Two-Stream Neural Networks for Tampered Face Detection

computer vision and pattern recognition, 2017.

Cited by: 90|Bibtex|Views57|DOI:https://doi.org/10.1109/CVPRW.2017.229
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet network to leverage features capturing local noise residuals and camera characteristics as a second stream. In addition, we use two different online face swaping ap...More

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