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

Chitwan Saharia, William Chan, Saurabh Saxena et al.

2022 · arXiv (Cornell University) · 2,109 citations

We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation. Our key discovery is that generic large language models (e.g. T5), pretrained on text-only corpora, are surprisingly effective at encoding text for image synthesis: increasing the size of the language model in Imagen boosts both sample fidelity and image-text alignment much more than increa…

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