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Painterly Image Generation Using Scene-Aware Style Transferring

机译:使用场景感知样式传输的绘画图像生成

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In this paper, we propose a method for painterly image generation that uses an example painting with a similar scene to reflect the style of an original work in great detail. The styles of specific painters and methods often employ different colors and brushwork for each individual subject. Likewise, the connections between various subjects in a work also affect the colors and brushwork used. Our method takes input images, searches an example database for paintings with similar scenes, i.e., paintings in which the subjects have similar positional relationships and connections, and transfers the color and brushwork of the paintings to the corresponding subjects of the target images to generate painterly images that reflect specific styles in great detail. In order to ensure close linkage between various elements and to reproduce styles faithfully, our method applies the GIST approach proposed by Oliva et al. to the process of searching for paintings with similar scenes before performing style transfers.
机译:在本文中,我们提出了一种绘画风格的图像生成方法,该方法使用具有相似场景的示例绘画来详细反映原始作品的风格。特定画家的风格和方法通常为每个主题使用不同的颜色和笔法。同样,作品中各个主题之间的联系也会影响所使用的颜色和笔法。我们的方法采用输入图像,在示例数据库中搜索具有相似场景的绘画(即,主题之间具有相似位置关系和关联的绘画),并将绘画的颜色和笔触转移到目标图像的相应主题以产生绘画效果反映特定样式的图像非常详细。为了确保各种元素之间的紧密联系并忠实再现样式,我们的方法采用了Oliva等人提出的GIST方法。在执行样式转换之前搜索具有相似场景的绘画的过程。

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