ARGAN: Fast Converging GAN for Animation Style Transfer

Transformation of real images to the animated image is one of the most challenging tasks in artistic style transfer. In this paper, using a novel architecture for Generative Adversarial Networks (GANs), a faster and more accurate result for style transfer is achieved. There are three common problems regarding animation style transfer. First, the original content of an image is lost during the gene...