用3D高斯点云实现全景场景的多物体精准修复，保持跨视角一致性。
Inpaint360GS: Efficient Object-Aware 3D Inpainting via Gaussian Splatting for 360° Scenes
- 通过2D分割蒸馏与虚拟相机引导，在360°场景中准确定位目标物体。
- 在复杂遮挡下仍能实现高质量、跨视角一致的三维补全。
- 专为全景修复设计新数据集，适合需要真实感全景编辑的研究者。
尽管基于NeRF和3D高斯点云（3DGS）的单物体正面图像修复取得进展，复杂360°场景的修复仍研究不足。主要挑战包括：(i) 在360°环境中识别目标物体，(ii) 多物体场景中严重遮挡导致难以定义修复区域，(iii) 跨视角保持外观一致性和高质量。为此，我们提出Inpaint360GS，一个基于3DGS的灵活全景编辑框架，支持多物体移除与高保真三维修复。通过将2D分割结果蒸馏至3D，并利用虚拟相机视图提供上下文指导，方法实现精准对象级编辑与一致场景重建。我们还构建了一个专用于360°修复的新数据集，填补了无真实标注物体缺失场景的空白。实验表明，Inpaint360GS优于现有基线，达到当前最优性能。
原文摘要 · Abstract (English)
Despite recent advances in single-object front-facing inpainting using NeRF and 3D Gaussian Splatting (3DGS), inpainting in complex 360° scenes remains largely underexplored. This is primarily due to three key challenges: (i) identifying target objects in the 3D field of 360° environments, (ii) dealing with severe occlusions in multi-object scenes, which makes it hard to define regions to inpaint, and (iii) maintaining consistent and high-quality appearance across views effectively. To tackle these challenges, we propose Inpaint360GS, a flexible 360° editing framework based on 3DGS that supports multi-object removal and high-fidelity inpainting in 3D space. By distilling 2D segmentation into 3D and leveraging virtual camera views for contextual guidance, our method enables accurate object-level editing and consistent scene completion. We further introduce a new dataset tailored for 360° inpainting, addressing the lack of ground truth object-free scenes. Experiments demonstrate that Inpaint360GS outperforms existing baselines and achieves state-of-the-art performance. Project page: https://dfki-av.github.io/inpaint360gs/
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