Denoising diffusion models represent a recent emerging topic in computer vision,
demonstrating remarkable results in the area of generative modeling. A diffusion model is a …

Diffusion models have emerged as a powerful new family of deep generative models with
record-breaking performance in many applications, including image synthesis, video …

We present ControlNet, a neural network architecture to add spatial conditioning controls to
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …

A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule
on the learned gradients, and back-propagate the score of a diffusion model through the …

We present Stable Video Diffusion-a latent video diffusion model for high-resolution, state-of-
the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained …

We present Imagen Video, a text-conditional video generation system based on a cascade
of video diffusion models. Given a text prompt, Imagen Video generates high definition …

We present Muse, a text-to-image Transformer model that achieves state-of-the-art image
generation performance while being significantly more efficient than diffusion or …

Large-scale generative models are capable of producing high-quality images from detailed
prompts. However, many aspects of an image are difficult or impossible to convey through …

Classifier-free guided diffusion models have recently been shown to be highly effective at
high-resolution image generation, and they have been widely used in large-scale diffusion …

During the last two years there has been a plethora of large generative models such as
ChatGPT or Stable Diffusion that have been published. Concretely, these models are able to …