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Painting style transfer with deep neural networks

Aljoša Rakita (2018) Painting style transfer with deep neural networks. EngD thesis.

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    What are deep neural networks and how they work is explained first in this diploma thesis. Next, we describe what is a painting style and what determines the style. With deep neural networks one can transfer the painting style from a selected source image to another target image. We demonstrate style transfer by making ``fake’’ pictures using paintings of Slovene impressionist painters. At the end we made a web survey to find out, if randomly selected people could distinguish such ``fake’’ pictures from the real painting of slovenian impressionists.

    Item Type: Thesis (EngD thesis)
    Keywords: style transfer, deep neural network, analysis
    Number of Pages: 69
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    prof. dr. Franc Solina71Mentor
    viš. pred. dr. Borut Batagelj298Comentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537952963)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 4241
    Date Deposited: 18 Sep 2018 17:09
    Last Modified: 04 Oct 2018 13:03
    URI: http://eprints.fri.uni-lj.si/id/eprint/4241

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