To assess text-to-image models in greater depth, we introduce DrawBench, a comprehensive and challenging benchmark for text-to-image models. With DrawBench, we compare Imagen with recent methods including VQ-GAN+CLIP, Latent Diffusion Models, and DALL-E 2, and find that human raters prefer Imagen over other models in side-by-side comparisons ...

Editing Flow. The input to Imagen Editor is a masked image and a text prompt, the output is an image with the unmasked areas untouched and the masked areas filled-in.The edits are faithful to input text prompts, while consistent with input images:

Imagen: Text-to-Image Diffusion Models

Imagen Video generates high resolution videos with Cascaded Diffusion Models.The first step is to take an input text prompt and encode it into textual embeddings with a T5 text encoder. A base Video Diffusion Model then generates a 16 frame video at 40×24 resolution and 3 frames per second; this is then followed by multiple Temporal Super-Resolution (TSR) and Spatial Super …