Automatic Image Generation of Peking Opera Face using StyleGAN2

Abstract

Image generation technology, which is often used in various applications of intelligent image generation, can learn the feature distribution of real images and sample from the distribution to obtain the generated images with high fidelity. This paper focuses on the feature extraction and intelligent generation techniques of Peking opera face with Chinese cultural characteristics. Based on the creation of a Peking opera face dataset, this paper compares the impact of different variants of a Style-based generator architecture for Generative Adversarial Networks (StyleGAN2) and different sizes of datasets on the quality of face generation. The experimental results verify that the synthetic images generated by StyleGAN2 with the addition of the Adaptive Discriminator Augmentation (ADA) module are visually better and have good local randomness when the dataset is small and unbalanced in distribution.