Face X-Ray for More General Face Forgery Detection
Abstract
In this paper we propose a novel image representation called face X-ray for detecting forgery in face images. The face X-ray of an input face image is a greyscale image that reveals whether the input image can be decomposed into the blending of two images from different sources. It does so by showing the blending boundary for a forged image and the absence of blending for a real image. We observe that most existing face manipulation methods share a common step: blending the altered face into an existing background image. For this reason, face X-ray provides an effective way for detecting forgery generated by most existing face manipulation algorithms. Face X-ray is general in the sense that it only assumes the existence of a blending step and does not rely on any knowledge of the artifacts associated with a specific face manipulation technique. Indeed, the algorithm for computing face X-ray can be trained without fake images generated by any of the state-of-the-art face manipulation methods. Extensive experiments show that face X-ray remains effective when applied to forgery generated by unseen face manipulation techniques, while most existing face forgery detection or deepfake detection algorithms experience a significant performance drop.
Read the paper
Related studies
- The potential and limitations of neutrons, electrons and X-rays for atomic resolution microscopy of unstained biological molecules
- X-ray-Computed Tomography Contrast Agents
- Reactivity of Surface Species in Heterogeneous Catalysts Probed by In Situ X-ray Absorption Techniques
- Single-crystal X-ray diffraction studies on structural transformations of porous coordination polymers
- Investigation of solid/vapor interfaces using ambient pressure X-ray photoelectron spectroscopy
- Resonant X-Ray Scattering Studies of Charge Order in Cuprates
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.