InteractiveVideo: User-Centric Controllable Video Generation with Synergistic Multimodal Instructions
This addresses the need for more intuitive and responsive video generation tools for users, though it appears incremental as it builds on existing generative approaches by adding interactive capabilities.
The paper tackles the problem of user control in video generation by introducing InteractiveVideo, a framework that allows dynamic interaction through multimodal instructions like text, images, painting, and drag-and-drop, enabling iterative refinement and fine-grained tailoring of videos.
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