LatentForensics: Towards frugal deepfake detection in the StyleGAN latent space

arXiv:2303.17222v2 Announce Type: replace
Abstract: The classification of forged videos has been a challenge for the past few years. Deepfake classifiers can now reliably predict whether or not video frames have been tampered with. However, their performance is tied to both the dataset used for training and the analyst's computational power. We propose a deepfake detection method that operates in the latent space of a state-of-the-art generative adversarial network (GAN) trained on high-quality face images. The proposed method leverages the …

abstract analyst arxiv challenge classification classifiers computational cs.cv dataset deepfake detection however performance space training type video videos