This is a pytorch implementation of Generative Adversarial Text-to-Image Synthesis paper, we train a conditional generative adversarial network.

This is a PyTorch-based implementation of the Generative Adversarial Text-to-Image Synthesis paper, utilizing a GAN architecture inspired by DCGAN.

17 мая 2016 г. · In this work, we develop a novel deep architecture and GAN formulation to effectively bridge these advances in text and image model- ing, ...

This tutorial will give an introduction to DCGANs through an example. We will train a generative adversarial network (GAN) to generate new celebrities. Не найдено: synthesis | Нужно включить: synthesis

1 авг. 2023 г. · Generative adversarial text to image synthesis proposes matching-aware discriminator (GAN-CLS), learning with manifold interpolation (GAN-INT), & combined one ...

In this paper, we propose Stacked Generative Adversarial Networks (StackGAN) aiming at generating high-resolution photo-realistic images. 16. Benchmarks · Subtasks

Hands-On Generative Adversarial Networks with PyTorch 2.x: Generate awesome image, audio, text, and 3D models using Python, 2nd Edition.

43,99 $ В наличии This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples.

Продолжительность: 34:28
Опубликовано: 1 авг. 2021 г.

To solve this challenging problem requires solving two sub- problems: first, learn a text feature representation that cap- tures the important visual details; ... Не найдено: pytorch | Нужно включить: pytorch