Despite significant advancements in video generation and editing using diffusion models,
achieving accurate and localized video editing remains a substantial challenge …

The rapid development of diffusion models (DMs) has significantly advanced image and
video applications, making" what you want is what you see" a reality. Among these, video …

With the recent advancement in large language models (LLMs), there is a growing interest in
combining LLMs with multimodal learning. Previous surveys of multimodal large language …

Abstract We introduce Emu Video Edit (EVE), a model that establishes a new state-of-the art
in video editing without relying on any supervised video editing data. To develop EVE we …

Recent advancements in generative models have significantly enhanced their capacity for
image generation, enabling a wide range of applications such as image editing, completion …

In the dynamic field of digital content creation using generative models, state-of-the-art video
editing models still do not offer the level of quality and control that users desire. Previous …

We propose a video editing framework, NaRCan, which integrates a hybrid deformation field
and diffusion prior to generate high-quality natural canonical images to represent the input …

We introduce OmniCreator, a novel framework that can conduct text-prompted unified
(image+ video) generation as well as editing all in one place. OmniCreator acquires …

Large-scale video generation models have the inherent ability to realistically model natural
scenes. In this paper, we demonstrate that through a careful design of a generative video …

Diffusion models have demonstrated remarkable success in image generation and editing,
with recent advancements enabling albedo-preserving image relighting. However, applying …