4 papers
SPATIALALIGN: Aligning Dynamic Spatial Relationships in Video Generation
Fengming Liu, Tat-Jen Cham, Chuanxia Zheng
Most text-to-video (T2V) generators prioritize aesthetic quality, but often ignoring the spatial constraints in the generated videos. In this work, we present SPATIALALIGN, a self-…
Timestep Embedding Tells: It's Time to Cache for Video Diffusion Model
Feng Liu, Shiwei Zhang, Xiaofeng Wang +6
As a fundamental backbone for video generation, diffusion models are challenged by low inference speed due to the sequential nature of denoising. Previous methods speed up the mode…
EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation
Xiaofeng Wang, Kang Zhao, Feng Liu +6
Video generation has emerged as a promising tool for world simulation, leveraging visual data to replicate real-world environments. Within this context, egocentric video generation…
DreamVideo-2: Zero-Shot Subject-Driven Video Customization with Precise Motion Control
Yujie Wei, Shiwei Zhang, Hangjie Yuan +9
Recent advances in customized video generation have enabled users to create videos tailored to both specific subjects and motion trajectories. However, existing methods often requi…