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arXiv · 2511.17185

PostCam: Camera-Controllable Novel-View Video Generation with Query-Shared Cross-Attention

Yipeng Chen·Zhichao Ye·Zhenzhou Fang·Xinyu Chen·Xiaoyu Zhang·Jialing Liu·Nan Wang·Guofeng Zhang·Haomin Liu
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Abstract

We propose PostCam, a streamlined framework for novel-view video generation that achieves superior detail preservation and precise camera trajectory editing in dynamic scenes. Current methods often struggle with a trade-off between pose-based control, which lacks visual detail, and rendering-based guidance, which is overly sensitive to geometric accuracy. Despite recent hybrid attempts, achieving precise motion and visual consistency remains challenging due to the lack of effective cross-modal alignment. We argue that robust control stems from the deep alignment of multimodal signals rather than increased input complexity. Our core contribution is the Query-Shared Cross-Attention mechanism, which projects 6-DoF poses and rendered features into a unified latent space. This allows the model to spontaneously achieve intrinsic consistency between motion cues and pixel-level guidance during denoising. Experiments demonstrate that PostCam maintains high-fidelity visual details while outperforming state-of-the-art methods by 20% in trajectory precision, exhibiting superior robustness in complex dynamic scenes. Our project webpage is publicly available at: https://cccqaq.github.io/PostCam.github.io/

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Yipeng Chen, Zhichao Ye, Zhenzhou Fang, Xinyu Chen, Xiaoyu Zhang, Jialing Liu, Nan Wang, Guofeng Zhang, Haomin Liu. 2025-11-21. PostCam: Camera-Controllable Novel-View Video Generation with Query-Shared Cross-Attention. https://arxiv.org/abs/2511.17185

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