Let's talk about Fakes

Transcript

1. Let's talk about Fakes Let's talk about all the good things And the bad things that may be
2. Making Faces • Face Synthesis
 from nothing to face • Facial Attributes 
 modify age, gender, add glasses change hairstyle or color • Face Swap
 use the body and background of target, face of source • Facial Expression Transfer
 transfer only the expression or modify expression to match an impersonator or an audio track (reenactment)
4. Face Synthesis https://research.nvidia.com/publication/2017-10_Progressive-Growing-of
5. https://thispersondoesnotexist.com/
6. Facial Attributes
7. https://www.faceapp.com/
8. https://www.faceapp.com/
9. Face Off (1997)
10. Nicolas Cage Everywhere
11. Reenactment Cafe 80s, Hill Valley, USA, (October 21, 2015)
12. Jordan Peele (2018)
13. Face2Face (2016)
14. RGB-D tracking
17. FaceSwapGAN (2018)
26. FaceShifter (Dec 2019)
30. How to Spot a Fake
31. https://www.kaggle.com/c/deepfake-detection-challenge
32. uneven skin tone artifacts in hair says strange things warped edges How to Spot a Fake obstruction glitches
33. That was a real photo.
34. uneven skin tone artifacts in hair says strange things warped edges How to Spot a Fake obstruction glitches
35. https://people.csail.mit.edu/mrub/vidmag/
36. Why this is important
37. We are hardwired to react to faces.
39. Especially to moving faces. 
 Even more so, emotional.
41. We have a tendency to fall for and spread shocking images.
44. We react to images that speak to our tribal instincts or align with our political world view
47. No matter how we try, how many tools we create to detect fakes, we WILL BE AFFECTED...
48. ...the question is: HOW?