---

ZotWeb	article-journal
Src Url	Gatys, Ecker, Bethge (2015)

In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown and there exists no artificial system with similar capabilities. However, 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 separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic images. Moreover, in light of the striking similarities between performance-optimised artificial neural networks and biological vision, our work offers a path forward to an algorithmic understanding of how humans create and perceive artistic imagery.

---

Citer:(Gatys et al., 2015)

FTag: Gatys-et-al-2015

APA7: Gatys, L. A., Ecker, A. S., & Bethge, M. (2015). A Neural Algorithm of Artistic Style. _ArXiv:1508.06576 [Cs, q-Bio] _. http://arxiv.org/abs/1508.06576

https://github.com/jgwill/tst-wiki-ma-dist/wiki/Gatys-et-al-2015

In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image
NSTContext | ref2012031450

The system uses neural representations to separate and recombine content and style of arbitrary images, providing a neural algorithm for the creation of artistic image

[...] an algorithmic understanding of how humans create and perceive artistic imagery.  (Gatys et al., 2015)
NSTGoal

The class of Deep Neural Networks that are most powerful in image processing tasks are called Convolutional Neural Network

Convolutional Neural Networks consist of layers of small computational units that process visual information hierarchically [...]   (Gatys et al., 2015)

[...] composing a complex interplay between the content and style of an image

---

ref2012031450

---

---