GAN(Generative Adversarial Networks)을 이용한 한국어 폰트 자동 변환

초록

In this paper, a new network architecture for Korean fonts transfer procedures along with an adversarial network is proposed. The architecture we proposed consists of two sub-nets: (1)an unbalanced u-net is responsible for transferring specified fonts style to another while maintaining semantic and structure information; (2)an adversarial nets. Our model employs a compound loss function that includes a L1 loss, a constant loss and a binary GAN loss to help in generating desired target fonts. The experiments demonstrate that we proposed model can automatically generate convincing realistic-looking target fonts.