DepthFake: A Depth-Based Strategy for Detecting Deepfake Videos

Luca Maiano, Lorenzo Papa, Ketbjano Vocaj, Irene Amerini

Abstract: Fake content has grown at an incredible rate over the past few years. The spread of social media and online platforms makes their dissemination on a large scale increasingly accessible by malicious actors. In parallel, due to the growing diffusion of fake image generation methods, many Deep Learning-based detection techniques have been proposed. Most of those methods rely on extracting salient features from RGB images to detect through a binary classifier if the image is fake or real.