Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Exploring Deepfakes
  • Table Of Contents Toc
  • Feedback & Rating feedback
Exploring Deepfakes

Exploring Deepfakes

By : Bryan Lyon, Matt Tora
4.5 (6)
close
close
Exploring Deepfakes

Exploring Deepfakes

4.5 (6)
By: Bryan Lyon, Matt Tora

Overview of this book

Applying Deepfakes will allow you to tackle a wide range of scenarios creatively. Learning from experienced authors will help you to intuitively understand what is going on inside the model. You’ll learn what deepfakes are and what makes them different from other machine learning techniques, and understand the entire process from beginning to end, from finding faces to preparing them, training the model, and performing the final swap. We’ll discuss various uses for face replacement before we begin building our own pipeline. Spending some extra time thinking about how you collect your input data can make a huge difference to the quality of the final video. We look at the importance of this data and guide you with simple concepts to understand what your data needs to really be successful. No discussion of deepfakes can avoid discussing the controversial, unethical uses for which the technology initially became known. We’ll go over some potential issues, and talk about the value that deepfakes can bring to a variety of educational and artistic use cases, from video game avatars to filmmaking. By the end of the book, you’ll understand what deepfakes are, how they work at a fundamental level, and how to apply those techniques to your own needs.
Table of Contents (15 chapters)
close
close
1
Part 1: Understanding Deepfakes
6
Part 2: Getting Hands-On with the Deepfake Process
10
Part 3: Where to Now?

Surveying Deepfakes

Understanding deepfakes begins with understanding where they came from and what they can do. In this chapter, we’ll begin to explore deepfakes and their operation. We will go through the basics of what makes a deepfake work, talking about the differences between a generative auto-encoder and a generative adversarial network (GAN). We will examine their usTo PD: es in media, education, and advertising. We’ll investigate their limitations and consider how to plan and design your deepfakes to avoid the common pitfalls. Finally, we’ll examine existing deepfake software and discuss what each kind can do.

We’ll cover this in the following sections:

  • Introducing deepfakes
  • Exploring the uses of deepfakes
  • Discovering how deepfakes work
  • Assessing the limitations of generative AI
  • Looking at existing deepfake software

Create a Note

Modal Close icon
You need to login to use this feature.
notes
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Delete Note

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete

Edit Note

Modal Close icon
Write a note (max 255 characters)
Cancel
Update Note

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY