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ClothGAN: generation of fashionable Dunhuang clothes using generative adversarial networks

机译：皮革：使用生成对抗网络的时尚敦煌衣服的生成

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摘要

Clothing is one of the symbols of human civilisation. Clothing design is an art form that combines practicality and artistry. The Dunhuang clothes culture has a long history which represents ancient Chinese aesthetics. Artificial intelligence (AI) technology has been recently applied to multiple areas, which is also drawing increasing attention in fashion. However, little research has been done on the usage of AI for the creation of clothing, especially in traditional culture. It is challenging that the exploration of computer science and Dunhuang clothing design, which is a cross-history interaction between AI and Chinese classical culture. In this paper, we propose ClothGAN, which is an innovative framework for "designing" new patterns and styles of clothes based on generative adversarial network (GAN) and style transfer algorithm. Besides, we built the Dunhuang clothes dataset and conducted experiments to generate new patterns and styles of clothes with Dunhuang elements. We evaluated these clothing works generated from different models by computing inception score (IS), human prefer score (HPS) and generated score (IS and HPS). The results show that our framework outperformed others in these designing works.
机译：服装是人类文明的象征之一。服装设计是一种结合实用性和艺术性的艺术形式。敦煌的衣服文化具有悠久的历史，代表中国古代美学。最近应用于多个区域的人工智能（AI）技术，这也吸引了时尚越来越多的关注。然而，对AI的使用进行了很少的研究，以创造衣服，特别是在传统文化中。计算机科学与敦煌服装设计探索是挑战，这是AI和中国古典文化之间的跨历史互动。在本文中，我们提出了一种基于生成对冲网络（GaN）和风格转移算法的“设计”新图案和衣服的创新框架。此外，我们建造了敦煌服装数据集，并进行了实验，以产生敦煌元素的新图案和款式。我们评估了通过计算成立得分（IS），人类更喜欢得分（HPS）和生成的分数（是和HPS）来评估这些服装工作。结果表明，我们的框架在这​​些设计作品中表明了其他人。

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