StyleganPDF

2022年12月18日 — PDF | Our goal with this survey is to provide an overview of the state of the art deep learning technologies for face generation and editing ...

由 T Karras 著作 · 2019 · 被引用 9655 次 — We propose an alternative generator architecture for gen- erative adversarial networks, borrowing from style transfer literature. The new architecture leads ...

由 T Karras 著作 · 2020 · 被引用 5229 次 — The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional gener- ative image modeling. We expose and analyze ...

High-quality version of the paper PDF. ├ stylegan-video.mp4, High-quality version of the result video. ├ images, Example images produced using our generator.

2022年8月11日 — StyleGAN in particular sets new standards for generative modeling regarding image quality and controllability. However, StyleGAN's performance ...

由 W Nie 著作 · 被引用 70 次 — In this work, we investigate semi- supervised disentanglement learning based on StyleGAN. (Karras et al., 2019), one of the state-of-the-art generative.

由 A Sauer 著作 · 2023 · 被引用 79 次 — StyleGAN-T greatly narrows the quality gap between GANs and other model families while generating samples at a rate of 10 FPS on an NVIDIA A100. The y-axis ...

由 A Sauer 著作 · 2023 · 被引用 79 次 — Download a PDF of the paper titled StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis, by Axel Sauer and 4 ...

由 T Karras 著作 · 2018 · 被引用 9655 次 — Abstract:We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature.

This paper describes a new methodology to train a style-based autoencoder where the encoder and generator are optimized end-to-end and shows that the ...