Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …

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 …

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

Abstract We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that
efficiently samples large-scale foundational image diffusion models in just 1–4 steps while …

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

Denoising diffusion models (DDMs) have shown promising results in 3D point cloud
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …

Diffusion models have significantly advanced the fields of image, audio, and video
generation, but they depend on an iterative sampling process that causes slow generation …

Diffusion probabilistic models (DPMs) have demonstrated a very promising ability in high-
resolution image synthesis. However, sampling from a pre-trained DPM is time-consuming …

Diffusion probabilistic models (DPMs) are emerging powerful generative models. Despite
their high-quality generation performance, DPMs still suffer from their slow sampling as they …

Diffusion probabilistic models (DPMs) have achieved impressive success in high-resolution
image synthesis, especially in recent large-scale text-to-image generation applications. An …