steef, Steve Messina, Sunil Kim, Torsten Reil.
https://www.patreon.com/TwoMinutePapers

Thumbnail background image credit: https://pixabay.com/photo-593358/
Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu

Károly Zsolnai-Fehér's links:
Faceboo

## Транскрипт

### FaceForensics: Identifying Facial Forgeries []

Dear Fellow Scholars, this is Two Minute Papers with Károly Zsolnai-Fehér. With the recent ascendancy of several new AI-based techniques for human facial reenactment, we are now able to create videos where we transfer our gestures onto famous actors or politicians and impersonate them.

### FaceForensics: Dataset Generation [0:16]

Clearly, as this only needs a few minutes of video as training data from the target, this could be super useful for animating photorealistic characters for video games and movies, reviving legendary actors who are not with us anymore, and much more.

### Face Forensics: Dataset [0:27]

And understandably, some are worried about the social implications of such a powerful

### Classification [0:34]

tool. In other words, if there are tools to create forgery, there should be tools to detect forgery, right? If we can train an AI to impersonate, why not train an other AI to detect impersonation? This has to be an arms race. However, this is no easy task to say the least. As an example, look here. Some of these faces are real, some are fake. What do you think, which is which? I will have to admit, my guesses weren't all that great. But what about you? Let me know in the comments section. Compression is also an issue. Since all videos you see here on YouTube are compressed in some way to reduce filesize, some of the artifacts that appear may easily throw off not only an AI, but a human as well. I bet there will be many completely authentic videos that will be thought of as fakes by humans in the near future. So how do we solve these problems? First, to obtain a neural network-based solution, we need a large dataset to train it on. This paper contains a useful dataset with over a 1000 videos that we can use to train such a neural network. These records contain pairs of original and manipulated videos, along with the input footage of the gestures that were transferred. After the training step, the algorithm will be able to pick up on the smallest changes

### Segmentation [1:48]

around the face and tell a forged footage from a real one, even in cases where we humans are unable to do that. This is really amazing. These green to red colors showcase regions that the AI thinks were tampered with. And it is correct. Interestingly, this can not only identify regions that are forgeries, but it can also

### Generative Refinement [2:08]

improve these forgeries too. I wonder if it can detect footage that is has improved itself? What do you think? Thanks for watching and for your generous support, and I'll see you next time!