We propose a method to distill a complex multistep diffusion model into a single-step
conditional GAN student model, dramatically accelerating inference, while preserving image …

Recent studies have shown that the denoising process in (generative) diffusion models can
induce meaningful (discriminative) representations inside the model, though the quality of …

As one of the most popular and sought-after generative models in the recent years, diffusion
models have sparked the interests of many researchers and steadily shown excellent …

We have made significant progress towards building foundational video diffusion models. As
these models are trained using large-scale unsupervised data, it has become crucial to …

Diffusion Models are popular generative modeling methods in various vision tasks, attracting
significant attention. They can be considered a unique instance of self-supervised learning …

SLEDGE is the first generative simulator for vehicle motion planning trained on real-world
driving logs. Its core component is a learned model that is able to generate agent bounding …

Diffusion models have emerged as the leading paradigm in generative modeling, excelling
in various applications. Despite their success, these models often misalign with human …

There is increased interest in using generative AI to create 3D spaces for Virtual Reality (VR)
applications. However, today's models produce artificial environments, falling short of …

Video diffusion models have shown great potential in generating high-quality videos,
making them an increasingly popular focus. However, their inherent iterative nature leads to …

Foley is a term commonly used in filmmaking, referring to the addition of daily sound effects
to silent films or videos to enhance the auditory experience. Video-to-Audio (V2A), as a …