Adversarial colorization of icons based on counter and color conditions

Tsai Ho Sun, Chien Hsun Lai, Sai-Keung Wong, Yu-Shuen Wang

研究成果: Conference contribution同行評審

16 引文 斯高帕斯(Scopus)

摘要

We present a system to help designers create icons that are widely used in banners, signboards, billboards, homepages, and mobile apps. Designers are tasked with drawing contours, whereas our system colorizes contours in different styles. This goal is achieved by training a dual conditional generative adversarial network (GAN) on our collected icon dataset. One condition requires the generated image and the drawn contour to possess a similar contour, while the other anticipates the image and the referenced icon to be similar in color style. Accordingly, the generator takes a contour image and a man-made icon image to colorize the contour, and then the discriminators determine whether the result fulfills the two conditions. The trained network is able to colorize icons demanded by designers and greatly reduces their workload. For the evaluation, we compared our dual conditional GAN to several state-of-the-art techniques. Experiment results demonstrate that our network is over the previous networks. Finally, we will provide the source code, icon dataset, and trained network for public use.

原文English
主出版物標題MM 2019 - Proceedings of the 27th ACM International Conference on Multimedia
發行者Association for Computing Machinery, Inc
頁面683-691
頁數9
ISBN(電子)9781450368896
DOIs
出版狀態Published - 21 10月 2019
事件27th ACM International Conference on Multimedia, MM 2019 - Nice, France
持續時間: 21 10月 201925 10月 2019

出版系列

名字MM 2019 - Proceedings of the 27th ACM International Conference on Multimedia

Conference

Conference27th ACM International Conference on Multimedia, MM 2019
國家/地區France
城市Nice
期間21/10/1925/10/19

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