SITCON18

1. Use AI to make
our own anime
girl face
Chia-Che​ (Mike) ​Chang
https://www.sli.do/SITCON18-S02

2. Hubert​ ​Lin
功德做盡力竭身亡
Yu-Chun (Howard) LoChia-Che​ (Mike) ​Chang
天下妹子皆我朋友

3. Outline
• Machine learning in the real life
• Generative adversarial networks (GAN)
• Use AI to make our own anime girl face
• Reference

4. Machine learning in the
movies
[Source: Machine Learning Lec1,Da-Cheng Juan]

5. Machine learning in real life
• Siri
• Amazon Echo
• Self-Driving Car
• Face Recognition
• etc.
[Source: DeepFace: Closing the Gap to
Human-Level Performance in Face Verification]

6. AlphaGo
[Source: https://deepmind.com/blog/alphago-zero-learning-scratch/]

7. What can we do with AI?

8. What can we do with AI?

9. What can we do with AI?

10. What can we do with AI?

11. What can we do with AI?
[Source: http://violet-evergarden.jp/]

12. GAN

13. GAN
[Source: https://www.slideshare.net/ckmarkohchang/generative-adversarial-networks]

14. GAN
[Source: https://www.slideshare.net/ckmarkohchang/generative-adversarial-networks]

15. GAN
[Source: https://www.slideshare.net/ckmarkohchang/generative-adversarial-networks]

16. GAN
[Source: https://www.slideshare.net/ckmarkohchang/generative-adversarial-networks]

17. Use AI to make our own anime
girl face

18. • CelebA [Real human image]
• 202599 images
• Resolution: 170x170
• [Anime girl image]
• 3589 images
• Resolution: 250x300
• Collected by ourselves
Dataset

19. 1. Recognize face
2. Center crop
3. Resize to 256x256
1. Directly center crop
2. Resize to 256x256
Dataset

20. 3
eyes
Failed
cropping
Weird accessories Multiple people
Dataset

21. CycleGAN

22. CycleGAN

23. CycleGAN

24. CycleGAN
• The results are bad and noisy.

25. CycleGAN
• The results are bad and noisy.
Inconsistence weird eyes Inconsistence

26. + Cropped Images
• Better quality, but outputs are still unstable and
noisy.

27. + Spectral Normalization
• Better quality

28. + Noisy Label

29. + Noisy Label

30. + FisherGAN

31. + FisherGAN

32. + FisherGAN

33. Interesting cases

34. Reference
• Paper
• Generative Adversarial Networks
• Image-to-Image Translation with Conditional
Adversarial Nets
• Unpaired Image-to-Image Translation using Cycle-
Consistent Adversarial Networks
• Least Squares Generative Adversarial Networks
• Spectral Normalization for Generative Adversarial
Networks
• Fisher GAN
• Dataset
• CelebA:
http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
• Anime girl: http://www.getchu.com/

35. Thanks for your listening!
These are our team members :)