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English(EN) RoGe: Novel View Synthesis via End-to-End Implicit Reconstruction and Generation

RoGe框架统一3D重建和生成,实现新视角合成

研究人员推出RoGe,一个新颖的新视角合成框架,将重建和生成整合到一个端到端的过程中。与依赖中间渲染图像或显式3D表示的先前方法不同,RoGe使用前馈重建模型来创建隐式场景表示。该表示的几何特征随后直接作为条件注入视频扩散模型,从而能够从稀疏输入视图和相机轨迹生成时间连贯的视频。在DL3DV数据集上的实验表明,RoGe的性能优于现有的基于重建、基于生成和混合基线。 AI

影响 这项研究可能带来更有效、更准确的方法,用于从有限的输入数据生成3D场景和视频。

排序理由 这是一篇详细介绍新视角合成新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

RoGe框架统一3D重建和生成,实现新视角合成

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这是一篇详细介绍新视角合成新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xiaolei Lang, Ze Kang, Zehao Huang, Naiyan Wang ·

    RoGe:通过端到端隐式重建与生成实现新视角合成

    arXiv:2609.02847v1 Announce Type: new Abstract: Novel view synthesis from sparse inputs requires both geometric grounding from the observed views and generative priors of unobserved regions, motivating recent hybrid methods that combine reconstruction and generation. However, exi…