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English(EN) DynStream: Online Streaming 4D Gaussian Reconstruction of Dynamic Worlds from Unposed Video

新框架支持从视频流实时重建3D和4D场景

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新的研究论文S2Tok和DynStream，引入了用于从流式视频进行实时3D和4D场景重建的新颖框架。S2Tok利用持久化空间令牌和基于Transformer的方法来维护动态场景状态，无需缓存先前帧即可进行渲染。DynStream通过处理局部时间窗口并将其融合到全局一致的场景中，专注于从无姿态视频流重建动态4D场景，在动态环境中取得了最先进的性能。 AI

影响 这些进展可能在虚拟现实、机器人和自主系统等领域带来更高效、更逼真的实时渲染应用。

排序理由 两篇在arXiv上发表的学术论文，介绍了3D/4D重建的新方法。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新框架支持从视频流实时重建3D和4D场景

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两篇在arXiv上发表的学术论文，介绍了3D/4D重建的新方法。
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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Fang Li, Jiraphon Yenphraphai, Quentin Herau, Depu Meng, Yihan Hu, Tianshuo Xu, Narendra Ahuja, Wei Zhan ·

    S2Tok：具有持久空间令牌的流式3D高斯重建

    arXiv:2610.08978v1 Announce Type: new Abstract: Streaming 3D reconstruction requires more than a sequence of geometric predictions: it requires a persistent scene state that can incorporate new evidence and remain renderable as observations arrive. Latent spatial tokens offer a p…

  2. arXiv cs.CV TIER_1 English(EN) · Dingwei Xian, Xiaoyu Zhou, Yajiao Xiong, Yongtao Wang, Ming-Hsuan Yang ·

    DynStream：从无姿态视频进行动态世界的在线流式4D高斯重建

    arXiv:2610.09720v1 Announce Type: new 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 Gaussi…

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