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 …

Abstract Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding
excessive compute demands by training a diffusion model in a compressed lower …

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 …

We propose a method for editing images from human instructions: given an input image and
a written instruction that tells the model what to do, our model follows these instructions to …

Large-scale text-to-image generative models have shown their remarkable ability to
synthesize diverse, high-quality images. However, directly applying these models for real …

Large-scale text-to-image generative models have been a revolutionary breakthrough in the
evolution of generative AI, synthesizing diverse images with highly complex visual concepts …

We present a diffusion-based model for 3D-aware generative novel view synthesis from as
few as a single input image. Our model samples from the distribution of possible renderings …

Text-conditioned image editing has recently attracted considerable interest. However, most
methods are currently limited to one of the following: specific editing types (eg, object …

Large-scale diffusion-based generative models have led to breakthroughs in text-
conditioned high-resolution image synthesis. Starting from random noise, such text-to-image …