Face X-Ray for More General Face Forgery Detection

@article{Li2020FaceXF,
  title={Face X-Ray for More General Face Forgery Detection},
  author={Lingzhi Li and Jianmin Bao and Ting Zhang and Hao Yang and Dong Chen and Fang Wen and B. Guo},
  journal={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2020},
  pages={5000-5009}
}
  • Lingzhi Li, Jianmin Bao, +4 authors B. Guo
  • Published 2020
  • Computer Science
  • 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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… Expand
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