DreamFactory: Pioneering Multi-Scene Long Video Generation with a Multi-Agent Framework

TL;DR

DreamFactory is a novel multi-agent framework that enables the generation of long, multi-scene videos with consistent style and content, overcoming limitations of existing short-video models.

Contribution

It introduces a multi-agent collaboration approach and new metrics for evaluating long video coherence, along with a comprehensive dataset for multi-scene video research.

Findings

Successfully generates long, stylistically coherent videos

Proposes novel metrics for cross-scene consistency evaluation

Provides a large, human-rated multi-scene video dataset

Abstract

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.