English(EN) CleanGS: Pareto-Guided Post-Hoc Cleanup of 3D Gaussian Splatting Scenes

CleanGS 通过帕累托引导清理优化 3D 高斯溅射场景

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了 CleanGS，一种新颖的后处理方法，旨在优化 3D 高斯溅射 (3DGS) 场景重建。该技术可有效移除从新角度观看场景时出现的、物体外的多余结构，而无需重新训练原始 3DGS 模型。CleanGS 采用帕累托引导方法，根据遮罩可靠性、相机基线和视角多样性选择最佳视图，然后在光栅化过程中使用“三中取二”的投票机制来保留相关的斯普拉特元素。与 FlashSplat 和 GaussianCut 等现有清理工具相比，该方法在 PSNR 指标上表现更优，并显著减少了处理时间和内存使用量。 AI

影响提高了 3D 场景重建的质量和效率，可能有助于需要详细且干净的 3D 模型的应用。

排序理由该集群包含一篇详细介绍 3D 场景重建新方法的学术论文。 [lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Jyotirmaya Shivottam, Om Kumar, Subhankar Mishra · 2026-10-27 04:00

CleanGS：基于帕累托最优的3D高斯泼溅场景事后清理

arXiv:2601.00913v2 Announce Type: replace Abstract: A pretrained 3D Gaussian Splatting (3DGS) reconstruction can reproduce its capture views well while retaining off-object structure that becomes visible under reframing. We present CleanGS, a post-hoc cleanup method that removes …

本文如何被排名

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CleanGS：基于帕累托最优的3D高斯泼溅场景事后清理

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