Towards a General Framework for Artistic Style Transfer

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10783)


In recent times, artificial intelligence has become more sophisticated when it comes to the creation of fine arts. Especially in the area of painting, artificial methods reached a new level of maturity in the process of replicating perceptual quality. These systems are able to separate style and content of given images, enabling them to recombine and mutate the facets to create novel content. This work defines a general framework for conducting artistic style transfer. This allows recombination and structured modification of state of the art algorithms for further investigation and profiling of artistic style transfer.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Volkswagen AGWolfsburgGermany
  2. 2.Faculty of Computer ScienceUniversity of MagdeburgMagdeburgGermany

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