Book Image

Exploring Deepfakes

By : Bryan Lyon, Matt Tora
Book Image

Exploring Deepfakes

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)
1
Part 1: Understanding Deepfakes
6
Part 2: Getting Hands-On with the Deepfake Process
10
Part 3: Where to Now?

Summary

The technology of deepfakes is not itself anything new or unique. These techniques existed in various forms long before they were applied to face-swapping, but deepfakes have caught public attention in a way that other AI techniques have never really been able to. There is something very visceral about seeing a face where it doesn’t belong, seeing an actor in a role you know that they didn’t play, or seeing your own face doing something you’ve never done.

While the techniques that make up deepfakes have all existed previously on their own, together, they provide completely new possibilities. There are numerous use cases that deepfakes can be applied to, from stunt-double replacement to advertising. The technology is here, and its use will only grow as more and more industries find ways to use it.

There are still limits to the capabilities of generative AI. Knowing what a deepfake cannot do is as important as knowing what it can do. Especially regarding data, knowing how to work around those limitations is key to a quality result.

We’ve given an overview of deepfakes, covering what they are, what they can be used for, how they work, their limitations, and the existing software you can use to make them. In the next chapter, we’ll cover the potential dangers of deepfakes and talk about the ethical questions that the technology brings with it.