Comments (2)
기존 StyleGAN의 문제점
- blob-like artifacts
- AdaIN에 의해 발생한다고 판단
- 작은 spike-type distribution이 feature map으로 들어올 때, 정규화를 통해 증가하고 영향을 끼침
- 새로운 구조 제안
- Progressive GAN에서 발생하는 artifact
- 치열이나 눈동자가 얼굴 방향에 안따라오는 현상
- 새로운 고화질 생성용 구조 제안
Weight Demodulation
- noise를 더해주는 부분을 변경 (norm 이후로 변경)
- AdaIN (Instance Norm + scaling(mean/std)) 대신 conditional scaling (just std!)
- 이 부분이 핵심인데 아직 이해 부족 (근데 재미가 너무 없는데...담에 다시...)
Progressive GAN 대체
- Residual 사용
from deep-papers.
Reference
- 두더지 개발자님 블로그
- 최윤제님 수업
from deep-papers.
Related Issues (20)
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- Progressive Growing of GANs for Improved Quality, Stability, and Variation HOT 2
- Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
- Image-to-Image Translation with Conditional Adversarial Networks HOT 1
- U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
- Wasserstein GAN
- Large Scale GAN Training for High Fidelity Natural Image Synthesis HOT 2
- Self-Attention Generative Adversarial Networks HOT 3
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from deep-papers.