In this project, we first attempted to reproduce and explore the GigaGAN model, uncovering its remarkable text-to-image processing techniques. Subsequently, we shifted our focus to the MinImagen2 architecture, an efficient text-to-image generation model capable of producing high-quality images. Our goal is to experiment with these two models, comparing their strengths and weaknesses, and ultimately share our findings and experiences in the world of image generation.
