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Flex4DHuman 使用扩散模型从视频中重建 4D 人体

研究人员开发了 Flex4DHuman,这是一种新颖的扩散模型,能够从单目或稀疏多视角视频中重建动态 4D 人体模型。该模型基于 Wan 2.1 1.3B 文本到视频架构构建,不需要骨骼或深度图等显式几何先验。相反,它使用相对相机姿态条件和独特的五轴位置编码来生成同步的密集多视角视频,然后可以将其与 4D Gaussian Splatting 一起用于详细的 4D 重建。Flex4DHuman 在基准数据集上展示了卓越的性能,并显示出在游戏、AR/VR 和视频重拍等应用中的潜力。 AI

影响 能够从随意拍摄的视频中大规模创建 4D 内容,可能对 AR/VR 和游戏行业产生影响。

排序理由 这是一篇描述新模型和方法的论文。

在 arXiv cs.CV 阅读 →

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Flex4DHuman 使用扩散模型从视频中重建 4D 人体

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报道来源 [2]

  1. arXiv cs.CV TIER_1 English(EN) · Jen-Hao Cheng, Yipeng Wang, Hao Zhang, Gengshan Yang, Jenq-Neng Hwang ·

    Flex4DHuman:用于4D人体重建的灵活多视角视频扩散模型

    arXiv:2606.13655v1 Announce Type: new Abstract: We present Flex4DHuman, a multi-view video diffusion model that transforms a monocular or sparse multi-view video of a dynamic subject into synchronized dense multi-view videos using only relative camera-pose conditioning. Unlike pr…

  2. arXiv cs.CV TIER_1 English(EN) · Jenq-Neng Hwang ·

    Flex4DHuman: 灵活的多视角视频扩散模型用于四维人体重建

    We present Flex4DHuman, a multi-view video diffusion model that transforms a monocular or sparse multi-view video of a dynamic subject into synchronized dense multi-view videos using only relative camera-pose conditioning. Unlike prior human-centric methods that rely on skeletons…