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arXiv · 2605.17303

LongDPM: Overlap-Aware 4D Reconstruction from Long Monocular Videos

Chenyi Xu·Yihao Wu·Liqi Yan·Chao Yang·Jianhui Zhang·Fangli Guan·Pan Li
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Abstract

Recovering a dynamic 3D scene from a long monocular video is crucial for dense geometry, camera motion, and temporal correspondence to remain consistent in a shared coordinate system. Existing methods face two key challenges: (1) feed-forward reconstruction models provide accurate local predictions but are limited to short clips, and (2) long-range trackers preserve correspondences without producing dense sequence-level reconstruction. This paper presents LongDPM, a novel overlap-aware framework for scalable long-range monocular dynamic reconstruction. First, LongDPM processes long videos in overlapping chunks, keeping inference memory bounded by the chunk length. Second, it connects chunk-local coordinate systems through confidence-weighted registration with static-aware overlap abstraction. Third, it associates dynamic identities across chunk boundaries and fuses matched trajectories to recover coherent long-range 3D motion. Experimental results demonstrate that LongDPM achieves superior long-range reconstruction and tracking performance, reducing dense tracking EPE over V-DPM on PointOdyssey, Kubric-F, and Kubric-G, while obtaining the best TUM-dynamics ATE for camera pose estimation.

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Chenyi Xu, Yihao Wu, Liqi Yan, Chao Yang, Jianhui Zhang, Fangli Guan, Pan Li. 2026-05-17. LongDPM: Overlap-Aware 4D Reconstruction from Long Monocular Videos. https://arxiv.org/abs/2605.17303

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