使用 U-GAT-IT 实现人脸和瓦扬人形之间的图像翻译

Ciara Nurdenara, Wikky Fawwaz Al Maki
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引用次数: 0

摘要

瓦扬人妖表演是印尼传统文化之一。由于在表演之前化妆和寻找合适的服装都需要时间,因此瓦扬人妖表演者需要花费大约一个小时的时间才能成为一名合格的瓦扬人妖。要解决这个问题,可以开发一个基于计算机的模拟工具,分别为瓦扬人妖表演者的脸部和头部化妆并穿上传统服装。这项任务可以通过图像翻译来完成。因此,可以将人的图像转换成瓦扬人的图像。本研究旨在使用 U-GAT-IT 将人脸通过添加妆容和配饰翻译成瓦扬人形,其非配对数据集包括 1216 个数据训练和 240 个数据测试。这项研究面临的挑战是如何保持输入图像中的图像背景和面部特征成分。这项研究采用了核截取距离(KID)、弗雷谢特截取距离(FID)和截取分数(IS)等定量测试方法来评估生成器输出图像的质量。实验结果表明,根据 IS、FID 和 KID 的值,U-GAT-IT 产生的结果比 DCLGAN 更好。U-GAT-IT 的 IS、FID 和 KID 值分别为 2.414、0.924 和 4.357。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image translation between human face and wayang orang using U-GAT-IT
Wayang orang performance is one of the Indonesian traditional cultures. The wayang orang players took about an hour to become a proper wayang orang since it takes time to have makeup and to find the appropriate costume before the performance is held. This problem can be solved by developing a computer-based simulation on applying makeup and traditional costume to the face and head of the wayang orang player, respectively. This task can be completed by using image translation. Therefore, people's images can be transformed into wayang orang images. This study aims to translate human faces into wayang orang by adding makeup and accessories using the U-GAT-IT with an unpaired dataset consisting of 1216 data trains and 240 data tests. The challenge of this research is to maintain the image background and the facial identity component in the input image. This research employs quantitative testing employ Kernel Inception Distance (KID), Frèchet Inception Distance (FID), and Inception Score (IS) to evaluate the quality of the output image obtained from the generator. The experimental results show that U-GAT-IT produces a better result than DCLGAN does according to the value of IS, FID, and KID. The IS, FID, and KID obtained by implementing U-GAT-IT are 2.414, 0.924, and 4.357, respectively.
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