Tensor-Based Deepfake Detection in Scaled and Compressed Images
Sara Concas, Gianpaolo Perelli, Gian Luca Marcialis, Giovanni Puglisi
Abstract
When deepfakes are widespread on chatting platforms, they are expected to be subject to heavy resizing and compressing steps. In this paper, we present a tensor-based representation of compressed and resized images. Tensor embeds DCT features computed on multi-scaled and multi-compressed versions of the input facial image. Moreover, a custom deep-architecture is designed and trained on the proposed representation. Experimental results show its pros and cons with respect to state-of-the-art methods.
Topics & Concepts
Computer scienceRepresentation (politics)Tensor (intrinsic definition)Artificial intelligenceImage (mathematics)Discrete cosine transformComputer visionArchitecturePattern recognition (psychology)MathematicsGeometryVisual artsPoliticsLawPolitical scienceArtGenerative Adversarial Networks and Image SynthesisAdvanced Image Processing TechniquesDigital Media Forensic Detection