CamCloneMaster: Enabling Reference-based Camera Control for Video Generation
- URL: http://arxiv.org/abs/2506.03140v1
- Date: Tue, 03 Jun 2025 17:59:02 GMT
- Title: CamCloneMaster: Enabling Reference-based Camera Control for Video Generation
- Authors: Yawen Luo, Jianhong Bai, Xiaoyu Shi, Menghan Xia, Xintao Wang, Pengfei Wan, Di Zhang, Kun Gai, Tianfan Xue,
- Abstract summary: CamCloneMaster is a framework that enables users to replicate camera movements from reference videos without requiring camera parameters or test-time fine-tuning.<n>We present a large-scale synthetic dataset designed for camera clone learning, encompassing diverse scenes, subjects, and camera movements.
- Score: 39.68297612349062
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Camera control is crucial for generating expressive and cinematic videos. Existing methods rely on explicit sequences of camera parameters as control conditions, which can be cumbersome for users to construct, particularly for intricate camera movements. To provide a more intuitive camera control method, we propose CamCloneMaster, a framework that enables users to replicate camera movements from reference videos without requiring camera parameters or test-time fine-tuning. CamCloneMaster seamlessly supports reference-based camera control for both Image-to-Video and Video-to-Video tasks within a unified framework. Furthermore, we present the Camera Clone Dataset, a large-scale synthetic dataset designed for camera clone learning, encompassing diverse scenes, subjects, and camera movements. Extensive experiments and user studies demonstrate that CamCloneMaster outperforms existing methods in terms of both camera controllability and visual quality.
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