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一种基于卷积神经网络的油画风格迁移算法

EasyChair Preprint no. 919

6 pagesDate: April 23, 2019

Abstract

油画风格是把一张图像的油画风格信息加到任意某张图像上,并保持该图像的语义内容,产生一个新的具有观赏性的图像。本文主要介绍了一种基于卷积神经网络的图像风格算法,可以分离和重组自然图片的图像内容与风格,进而实现图片的油画化迁移。该算法可以将任意图像的内容与众多知名油画风格相结合,获得高感知质量的艺术作品。通过实验验证该算法能够实现图像内容与优化风格的深度融合,证明了该算法的有效性。

Keyphrases: Convolutional Neural Network, image stylization, oil painting

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:919,
  author = {Jiang Min and Sheng Ran and Zhu De and Duan Yunsheng and Li Fangfang and Sun Dong},
  title = {一种基于卷积神经网络的油画风格迁移算法},
  howpublished = {EasyChair Preprint no. 919},

  year = {EasyChair, 2019}}
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