HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives

Yihao Meng, Hao Ouyang, Yue Yu, Qiuyu Wang, Wen Wang +7 more
10/23/2025
cs.CV

No official code found. Best implementation: yihao-meng/HoloCine (702 stars, last commit 2025-11-26).

Abstract

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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[CVPR 2026 Highlight] Official Implementations for Paper - HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives

702121PythonOct 22, 202510 months agoNOASSERTION

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Cite this paper

@article{meng2025holocine,
  title  = {HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives},
  author = {Yihao Meng and Hao Ouyang and Yue Yu and Qiuyu Wang and Wen Wang and Ka Leong Cheng and Hanlin Wang and Yixuan Li and Cheng Chen and Yanhong Zeng and Yujun Shen and Huamin Qu},
  year   = {2025},
  eprint = {2510.20822},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.20822v1}
}

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