DreamFactory: Pioneering Multi-Scene Long Video Generation with a Multi-Agent Framework
<|reference_start|>DreamFactory: Pioneering Multi-Scene Long Video Generation with a Multi-Agent Framework: Current video generation models excel at creating short, realistic clips, but struggle with longer, multi-scene videos. We introduce \texttt{DreamFactory}, an LLM-based framework that tackles this challenge. \texttt{DreamFactory} leverages multi-agent collaboration principles and a Key Frames Iteration Design Method to ensure consistency and style across long videos. It utilizes Chain of Thought (COT) to address uncertainties inherent in large language models. \texttt{DreamFactory} generates long, stylistically coherent, and complex videos. Evaluating these long-form videos presents a challenge. We propose novel metrics such as Cross-Scene Face Distance Score and Cross-Scene Style Consistency Score. To further research in this area, we contribute the Multi-Scene Videos Dataset containing over 150 human-rated videos.<|reference_end|>
@article{xie2024dreamfactory:,
    title={DreamFactory: Pioneering Multi-Scene Long Video Generation with a
  Multi-Agent Framework},
    author={Zhifei Xie, Daniel Tang, Dingwei Tan, Jacques Klein, Tegawend F.
  Bissyand, Saad Ezzini},
    journal={arXiv preprint arXiv:2408.11788},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.11788},
    primaryClass={cs.AI cs.CL cs.CV cs.SE}
}