Human video generation is a dynamic and rapidly evolving task that aims to synthesize 2D
human body video sequences with generative models given control conditions such as text …

Character image animation, which generates high-quality videos from a reference image
and target pose sequence, has seen significant progress in recent years. However, most …

Recent advancements in character video synthesis still depend on extensive fine-tuning or
complex 3D modeling processes, which can restrict accessibility and hinder real-time …

Current diffusion models for human image animation struggle to ensure identity (ID)
consistency. This paper presents StableAnimator, the first end-to-end ID-preserving video …

This study delves into the intricacies of synchronizing facial dynamics with multilingual audio
inputs, focusing on the creation of visually compelling, time-synchronized animations …

Human motion video generation has garnered significant research interest due to its broad
applications, enabling innovations such as photorealistic singing heads or dynamic avatars …

Recent work on human animation usually involves audio, pose, or movement maps
conditions, thereby achieves vivid animation quality. However, these methods often face …

Recent character image animation methods based on diffusion models, such as Animate
Anyone, have made significant progress in generating consistent and generalizable …

Human motion video generation has advanced significantly, while existing methods still
struggle with accurately rendering detailed body parts like hands and faces, especially in …

In this work, we present DreamDance, a novel method for animating human images using
only skeleton pose sequences as conditional inputs. Existing approaches struggle with …