InteractiveVideo: User-Centric Controllable Video Generation with Synergistic Multimodal Instructions

February 05, 2024 ยท Entered Twilight ยท ๐Ÿ› arXiv.org

๐Ÿ’ค TWILIGHT: Eternal Rest
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Repo contents: .gitignore, LICENSE, README.md, assets, demo, models, requirements.txt, samples, scripts

Authors Yiyuan Zhang, Yuhao Kang, Zhixin Zhang, Xiaohan Ding, Sanyuan Zhao, Xiangyu Yue arXiv ID 2402.03040 Category cs.CV: Computer Vision Cross-listed cs.AI, cs.LG, cs.MM Citations 7 Venue arXiv.org Repository https://github.com/invictus717/InteractiveVideo โญ 132 Last Checked 3 months ago
Abstract
We introduce $\textit{InteractiveVideo}$, a user-centric framework for video generation. Different from traditional generative approaches that operate based on user-provided images or text, our framework is designed for dynamic interaction, allowing users to instruct the generative model through various intuitive mechanisms during the whole generation process, e.g. text and image prompts, painting, drag-and-drop, etc. We propose a Synergistic Multimodal Instruction mechanism, designed to seamlessly integrate users' multimodal instructions into generative models, thus facilitating a cooperative and responsive interaction between user inputs and the generative process. This approach enables iterative and fine-grained refinement of the generation result through precise and effective user instructions. With $\textit{InteractiveVideo}$, users are given the flexibility to meticulously tailor key aspects of a video. They can paint the reference image, edit semantics, and adjust video motions until their requirements are fully met. Code, models, and demo are available at https://github.com/invictus717/InteractiveVideo
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