Yuanxiang Ni, Xianliang Huang, Ruihan Hou, Feng Xie, Hao Zhang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28351 · open-access PDF
从单眼视频中重建动态3D场景需要从噪音和间歇地可见的观察中推断运动。长距离轨道提供了宝贵的几何限制,但将它们的碎片化时间覆盖范围整合到共享的连续运动中仍然是具有挑战性的。我们引入了“textbf{RayCo4D}”,一个为单眼4D重建的光线条件连续运动模型,明确地将视觉测量与隐藏的3D运动状态分离开来。
Machine translation (Meta M2M100); the English original follows.
Reconstructing dynamic 3D scenes from monocular video requires inferring motion from noisy and intermittently visible observations. Long-range tracks provide valuable geometric constraints, but integrating their fragmented temporal coverage into shared, continuous motion remains challenging. We introduce \textbf{RayCo4D}, a ray-conditioned continuous motion model for monocular 4D reconstruction that explicitly separates visual measurements from latent 3D motion states. Each track is associated with a reference-time 3D query constrained to its camera ray, and its image and depth observations co
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