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 …

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

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 …

World models, especially in autonomous driving, are trending and drawing extensive
attention due to their capacity for comprehending driving environments. The established …

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 …

Motions in a video primarily consist of camera motion, induced by camera movement, and
object motion, resulting from object movement. Accurate control of both camera and object …

This paper introduces ModelScopeT2V, a text-to-video synthesis model that evolves from a
text-to-image synthesis model (ie, Stable Diffusion). ModelScopeT2V incorporates spatio …

The development of text-to-video (T2V), ie, generating videos with a given text prompt, has
been significantly advanced in recent years. However, relying solely on text prompts often …

Character Animation aims to generating character videos from still images through driving
signals. Currently diffusion models have become the mainstream in visual generation …