Research on transfer effect of ink style based on ChipGAN

Nan Liu; Hongjuan Wang; Yahui Ding

doi:10.1117/12.2679126

25 May 2023 Research on transfer effect of ink style based on ChipGAN

Nan Liu, Hongjuan Wang, Yahui Ding

Proceedings Volume 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023); 1271215 (2023) https://doi.org/10.1117/12.2679126
Event: International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 2023, Huzhou, China

Abstract

Generated Adversarial Network has been widely used in the field of image style transfer. Among them, ChipGAN is specifically aimed at the study of Chinese ink painting style transfer. In previous studies, it has demonstrated its excellent transfer effect at the visual level. In this paper, using CycleGAN and ChipGAN model, we adjust the parameters by controlling the variable method, quantitatively compare the image style transfer of the two models on the basis of visual effect comparison, and prove the effectiveness of ChipGAN in ink style transfer and the complexity in training.

Citation Download Citation

Nan Liu, Hongjuan Wang, and Yahui Ding "Research on transfer effect of ink style based on ChipGAN", Proc. SPIE 12712, International Conference on Cloud Computing, Performance Computing, and Deep Learning (CCPCDL 2023), 1271215 (25 May 2023); https://doi.org/10.1117/12.2679126

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