Generative Models

StyleGAN2

Introduced by Karras et al. in Analyzing and Improving the Image Quality of StyleGAN

StyleGAN2 is a generative adversarial network that builds on StyleGAN with several improvements. First, adaptive instance normalization is redesigned and replaced with a normalization technique called weight demodulation. Secondly, an improved training scheme upon progressively growing is introduced, which achieves the same goal - training starts by focusing on low-resolution images and then progressively shifts focus to higher and higher resolutions - without changing the network topology during training. Additionally, new types of regularization like lazy regularization and path length regularization are proposed.

Source: Analyzing and Improving the Image Quality of StyleGAN

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Image Generation 52 19.33%
Disentanglement 13 4.83%
Image Manipulation 13 4.83%
Face Generation 11 4.09%
Face Recognition 8 2.97%
Translation 7 2.60%
Conditional Image Generation 7 2.60%
Face Swapping 6 2.23%
Domain Adaptation 6 2.23%

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