Training StyleGAN3 with Vision-Aided GAN on Runpod

StyleGAN3 represents the latest advancement in generative adversarial networks (GANs), capable of producing remarkably realistic high-resolution images without the artifacts that plagued previous GAN iterations. This improvement is achieved through a novel upsampling method that prevents aliasing, enabling applications such as realistic face generation for video games and movies. Additionally, StyleGAN3 introduces a faster training process called "progressive growing," allowing it to start with lower resolution images and gradually increase detail, significantly reducing training time compared to previous methods. An experiment using StyleGAN3 and a vision-aided GAN on the danbooru2019 dataset demonstrated the model's potential, although some artifacts were still observed. Despite these challenges, StyleGAN3 is poised to revolutionize image generation, promising new applications and enhanced quality in the field.