Autoencoders and Image Manipulation

In previous chapters, we learned about classifying images, detecting objects in an image, and segmenting the pixels corresponding to objects in images. In this chapter, we will learn about representing an image in a lower dimension using autoencoders and then leveraging the lower-dimensional representation of an image to generate new images by using variational autoencoders. Learning how to represent images in a lower number of dimensions helps us manipulate (modify) the images to a considerable degree. We will also learn about generating novel images that are based on the content and style of two different images. We will then explore how to modify images in such a way that the image is visually unaltered; however, the class corresponding to the image is changed from one to another when the image is passed through an image classification model. Finally, we will learn about generating deepfakes: given a source image of person A, we generate a target...