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arXiv · 2610.09720

DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video

Dingwei Xian·Xiaoyu Zhou·Yajiao Xiong·Yongtao Wang·Ming-Hsuan Yang
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Abstract

Online reconstruction of dynamic 4D scenes from long, unposed streaming videos requires both continuous processing and photorealistic rendering, which existing methods struggle to achieve simultaneously. Existing feed-forward Gaussian methods are restricted to offline processing, whereas online point-cloud approaches struggle to maintain dense geometry and high-fidelity rendering. We present DynStream, a framework for streaming 4D Gaussian reconstruction from long, unposed videos. Given a continuous video stream, DynStream reconstructs the scene within local temporal windows and incrementally aligns and fuses these local reconstructions into a globally consistent scene, enabling online 4D reconstruction without per-scene optimization. By jointly enforcing cross-window geometric consistency and modeling time-varying scene content, DynStream supports efficient reconstruction and photorealistic rendering over extended video streams. Experiments demonstrate that DynStream enables high-fidelity online dynamic reconstruction and rendering from long video streams, achieving state-of-the-art performance across diverse dynamic indoor and outdoor scenes.

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Dingwei Xian, Xiaoyu Zhou, Yajiao Xiong, Yongtao Wang, Ming-Hsuan Yang. 2026-10-07. DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video. https://arxiv.org/abs/2610.09720

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