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Chinese flower-bird character generation based on pencil drawings or brush drawings

机译:基于铅笔画或毛笔画的中国花鸟字符生成

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摘要

Chinese flower-bird characters are gems of traditional Chinese art. It is an artistic font and the strokes of the characters are designed as beautiful patterns of flowers, birds, etc. The generation of such characters requires painters' great efforts. Imagine that if we only need to sketch the outline of the ideal flower-bird characters using a pencil, and then we can quickly obtain these artistic characters, which will be of great significance in promoting their development, allowing more people to appreciate and even create this art by computer. Recently, with the development of deep learning and the invention of generative adversarial networks (GANs), some studies on font generation have made new progress. However, there is no research on the generation of flower-bird characters. We provide a solution by designing a GAN-based architecture to generate flower-bird characters. More specifically, a generator inspired by U-Net translates pencil drawings or brush drawings to flower-bird characters, and a patch-level discriminator distinguishes whether the received image is real. In addition to adversarial loss, a valid loss term called structural similarity loss is designed to further drive the network to generate satisfactory images. The quantitative analysis and user perceptual validation show the effectiveness of our method. (C) 2019 SPIE and IS&T
机译:中国花鸟人物是中国传统艺术的瑰宝。它是一种艺术字体,字符的笔触设计为花朵,鸟类等的美丽图案。要生成此类字符,需要画家付出很大的努力。想象一下,如果只需要用铅笔勾勒出理想的花鸟人物的轮廓,然后我们就能迅速获得这些艺术人物,这对于促进它们的发展具有重要意义,使更多的人欣赏甚至创造这种艺术是通过计算机实现的。近年来,随着深度学习的发展和生成对抗网络(GAN)的出现,一些关于字体生成的研究取得了新的进展。然而,关于花鸟角色的产生尚无研究。我们通过设计基于GAN的体系结构以生成花鸟字符来提供解决方案。更具体地说,受U-Net启发的生成器将铅笔绘图或画笔绘图转换为花鸟字符,而色块级鉴别器则区分接收到的图像是否真实。除对抗性损失外,还设计了一个有效的损失术语,称为结构相似性损失,以进一步驱动网络生成满意的图像。定量分析和用户感知验证表明了我们方法的有效性。 (C)2019 SPIE和IS&T

著录项

  • 来源
    《Journal of electronic imaging》 |2019年第3期|033029.1-033029.14|共14页
  • 作者单位

    South China Univ Technol, Sch Comp Sci & Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou, Guangdong, Peoples R China;

    South China Univ Technol, Sch Comp Sci & Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou, Guangdong, Peoples R China;

    South China Univ Technol, Sch Comp Sci & Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou, Guangdong, Peoples R China;

    South China Univ Technol, Sch Comp Sci & Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou, Guangdong, Peoples R China;

    South China Univ Technol, Sch Comp Sci & Engn, Guangzhou Higher Educ Mega Ctr, Guangzhou, Guangdong, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    deep learning; generative adversarial network; font generation; Chinese flower-bird character;

    机译:深度学习;生成对抗网络;字体生成;中国花鸟角色;
  • 入库时间 2022-08-18 04:20:25

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