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	Hierarchical oil painting stylization with limited reference via sparse representation
	Yang, Saboya ; Liu, Jiaying ; Yang, Shuai ; Xia, Sifeng ; Guo, Zongming
	2015
英文摘要	Traditional image stylization is enforced by learning the mappings with an external paired training set. But in practice, people usually encounter a specific stylish image and want to transfer its style to their own pictures without the external dataset. Thus, we propose a hierarchical stylization model with limited reference particularly for oil paintings. First, the edge patch based dictionary is trained to build connections between images and limited reference, then reconstruct the structure layer. Due to the highly structured property of saliency regions, the saliency mask is extracted to integrate the structure layer and the texture layer with different weights. Hence, the advantages of both sparse representation based methods and example based methods are integrated. Moreover, the color layer and the surface layer are considered to make the output more consistent with the artist's individual oil painting style. Subjective results demonstrate the proposed method produces desirable results with state-of-art methods while keeping consistent with the artist's oil painting style. ? 2015 IEEE.; EI
语种	英语
出处	17th IEEE International Workshop on Multimedia Signal Processing, MMSP 2015
DOI标识	10.1109/MMSP.2015.7340850
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/436460]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	Yang, Saboya,Liu, Jiaying,Yang, Shuai,et al. Hierarchical oil painting stylization with limited reference via sparse representation. 2015-01-01.

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