Fast Face-swap Using Convolutional Neural Networks

ICCV 2017 Iryna KorshunovaWenzhe ShiJoni DambreLucas Theis

We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression, and lighting. To perform this mapping, we use convolutional neural networks trained to capture the appearance of the target identity from an unstructured collection of his/her photographs.This approach is enabled by framing the face swapping problem in terms of style transfer, where the goal is to render an image in the style of another one... (read more)

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