Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation

Yingshuang Zou; Xiaoyu Shi; Yawen Luo; Ziang Li; Qinghe Wang; Mengfei Li; Chengfeng Zhao; Xintao Wang; Pengfei Wan; Kun Gai; Yuan Liu

arXiv · 2610.26801

Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation

Yingshuang Zou·Xiaoyu Shi·Yawen Luo·Ziang Li·Qinghe Wang·Mengfei Li·Chengfeng Zhao·Xintao Wang·Pengfei Wan·Kun Gai·Yuan Liu

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Abstract

Recent advances in text-to-video generation have enabled high-fidelity single-shot synthesis, yet practical storytelling creation requires multi-shot videos with both strong inter-shot consistency and fine-grained controllability. Existing multi-shot video generation approaches achieve strong consistency but still fall short in controllability. In this paper, we propose Mise-en-Video (MeV), a highly controllable multi-shot video generation framework that allows video creators to conduct staging the multi-shot in the 3D space and then generate the corresponding multi-shot video. To achieve this, our framework combines a hierarchical attention mechanism for multi-level narrative consistency with 3D-aware layout guidance for precise, per-shot spatial control. To support training and evaluation, we develop standardized annotation pipelines and construct a 160K-video dataset with hierarchical multi-shot texts and oriented 3D bounding boxes. Extensive experiments demonstrate that MeV consistently outperforms strong baselines in video quality, inter-shot consistency, and subject-level controllability.

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BibTeX RIS

Yingshuang Zou, Xiaoyu Shi, Yawen Luo, Ziang Li, Qinghe Wang, Mengfei Li, Chengfeng Zhao, Xintao Wang, Pengfei Wan, Kun Gai, Yuan Liu. 2026-10-19. Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation. https://arxiv.org/abs/2610.26801

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