참고한 코드: https://github.com/mrzhu-cool/pix2pix-pytorch GitHub - mrzhu-cool/pix2pix-pytorch: PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Network PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks". - GitHub - mrzhu-cool/pix2pix-pytorch: PyTorch implementation of "Image-to-Image Transl... github.com network.py import ..

👩‍💻 Git-hub Link: https://github.com/SohyeonKim-dev/CycleGAN GitHub - SohyeonKim-dev/CycleGAN: 2022 HYPER cycle-GAN 공모전 2022 HYPER cycle-GAN 공모전. Contribute to SohyeonKim-dev/CycleGAN development by creating an account on GitHub. github.com 👩‍💻 느낀 점 1) 생각보다 코드 해석은 어렵지 않았다. 2) 상상 이상으로 훈련하는데 시간 많이 걸림 🤢 3) 공모전 준비로 책도 찾아 읽었는데, 처음으로 탐독해봤다. (미술관에 GAN 딥러닝 실전 프로젝트, 데이비드 포스터) 필요한 부분만 찾아서 읽고, 나머지 부분은 빠르게 ..

생성적 적대 신경망(Generative Adversarial network) https://arxiv.org/abs/1406.2661 https://thispersondoesnotexist.com https://www.youtube.com/watch?v=AVvlDmhHgC4 https://www.youtube.com/watch?v=z-LIpUX-lpc Image to image GAN 1) Pix to Pix 2) Cycle GAN 3) Conditional GAN 4) Stacked GAN 5) Information maximizing GAN 6) Super resolution GAN 7) Patch GAN 8) Pix2pixhd 논문 자료 : 윤영이의 GAN 강의