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

The metaverse integrates physical and virtual realities, enabling humans and their avatars to
interact in an environment supported by technologies such as high-speed internet, virtual …

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 …

Recently, DreamFusion demonstrated the utility of a pretrained text-to-image diffusion model
to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis …

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

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 …

While generative models produce high-quality images of concepts learned from a large-
scale database, a user often wishes to synthesize instantiations of their own concepts (for …

The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated
strong power of learning complex structures and meaningful semantics. However, relying …

To replicate the success of text-to-image (T2I) generation, recent works employ large-scale
video datasets to train a text-to-video (T2V) generator. Despite their promising results, such …