Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Image Generation with TensorFlow

You're reading from   Hands-On Image Generation with TensorFlow A practical guide to generating images and videos using deep learning

Arrow left icon
Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781838826789
Length 306 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Soon Yau Cheong Soon Yau Cheong
Author Profile Icon Soon Yau Cheong
Soon Yau Cheong
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Fundamentals of Image Generation with TensorFlow
2. Chapter 1: Getting Started with Image Generation Using TensorFlow FREE CHAPTER 3. Chapter 2: Variational Autoencoder 4. Chapter 3: Generative Adversarial Network 5. Section 2: Applications of Deep Generative Models
6. Chapter 4: Image-to-Image Translation 7. Chapter 5: Style Transfer 8. Chapter 6: AI Painter 9. Section 3: Advanced Deep Generative Techniques
10. Chapter 7: High Fidelity Face Generation 11. Chapter 8: Self-Attention for Image Generation 12. Chapter 9: Video Synthesis 13. Chapter 10: Road Ahead 14. Other Books You May Enjoy

Segmentation map-to-image translation with GauGAN

GauGAN (named after 19th-century painter Paul Gauguin) is a GAN from Nvidia. Speaking of Nvidia, it is one of the handful of companies that has invested heavily in GANs. They have achieved several breakthroughs in this space, including ProgressiveGAN (we'll cover that in Chapter 7, High Fidelity Face Generation), to generate high-resolution images, and StyleGAN for high-fidelity faces.

Their main business is in making graphics chips rather than AI software. Therefore, unlike some other companies, who keep their code and trained models as closely guarded secrets, Nvidia tends to open source their software code to the general public. They have built a web page (http://nvidia-research-mingyuliu.com/gaugan/) to showcase GauGAN, which can generate photorealistic landscape photos from segmentation maps. The following screenshot is taken from their web page.

Feel free to pause this chapter for a bit and have a play with the application...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image