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作 者:Xuanhong WANG Cong LI Zengguo SUN Luying HUI
机构地区:[1]Xi’an University of Posts and Telecommunications,Xi’an 710121,China [2]School of Computer Science,Shaanxi Normal University,Xi’an 710119,China [3]Key Laboratory of Intelligent Computing and Service Technology for Folk Song,Ministry of Culture and Tourism,Xi’an 710119,China
出 处:《Chinese Journal of Electronics》2024年第3期584-600,共17页电子学报(英文版)
基 金:supported by the Xi’an University of Posts and Telecommunications Graduate Innovation Fund (Grant No.CXJJYL2022004);the National Natural Science Foundation of China (Grant No.62377033);the Fundamental Research Funds for the Central Universities (Grant No.GK202205036);the Xi’an Science and Technology Plan Project (Grant No.23ZDCYJSGG0010-2022)。
摘 要:With the rapid development of deep learning,generative adversarial network(GAN)has become a research hotspot in the field of computer vision.GAN has a wide range of applications in image generation.Inspired by GAN,a series of models of Chinese character font generation have been proposed in recent years.In this paper,the latest research progress of Chinese character font generation is analyzed and summarized.GAN and its development history are summarized.GAN-based methods for Chinese character font generation are clarified as well as their improvements,based on whether the specific elements of Chinese characters are considered.The public datasets used for font generation are summarized in detail,and various application scenarios of font generation are provided.The evaluation metrics of font generation are systematically summarized from both qualitative and quantitative aspects.This paper contributes to the in-depth research on Chinese character font generation and has a positive effect on the inheritance and development of Chinese culture with Chinese characters as its carrier.
关 键 词:Generative adversarial network Font generation Image-to-image translation Deep learning
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