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StyleGAN2 - Official TensorFlow Implementation. Contribute to NVlabs/stylegan2 development by creating an account on GitHub.
Picture: These people are not real – they were produced by our generator that allows control over different aspects of the image. This repository contains the official TensorFlow implementation of the following paper: A Style-Based Generator Architecture for Generative Adversarial Networks.
17 de jun. de 2020 · This new project called StyleGAN2, presented at CVPR 2020, uses transfer learning to generate a seemingly infinite numbers of portraits in an infinite variety of painting styles.
Learn how to train StyleGAN 2, an improved generator architecture for generative adversarial networks, with less than 500 lines of code. Compare StyleGAN 2 with Progressive GAN and StyleGAN, and see the differences in image quality and style mixing.
A list of StyleGAN models and datasets from 2017 to 2021, with links to ArXiv papers, PyTorch and TensorFlow implementations, and videos. StyleGAN2-ADA is the latest version of StyleGAN2 with adversarial domain adaptation.
3 de dic. de 2019 · A paper that exposes and addresses the artifacts of StyleGAN, a state-of-the-art generative image model. It proposes changes in model architecture, training methods, and regularization to improve image quality and invertibility.
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.
