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  Image Style Transfer Using Convolutional Neural Networks

Gatys, L., Ecker, A., & Bethge, M. (2016). Image Style Transfer Using Convolutional Neural Networks. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016) (pp. 2414-2423). Piscataway, NJ, USA: IEEE.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-7A92-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-7A93-1
Genre: Conference Paper

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Gatys, LA, Author
Ecker, AS1, 2, 3, Author              
Bethge, M1, 2, Author              
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

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 Abstract: Rendering the semantic content of an image in different styles is a difficult image processing task. Arguably, a major limiting factor for previous approaches has been the lack of image representations that explicitly represent semantic information and, thus, allow to separate image content from style. Here we use image representations derived from Convolutional Neural Networks optimised for object recognition, which make high level image information explicit. We introduce A Neural Algorithm of Artistic Style that can separate and recombine the image content and style of natural images. The algorithm allows us to produce new images of high perceptual quality that combine the content of an arbitrary photograph with the appearance of numerous well-known artworks. Our results provide new insights into the deep image representations learned by Convolutional Neural Networks and demonstrate their potential for high level image synthesis and manipulation.

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 Dates: 2016-06
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/CVPR.2016.265
BibTex Citekey: GatysEB2016_2
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Title: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016)
Place of Event: Las Vegas, NV, USA
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Title: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2414 - 2423 Identifier: ISBN: 978-146738851-1