Identity-preserving text-to-video (IPT2V) generation aims to create high-fidelity videos with
consistent human identity. It is an important task in video generation but remains an open …

Diffusion models have garnered significant success in generative tasks, emerging as the
predominant model in this domain. Despite their success, the substantial computational …

Multi-modal generative AI has received increasing attention in both academia and industry.
Particularly, two dominant families of techniques are: i) The multi-modal large language …

Motion control is crucial for generating expressive and compelling video content; however,
most existing video generation models rely mainly on text prompts for control, which struggle …

Recently, camera pose, as a user-friendly and physics-related condition, has been
introduced into text-to-video diffusion model for camera control. However, existing methods …

Story visualization, the task of creating visual narratives from textual descriptions, has seen
progress with text-to-image generation models. However, these models often lack effective …

Understanding the ability of humans to use objects is crucial for AI to improve daily life.
Existing studies for learning such ability focus on human-object patterns (eg, contact, spatial …

Recent advancements in video generation have been greatly driven by video diffusion
models, with camera motion control emerging as a crucial challenge in creating view …

Current diffusion-based face animation methods generally adopt a ReferenceNet (a copy of
U-Net) and a large amount of curated self-acquired data to learn appearance features, as …

We have witnessed the unprecedented success of diffusion-based video generation over
the past year. Recently proposed models from the community have wielded the power to …