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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“The machine’s already talking. You’re too old, older than 40. You can’t hear a sound above 15 kilohertz. But I can… with the ear I’ve got left. My friend’s been beeping morse code at that frequency since you brought your phone in here. She’s been talking to me the whole time, telling me about you. You’re scared of me, even with all these guards watching. By the way, that one has a bum knee. You’re so scared of me that you hid a knife in your pocket. I couldn’t reach it till you got close enough to cut me.”