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Despite the rapid progress in style transfer, existing approaches using feed-forward generative network for multi-style or arbitrary-style transfer are usually compromised of image quality and model flexibility.
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C. Feichtenhofer, A. Pinz, and A. Zisserman · 2016
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L. A. Gatys, A. S. Ecker, and M. Bethge · 2016
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L. A. Gatys, A. S. Ecker, M. Bethge, A. Hertzmann, and E. Shechtman · 2016
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X. Shen, A. Hertzmann, J. Jia, S. Paris, B. Price, E. Shechtman, and I. Sachs · 2016
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Texture networks: Feed-forward synthesis of textures and stylized images
D. Ulyanov, V. Lebedev, A. Vedaldi, and V. Lempitsky · 2016
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H. Zhang, T. Xu, H. Li, S. Zhang, X. Huang, X. Wang, and D. Metaxas · 2016
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Stylebank: An explicit representation for neural image style transfer
D. Chen, L. Yuan, J. Liao, N. Yu, and G. Hua · 2017
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