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arXiv · 2412.03526

Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos

Hanxue Liang·Jiawei Ren·Ashkan Mirzaei·Antonio Torralba·Ziwei Liu·Igor Gilitschenski·Sanja Fidler·Cengiz Oztireli·Huan Ling·Zan Gojcic·Jiahui Huang
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Abstract

Recent advancements in static feed-forward scene reconstruction have demonstrated significant progress in high-quality novel view synthesis. However, these models often struggle with generalizability across diverse environments and fail to effectively handle dynamic content. We present BTimer (short for BulletTimer), the first motion-aware feed-forward model for real-time reconstruction and novel view synthesis of dynamic scenes. Our approach reconstructs the full scene in a 3D Gaussian Splatting representation at a given target ('bullet') timestamp by aggregating information from all the context frames. Such a formulation allows BTimer to gain scalability and generalization by leveraging both static and dynamic scene datasets. Given a casual monocular dynamic video, BTimer reconstructs a bullet-time scene within 150ms while reaching state-of-the-art performance on both static and dynamic scene datasets, even compared with optimization-based approaches.

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Hanxue Liang, Jiawei Ren, Ashkan Mirzaei, Antonio Torralba, Ziwei Liu, Igor Gilitschenski, Sanja Fidler, Cengiz Oztireli, Huan Ling, Zan Gojcic, Jiahui Huang. 2025-09-21. Feed-Forward Bullet-Time Reconstruction of Dynamic Scenes from Monocular Videos. https://arxiv.org/abs/2412.03526

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