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It this paper we revisit the fast stylization method introduced in Ulyanov et. al. (2016). We show how a small change in the stylization architecture results in a significant qualitative improvement in the generated images. The change is limited to swapping batch normalization with instance normalization, and to apply the latter both at training and testing times. The resulting method can be used to train high-performance architectures for real-time image generation. The code will is made available on github at https: //github. com/DmitryUlyanov/textureₙets. Full paper can be found at arXiv: 1701. 02096.
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Dmitry Ulyanov
Skolkovo Institute of Science and Technology
Andrea Vedaldi
University of California, Los Angeles
Victor Lempitsky
Skolkovo Institute of Science and Technology
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Ulyanov et al. (Wed,) studied this question.
synapsesocial.com/papers/69dcafae89c4deb67d359597 — DOI: https://doi.org/10.48550/arxiv.1607.08022
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