4 papers
Focal Guidance: Unlocking Controllability from Semantic-Weak Layers in Video Diffusion Models
Yuanyang Yin, Yufan Deng, Shenghai Yuan +3
The task of Image-to-Video (I2V) generation aims to synthesize a video from a reference image and a text prompt. This requires diffusion models to reconcile high-frequency visual c…
Comp-Attn: Present-and-Align Attention for Compositional Video Generation
Hongyu Zhang, Yufan Deng, Shenghai Yuan +5
In the domain of text-to-video (T2V) generation, reliably synthesizing compositional content involving multiple subjects with intricate relations is still underexplored. The main c…
MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement
Yufan Deng, Yuanyang Yin, Xun Guo +8
We tackle the task of any-reference video generation, which aims to synthesize videos conditioned on arbitrary types and combinations of reference subjects, together with textual p…
CINEMA: Coherent Multi-Subject Video Generation via MLLM-Based Guidance
Yufan Deng, Xun Guo, Yizhi Wang +7
Video generation has witnessed remarkable progress with the advent of deep generative models, particularly diffusion models. While existing methods excel in generating high-quality…