让AI一次生成连贯长篇电影叙事，支持角色与镜头的全局一致性。
HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives
- 通过窗口交叉注意力实现文本提示精准定位到特定镜头。
- 采用稀疏跨镜头自注意力，支持分钟级视频高效生成。
- 具备角色记忆与电影运镜直觉，适合影视创作与交互设计。
当前最先进的文生视频模型擅长生成孤立片段，但在构建连贯的多镜头叙事方面表现不足，而这是讲故事的核心。我们提出HoloCine，通过整体化生成整个场景，确保从第一镜到最后一镜的全局一致性，弥合了这一‘叙事鸿沟’。其架构利用窗口交叉注意力机制，将文本提示精确定位至特定镜头；同时采用稀疏跨镜头自注意力模式（镜头内密集、镜头间稀疏），保障分钟级生成的效率。除在叙事连贯性上达到新基准外，HoloCine还展现出显著的涌现能力：对角色和场景具有持续记忆，以及对电影手法的直观理解。本工作标志着从片段合成迈向自动化电影制作的转折点，使端到端的影视创作成为可能。代码已开源：https://holo-cine.github.io/。
原文摘要 · Abstract (English)
State-of-the-art text-to-video models excel at generating isolated clips but fall short of creating the coherent, multi-shot narratives, which are the essence of storytelling. We bridge this "narrative gap" with HoloCine, a model that generates entire scenes holistically to ensure global consistency from the first shot to the last. Our architecture achieves precise directorial control through a Window Cross-Attention mechanism that localizes text prompts to specific shots, while a Sparse Inter-Shot Self-Attention pattern (dense within shots but sparse between them) ensures the efficiency required for minute-scale generation. Beyond setting a new state-of-the-art in narrative coherence, HoloCine develops remarkable emergent abilities: a persistent memory for characters and scenes, and an intuitive grasp of cinematic techniques. Our work marks a pivotal shift from clip synthesis towards automated filmmaking, making end-to-end cinematic creation a tangible future. Our code is available at: https://holo-cine.github.io/.
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