The recent wave of AI-generated content (AIGC) has witnessed substantial success in
computer vision, with the diffusion model playing a crucial role in this achievement. Due to …

The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

Text-to-Image diffusion models have made tremendous progress over the past two years,
enabling the generation of highly realistic images based on open-domain text descriptions …

This work aims to learn a high-quality text-to-video (T2V) generative model by leveraging a
pre-trained text-to-image (T2I) model as a basis. It is a highly desirable yet challenging task …

The pursuit of controllability as a higher standard of visual content creation has yielded
remarkable progress in customizable image synthesis. However, achieving controllable …

Animating a still image offers an engaging visual experience. Traditional image animation
techniques mainly focus on animating natural scenes with stochastic dynamics (eg clouds …

Humans can easily solve multimodal tasks in context with only a few demonstrations or
simple instructions which current multimodal systems largely struggle to imitate. In this work …

We introduce Lumiere–a text-to-video diffusion model designed for synthesizing videos that
portray realistic, diverse and coherent motion–a pivotal challenge in video synthesis. To this …

We present Stable Video Diffusion-a latent video diffusion model for high-resolution, state-of-
the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained …

Significant advancements have been achieved in the realm of large-scale pre-trained text-to-
video Diffusion Models (VDMs). However, previous methods either rely solely on pixel …