Detecting fake images
In the previous section, we looked at how deepfake images and videos can be generated. As the technology to do so is accessible to everyone, we also discussed the impact that this can have at multiple levels. Now, we will look at how fake images can be detected. This is an important problem to solve and has far-reaching impacts on social media and the internet in general.
A naive model to detect fake images
We know that machine learning has driven significant progress in the domain of image processing. Convolutional neural networks (CNNs) have surpassed prior image detectors and achieved accuracy even greater than that of humans. As a first step toward detecting deepfake images, we will treat the task as a simple binary classification and use standard deep learning image classification approaches.
The dataset
There are several publicly available datasets for deepfake detection. We will use the 140k Real and Fake Faces Dataset. This dataset is freely...
