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 …

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 …

It has been recognized that the data generated by the denoising diffusion probabilistic
model (DDPM) improves adversarial training. After two years of rapid development in …

Denoising diffusion models hold great promise for generating diverse and realistic human
motions. However, existing motion diffusion models largely disregard the laws of physics in …

We consider the problem of inferring high-dimensional data $ x $ in a model that consists of
a prior $ p (x) $ and an auxiliary differentiable constraint $ c (x, y) $ on $ x $ given some …

Denoising diffusion models (DDMs) have emerged as a powerful class of generative
models. A forward diffusion process slowly perturbs the data, while a deep model learns to …

Diffusion models have found widespread adoption in various areas. However, their
sampling process is slow because it requires hundreds to thousands of network evaluations …

Warning: this paper contains data, prompts, and model outputs that are offensive in nature.
Recently, there has been a surge of interest in integrating vision into Large Language …