arXiv:2411.10836

AnimateAnything: Consistent and Controllable Animation for Video Generation

Guojun Lei, Chi Wang, Hong Li, Rong Zhang, Yikai Wang, Weiwei Xu

제출 2024-11-16

원문 초록

We present a unified controllable video generation approach AnimateAnything that facilitates precise and consistent video manipulation across various conditions, including camera trajectories, text prompts, and user motion annotations. Specifically, we carefully design a multi-scale control feature fusion network to construct a common motion representation for different conditions. It explicitly converts all control information into frame-by-frame optical flows. Then we incorporate the optical flows as motion priors to guide final video generation. In addition, to reduce the flickering issues caused by large-scale motion, we propose a frequency-based stabilization module. It can enhance temporal coherence by ensuring the video's frequency domain consistency. Experiments demonstrate that our method outperforms the state-of-the-art approaches. For more details and videos, please refer to the webpage: https://yu-shaonian.github.io/Animate_Anything/.

함께 살펴볼 논문

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arXiv:2507.07966공통 태그 Video Generation공식 코드 · Papers with Code

Scaling RL to Long Videos

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