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Generative Adversarial Networks Projects

You're reading from  Generative Adversarial Networks Projects

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136678
Pages 316 pages
Edition 1st Edition
Languages
Author (1):
Kailash Ahirwar Kailash Ahirwar
Profile icon Kailash Ahirwar

Table of Contents (11) Chapters

Preface 1. Introduction to Generative Adversarial Networks 2. 3D-GAN - Generating Shapes Using GANs 3. Face Aging Using Conditional GAN 4. Generating Anime Characters Using DCGANs 5. Using SRGANs to Generate Photo-Realistic Images 6. StackGAN - Text to Photo-Realistic Image Synthesis 7. CycleGAN - Turn Paintings into Photos 8. Conditional GAN - Image-to-Image Translation Using Conditional Adversarial Networks 9. Predicting the Future of GANs 10. Other Books You May Enjoy

Architecture of StackGAN

StackGAN is a two-stage network. Each stage has two generators and two discriminators. StackGAN is made up of many networks, which are as follows:

  • Stack-I GAN: text encoder, Conditioning Augmentation network, generator network, discriminator network, embedding compressor network
  • Stack-II GAN: text encoder, Conditioning Augmentation network, generator network, discriminator network, embedding compressor network
Source: arXiv:1612.03242 [cs.CV]

The preceding image is self-explanatory. It represents both stages of the StackGAN network. As you can see, the first stage is generating images with dimensions of 64x64. Then the second stage takes these low-resolution images and generates high-resolution images with dimensions of 256x256. In the next few sections, we will explore the different components in the StackGAN network. Before doing this, however, let...

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