Aesthetic Style Transfer through Text-to-image Synthesis and Image-to-image Translation

Megumi Kotera, Ren Togo, Takahiro Ogawa, M. Haseyama
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引用次数: 2

Abstract

This paper presents a style transfer method combining generative adversarial networks and style transfer networks. In the previous style transfer methods, transformation from one image to another has been proposed. On the other hand, our method enables style transfer from a text to an image. This will be helpful when there are no images that represent the desired style. Experimental results show the effectiveness of our method.
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从文本到图像的综合和图像到图像的翻译看审美风格的转移
提出了一种结合生成对抗网络和风格迁移网络的风格迁移方法。在以前的风格转移方法中,已经提出了从一个图像到另一个图像的转换。另一方面,我们的方法可以将样式从文本转移到图像。当没有图像代表所需的样式时,这将是有用的。实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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