Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion

Zhenghong Zhou; Xiaohang Zhan; Zhiqin Chen; Soo Ye Kim; Nanxuan Zhao; Haitian Zheng; Qing Liu; He Zhang; Zhe Lin; Yuqian Zhou; Jiebo Luo

arXiv · 2603.15614

Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion

Zhenghong Zhou·Xiaohang Zhan·Zhiqin Chen·Soo Ye Kim·Nanxuan Zhao·Haitian Zheng·Qing Liu·He Zhang·Zhe Lin·Yuqian Zhou·Jiebo Luo

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Abstract

Recent video diffusion models have made remarkable strides in visual quality, yet precise, fine-grained control remains a key bottleneck that limits practical customizability for content creation. For AI video creators, three forms of control are crucial: (i) scene composition, (ii) multi-view consistent subject customization, and (iii) camera-pose or object-motion adjustment. Existing methods typically handle these dimensions in isolation, with limited support for multi-view subject synthesis and identity preservation under arbitrary pose changes. This lack of a unified architecture makes it difficult to support versatile, jointly controllable video. We introduce Tri-Prompting, a unified framework and two-stage training paradigm that integrates scene composition, multi-view subject consistency, and motion control. Our approach leverages a dual-condition motion module driven by 3D tracking points for background scenes and downsampled RGB cues for foreground subjects. To ensure a balance between controllability and visual realism, we further propose an inference ControlNet scale schedule. Tri-Prompting supports novel workflows, including 3D-aware subject insertion into any scenes and manipulation of existing subjects in an image. Experimental results demonstrate that Tri-Prompting significantly outperforms specialized baselines such as Phantom and DaS in multi-view subject identity, 3D consistency, and motion accuracy.

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Zhenghong Zhou, Xiaohang Zhan, Zhiqin Chen, Soo Ye Kim, Nanxuan Zhao, Haitian Zheng, Qing Liu, He Zhang, Zhe Lin, Yuqian Zhou, Jiebo Luo. 2026-03-16. Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion. https://arxiv.org/abs/2603.15614

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