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arXiv · 1701.04851

Synthesizing Normalized Faces from Facial Identity Features

Forrester Cole·David Belanger·Dilip Krishnan·Aaron Sarna·Inbar Mosseri·William T. Freeman
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Abstract

We present a method for synthesizing a frontal, neutral-expression image of a person's face given an input face photograph. This is achieved by learning to generate facial landmarks and textures from features extracted from a facial-recognition network. Unlike previous approaches, our encoding feature vector is largely invariant to lighting, pose, and facial expression. Exploiting this invariance, we train our decoder network using only frontal, neutral-expression photographs. Since these photographs are well aligned, we can decompose them into a sparse set of landmark points and aligned texture maps. The decoder then predicts landmarks and textures independently and combines them using a differentiable image warping operation. The resulting images can be used for a number of applications, such as analyzing facial attributes, exposure and white balance adjustment, or creating a 3-D avatar.

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Forrester Cole, David Belanger, Dilip Krishnan, Aaron Sarna, Inbar Mosseri, William T. Freeman. 2017-01-17. Synthesizing Normalized Faces from Facial Identity Features. https://arxiv.org/abs/1701.04851

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