MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
Current video generation techniques excel at single-shot clips but struggle to produce narrative multi-shot videos, which require flexible shot arrangement, coherent narrative, and controllability beyond text prompts. To tackle these challenges, we propose MultiShotMaster, a framework for highly controllable multi-shot video generation. We extend a pretrained single-shot model by integrating two novel variants of RoPE. First, we introduce Multi-Shot Narrative RoPE, which applies explicit phase shift at shot transitions, enabling flexible shot arrangement while preserving the temporal narrative order. Second, we design Spatiotemporal Position-Aware RoPE to incorporate reference tokens and grounding signals, enabling spatiotemporal-grounded reference injection. In addition, to overcome data scarcity, we establish an automated data annotation pipeline to extract multi-shot videos, captions, cross-shot grounding signals and reference images. Our framework leverages the intrinsic architectural properties to support multi-shot video generation, featuring text-driven inter-shot consistency, customized subject with motion control, and background-driven customized scene. Both shot count and duration are flexibly configurable. Extensive experiments demonstrate the superior performance and outstanding controllability of our framework.
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Qinghe Wang
claimed_verified
2025-12-03T09:13:33.820Z
646f3418a6a58aa29505fd30
https://cdn-avatars.huggingface.co/v1/production/uploads/646f3418a6a58aa29505fd30/1z13rnpb6rsUgQsYumWPg.png
QINGHE WANG
Qinghew
user
Qinghew
692fcb3726742347f61dad19
Xiaoyu Shi
692fcb3726742347f61dad1a
Baolu Li
claimed_verified
2025-12-03T09:13:31.176Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/JEQW6WZBcmjAWwODiDkYA.jpeg
Libaolu
8ruceLi
user
8ruceLi
692fcb3726742347f61dad1b
Weikang Bian
692fcb3726742347f61dad1c
Quande Liu
692fcb3726742347f61dad1d
Huchuan Lu
692fcb3726742347f61dad1e
Xintao Wang
692fcb3726742347f61dad1f
Pengfei Wan
692fcb3726742347f61dad20
Kun Gai
692fcb3726742347f61dad21
Xu Jia
MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
Current video generation techniques excel at single-shot clips but struggle to produce narrative multi-shot videos, which require flexible shot arrangement, coherent narrative, and controllability beyond text prompts. To tackle these challenges, we propose MultiShotMaster, a framework for highly controllable multi-shot video generation. We extend a pretrained single-shot model by integrating two novel variants of RoPE. First, we introduce Multi-Shot Narrative RoPE, which applies explicit phase shift at shot transitions, enabling flexible shot arrangement while preserving the temporal narrative order. Second, we design Spatiotemporal Position-Aware RoPE to incorporate reference tokens and grounding signals, enabling spatiotemporal-grounded reference injection. In addition, to overcome data scarcity, we establish an automated data annotation pipeline to extract multi-shot videos, captions, cross-shot grounding signals and reference images. Our framework leverages the intrinsic architectural properties to support multi-shot video generation, featuring text-driven inter-shot consistency, customized subject with motion control, and background-driven customized scene. Both shot count and duration are flexibly configurable. Extensive experiments demonstrate the superior performance and outstanding controllability of our framework.
MultiShotMaster extends a single-shot model with novel RoPE variants for flexible and controllable multi-shot video generation, addressing data scarcity with an automated annotation pipeline.
RoPE Multi-Shot Narrative RoPE Spatiotemporal Position-Aware RoPE reference tokens cross-shot grounding signals reference images text-driven inter-shot consistency motion control background-driven customized scene