Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding

This paper introduces Imagen, a text-to-image diffusion model that achieves a high degree of photorealism and deep language understanding. By scaling the size of the language model while keeping the image diffusion model fixed, Imagen attains state-of-the-art performance on text-to-image generation benchmarks, demonstrating the importance of large language models for this task. The model leverages diffusion techniques to generate images from text descriptions, resulting in impressive visual fidelity and coherence with the input text.