论文标题
与Stylegan的面部生成和编辑：一项调查
Face Generation and Editing with StyleGAN: A Survey
论文作者
论文摘要
我们对这项调查的目标是概述使用StyleGan的面部生成和编辑的最先进的深度学习方法。该调查涵盖了Stylegan的演变，从PGGAN到StyleGan3，并探讨了相关主题，例如适合培训的指标，不同的潜在表示，gan倒置到Stylegan的潜在空间，脸部图像编辑，跨域面部式样式化，面部恢复，脸部修复，甚至是深层应用程序。我们旨在为读者提供一个有关深度学习领域并正在寻找可访问的介绍和概述的读者的入口点。
Our goal with this survey is to provide an overview of the state of the art deep learning methods for face generation and editing using StyleGAN. The survey covers the evolution of StyleGAN, from PGGAN to StyleGAN3, and explores relevant topics such as suitable metrics for training, different latent representations, GAN inversion to latent spaces of StyleGAN, face image editing, cross-domain face stylization, face restoration, and even Deepfake applications. We aim to provide an entry point into the field for readers that have basic knowledge about the field of deep learning and are looking for an accessible introduction and overview.
