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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 2. 3D-GAN - Generating Shapes Using GANs FREE CHAPTER 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

Practical applications of 3D-GANs

3D-GANs can potentially be used in a wide variety of industries, as follows:

  • Manufacturing: 3D-GANs can be a creative tool to help create prototypes quickly. They can come up with creative ideas and can help in simulating and visualizing 3D models.
  • 3D printing: 3D images generated by 3D-GANs can be used to print objects in 3D printing. The manual process of creating 3D models is very lengthy.
  • Design processes: 3D generated models can provide a good estimate of the eventual outcome of a particular process. They can show us what is going to get built.
  • New samples: Similar to other GANs, 3D-GANs can generate images to train a supervised model.

You have been reading a chapter from
Generative Adversarial Networks Projects
Published in: Jan 2019
Publisher: Packt
ISBN-13: 9781789136678
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