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English(EN) FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors

FixAnything模型利用视频生成先验精炼3D渲染伪影

研究人员开发了FixAnything,一个旨在精炼3D渲染并修复高斯喷溅和NeRF等各种表示中的伪影的新模型。该模型重新利用了预训练的视频生成模型,将渲染清理视为一个视频到视频的转换任务。通过使用二值掩码来识别干净像素,并采用直接偏好优化(Direct Preference Optimization)以及相机姿态准确性作为奖励信号,FixAnything只需极少的微调即可实现3D一致的结果,提供了一个可以替代多个专业精炼管线的通用解决方案。 AI

影响 这项研究为提高3D渲染质量提供了一种统一的方法,有可能简化3D艺术家和开发者的工作流程。

排序理由 该集群描述了一篇关于用于3D渲染精炼的新颖模型的新研究论文。

在 Hugging Face Daily Papers 阅读 →

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FixAnything模型利用视频生成先验精炼3D渲染伪影

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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    FixAnything:通过视频生成先验进行3D一致性渲染精炼

    Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces artifacts when input views are sparse or target views lie far from the input. Recent work mitigates these artifacts using diffusi…

  2. arXiv cs.CV TIER_1 English(EN) · Khiem Vuong, Deva Ramanan, Srinivasa Narasimhan ·

    FixAnything:通过视频生成先验实现3D一致性渲染精炼

    arXiv:2608.23549v1 Announce Type: new Abstract: Rendering views using 3D scene representations such as Gaussian Splatting (3DGS), Neural Radiance Fields (NeRF), meshes, or even point clouds produces artifacts when input views are sparse or target views lie far from the input. Rec…