In fine art, especially painting, humans havemastered the skill to create unique visual experiences through composing a complex interplay between the con- tent and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. How- ever, in other key areas of visual perception such as object and face recognition near-human performance was recently demonstrated by a class of biologically inspired vision models called Deep Neural Networks. Here we introduce an artificial system based on a Deep Neural Network that creates artistic images of high perceptual quality. The system uses neural representations to sepa- rate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the strik- ing similarities between performance-optimised artificial neural networks and biological vision,our work offers a path forward to an algorithmic under- standing of how humans create and perceive artistic imagery.

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