Font Generation Method based on U-net
Authors: 
Ming Liu, Xin Chen, Gang LiuAuthors Info & Claims
Ming Liu, Xin Chen, Gang LiuAuthors Info & ClaimsPages 247 - 253
Abstract
The main task of the font design is to design a suitable font according to the actual application scenario, which has extremely wide commercial application value. Generally the traditional font design requires professionals to design, with longer design time, lower work efficiency, and higher labor costs. Font design is essentially a problem of image synthesis. U-net is a deep learning network structure, which has been widely used in image synthesis, but the images synthesized by U-net have the disadvantages of low image quality and poor visual effects. In order to improve the shortcomings of U-net image synthesis effectively, this paper provides an improved U-net method for better font design. The new method is called Swish-gated residual dilated U-net (Swish-gated residual dilated U-net, SGRDU). In SGRDU, the proposed swish layer and swish-gated residual block can effectively control the information transmitted by each horizontal and vertical layer in U-net, and accelerate the network convergence. Dilated convolution is used to improve the perception of the network. Experimental results show that, compared with other residual U-net, the font synthesized by SGRDU has better visual effect and quality.
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Published In
December 2020
294 pages
ISBN:9781450388436
DOI:10.1145/3445815
Copyright © 2020 ACM.
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Association for Computing Machinery
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Published: 17 March 2021
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CSAI 2020
CSAI 2020: 2020 4th International Conference on Computer Science and Artificial Intelligence
December 11 - 13, 2020
Zhuhai, China
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