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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.
The second version of StyleGAN, called StyleGAN2, was published on February 5, 2020. It removes some of the characteristic artifacts and improves the image quality. Nvidia introduced StyleGAN3, described as an "alias-free" version, on June 23, 2021, and made source available on October 12, 2021.
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.
