[Day67] AI에게 색칠공부하게 만들기

오늘의 실습은 스케치만 있는 이미지를 입력하면 AI가 알아서 색칠을 하도록 만드는 것이었는데요. 이 실습을 하면서 참고한 자료들을 아래에 공유합니다.

1. TF2-GAN

github.com/thisisiron/TF2-GAN

thisisiron/TF2-GAN

2. Stochastic Polling & Maxout

m.blog.naver.com/PostView.nhn?blogId=laonple&logNo=221259325819&proxyReferer=&proxyReferer=https:%2F%2Fwww.google.com%2F

9. Stochastic Polling & Maxouot

3, Maxout Networks

arxiv.org/pdf/1302.4389.pdf

4. GAN 500 (data)

https://aiffelstaticprd.blob.core.windows.net/media/documents/GAN_500.zip

5. Image-to-Image Translation with Conditional Adversarial Networks (paper)

arxiv.org/pdf/1611.07004.pdf

6. U-Net 논문 리뷰 — U-Net: Convolutional Networks for Biomedical Image Segmentation

medium.com/@msmapark2/u-net-%EB%85%BC%EB%AC%B8-%EB%A6%AC%EB%B7%B0-u-net-convolutional-networks-for-biomedical-image-segmentation-456d6901b28a

U-Net 논문 리뷰 — U-Net: Convolutional Networks for Biomedical Image Segmentation

7. Sketch2Pokemon (kaggle)

www.kaggle.com/norod78/sketch2pokemon

Sketch2Pokemon

8. Understanding PatchGAN

medium.com/@sahiltinky94/understanding-patchgan-9f3c8380c207

Understanding PatchGAN

9. Cityscape data

aiffelstaticprd.blob.core.windows.net/media/documents/cityscapes.zip

10. Pix2Pix

www.tensorflow.org/tutorials/generative/pix2pix?hl=ko

Pix2Pix  |  TensorFlow Core