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Exploring Deepfakes

You're reading from  Exploring Deepfakes

Product type Book
Published in Mar 2023
Publisher Packt
ISBN-13 9781801810692
Pages 192 pages
Edition 1st Edition
Languages
Authors (2):
Bryan Lyon Bryan Lyon
Profile icon Bryan Lyon
Matt Tora Matt Tora
Profile icon Matt Tora
View More author details

Table of Contents (15) Chapters

Preface 1. Part 1: Understanding Deepfakes
2. Chapter 1: Surveying Deepfakes 3. Chapter 2: Examining Deepfake Ethics and Dangers 4. Chapter 3: Acquiring and Processing Data 5. Chapter 4: The Deepfake Workflow 6. Part 2: Getting Hands-On with the Deepfake Process
7. Chapter 5: Extracting Faces 8. Chapter 6: Training a Deepfake Model 9. Chapter 7: Swapping the Face Back into the Video 10. Part 3: Where to Now?
11. Chapter 8: Applying the Lessons of Deepfakes 12. Chapter 9: The Future of Generative AI 13. Index 14. Other Books You May Enjoy

Text-guided image generation

Text-guided image generation is an interesting category of generative AI. OpenAI had several developers release a paper called Learning Transferable Visual Models From Natural Language Supervision (https://arxiv.org/abs/2103.00020). Though I prefer the summary title they posted on their blog CLIP: Connecting Text and Images. CLIP was mentioned in Chapter 8, Applying the Lessons of Deepfakes, but we’ll talk about it some more here.

CLIP

CLIP is actually a pair of neural network encoders. One is trained on images while the other is trained on text. So far, this isn’t very unusual. The real trick comes from how the two are linked. Essentially, both encoders are passed data from the same image; the image encoder gets the image, the text encoder gets the image’s description, and then the encoding they generate is compared to each other. This training methodology effectively trains two separate models to create the same output given...

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