High-level workflow
Fake content generation is a complex task consisting of a number of components and steps that help in generating believable content. While this space is seeing quite a lot of research and hacks that improve the overall results, the setup can largely be explained using a few common building blocks. In this section, we will discuss a common high-level flow that describes how a deepfake setup uses data to train and generate fake content. We will also touch upon a few common architectures used in a number of works as basic building blocks.
As discussed earlier, a deepfake setup requires a source identity (xs) which drives the target identity (xt) to generate fake content (xg). To understand the high-level flow, we will continue with this notation, along with the concepts related to the key feature set discussed in the previous section. The steps are as follows:
- Input processing
- The input image (xs or xt) is processed using a face...
