We propose DiffusionDet, a new framework that formulates object detection as a denoising
diffusion process from noisy boxes to object boxes. During the training stage, object boxes …

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 …

Text-guided image generation has progressed rapidly in recent years, inspiring major
breakthroughs in text-guided shape generation. Recently, it has been shown that using …

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 …

We present a method to formulate algorithm discovery as program search, and apply it to
discover optimization algorithms for deep neural network training. We leverage efficient …

The diffusion-based generative models have achieved remarkable success in text-based
image generation. However, since it contains enormous randomness in generation …

Finding correspondences between images is a fundamental problem in computer vision. In
this paper, we show that correspondence emerges in image diffusion models without any …

Diffusion models have made significant breakthroughs in image, audio, and video
generation, but they depend on an iterative generation process that causes slow sampling …

Natural and expressive human motion generation is the holy grail of computer animation. It
is a challenging task, due to the diversity of possible motion, human perceptual sensitivity to …

Human motion modeling is important for many modern graphics applications, which typically
require professional skills. In order to remove the skill barriers for laymen, recent motion …