Face X-ray for More General Face Forgery Detection
- URL: http://arxiv.org/abs/1912.13458v2
- Date: Sun, 19 Apr 2020 02:22:40 GMT
- Title: Face X-ray for More General Face Forgery Detection
- Authors: Lingzhi Li, Jianmin Bao, Ting Zhang, Hao Yang, Dong Chen, Fang Wen,
Baining Guo
- Abstract summary: 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.
- Score: 45.59018645493997
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- 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.
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