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.
