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Generative Adversarial Networks Projects

You're reading from   Generative Adversarial Networks Projects Build next-generation generative models using TensorFlow and Keras

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136678
Length 316 pages
Edition 1st Edition
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Author (1):
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Kailash Ahirwar Kailash Ahirwar
Author Profile Icon Kailash Ahirwar
Kailash Ahirwar
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Table of Contents (11) Chapters Close

Preface 1. Introduction to Generative Adversarial Networks FREE CHAPTER 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

Preparing the data

In this chapter, we will use the 3D ShapeNets dataset, available at http://3dshapenets.cs.princeton.edu/3DShapeNetsCode.zip. It was released by Wu and Song et al. and consists of properly annotated 3D shapes for 40 object categories. We will use the volumetric data available in the directory, which we will discuss in more detail later on in this chapter. In the next few sections, we will download, extract, and explore the dataset.

The 3D ShapeNets dataset is for academic use only. If you intend to use the dataset for commercial purposes, request permission from the authors of the paper, who can be reached at the following email address: shurans@cs.princeton.edu.

Download and extract the dataset

Run the following...

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