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, a class of generative models, have garnered immense interest
lately in various deep-learning problems. A diffusion probabilistic model defines a forward …

The recent success of text-to-image synthesis has taken the world by storm and captured the
general public's imagination. From a technical standpoint, it also marked a drastic change in …

We present SDXL, a latent diffusion model for text-to-image synthesis. Compared to
previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone …

With the advance of text-to-image (T2I) diffusion models (eg, Stable Diffusion) and
corresponding personalization techniques such as DreamBooth and LoRA, everyone can …

Automatic text-to-3D generation that combines Score Distillation Sampling (SDS) with the
optimization of volume rendering has achieved remarkable progress in synthesizing realistic …

Recently, diffusion models have achieved remarkable success in text-to-image generation,
enabling the creation of high-quality images from text prompts and various conditions …

We present an approach to reconstruct humans and track them over time. At the core of our
approach, we propose a fully" transformerized" version of a network for human mesh …

The recent wave of large-scale text-to-image diffusion models has dramatically increased
our text-based image generation abilities. These models can generate realistic images for a …

Currently, applying diffusion models in pixel space of high resolution images is difficult.
Instead, existing approaches focus on diffusion in lower dimensional spaces (latent …