A Comic Head Images Generation Algorithm Based on Improved Deep Convolutional Generative Adversarial Networks

In this paper, a generative adversarial network is applied to the generation of comic head images. Aiming at solving the problems of poor image quality, single generated samples, and slow model convergence in the generation process, a caricature head image generation algorithm based on improved deep convolutional generative adversarial network (DCGAN) is proposed. By adjusting the network structure, the ability to generate models and discriminate models is better balanced. The quality of the generated samples is enhanced, meanwhile, the convergence speed of the entire network is also improved. The experimental results show that the algorithm has a good effect on the generation of comic head images.