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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

Concepts

Author (1):

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

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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.

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Authors (1)

Kailash Ahirwar

Kailash Ahirwar is a machine learning and deep learning enthusiast. He has worked in many areas of Artificial Intelligence (AI), ranging from natural language processing and computer vision to generative modeling using GANs. He is a co-founder and CTO of Mate Labs. He uses GANs to build different models, such as turning paintings into photos and controlling deep image synthesis with texture patches. He is super optimistic about AGI and believes that AI is going to be the workhorse of human evolution.

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