KREUZADER — prostheticknowledge: DeepWarp Research from...

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Research from Skolkovo Institute of Science and Technology uses Neural Networks to easily alter the position of gaze of a photographic subject:

In this work, we consider the task of generating highly-realistic images of a given face with a redirected gaze. We treat this problem as a specific instance of conditional image generation, and suggest a new deep architecture that can handle this task very well as revealed by numerical comparison with prior art and a user study. Our deep architecture performs coarse-to-fine warping with an additional intensity correction of individual pixels. All these operations are performed in a feed-forward manner, and the parameters associated with different operations are learned jointly in the end-to-end fashion. After learning, the resulting neural network can synthesize images with manipulated gaze, while the redirection angle can be selected arbitrarily from a certain range and provided as an input to the network.         

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Source: yaroslav.ganin.net
deep learning machine learning neural networking

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