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Painterly Image Generation Using Scene-Aware Style Transferring

机译:使用场景感知风格传输的画家图像生成

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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,我们提出了一种用于绘画图像生成的方法,它使用具有类似场景的示例绘画来反映原始工作的风格。特定画家和方法的风格通常为每个受试者采用不同的颜色和笔刷。同样,工作中的各种科目之间的连接也会影响所使用的颜色和笔刷。我们的方法采用输入图像,搜索具有类似场景的绘画的示例数据库,即受试者具有相似的位置关系和连接的绘画,并将绘画的颜色和笔触传送到目标图像的相应主题以产生绘画以完美的细节反映特定样式的图像。为了确保各种元素之间的密切联动并忠实地重现样式,我们的方法适用于Oliva等人提出的GIST方法。在执行样式传输之前搜索具有类似场景的绘画的过程。

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