[Submitted on 22 Jul 2026]
Title:3D-GIMP: When 3D Gaussian Inpainting Meets PatchMatch
View a PDF of the paper titled 3D-GIMP: When 3D Gaussian Inpainting Meets PatchMatch, by Xuening Tian and Dieter Schmalstieg and Shohei Mori
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Abstract:Recent advances in 3D scene editing have leveraged iterative diffusion models to update input views. However, this process is computationally expensive and struggles to produce sharp details. Meanwhile, ``hallucination drift'' frequently introduces multi-view inconsistencies, leading to structural artifacts when rendering novel viewpoints. To address this problem, we present 3D-GIMP (3D Gaussian Inpainting Meets Patch Matching), a novel hybrid paradigm designed for high-fidelity object removal in 3D Gaussian Splatting. Instead of diffusing every view, 3D-GIMP performs a single generative inpainting on a key reference view, which serves as an appearance prior. We then introduce a 3D-aware PatchMatch algorithm to propagate these reference textures across all remaining views via correspondence matching, effectively bypassing the stochastic nature of frame-by-frame diffusion. By prioritizing reconstructive consistency over iterative generation, 3D-GIMP maintains high-frequency details across arbitrary resolutions while ensuring a mathematically consistent 3D reconstruction. Our experiments demonstrate that 3D-GIMP not only achieves competitive inpainting quality as previous methods using diffusion in multiple views, but also outperforms these methods in rendering speed and view consistency.
Comments: 15 pages
Subjects:
Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR)
Cite as: arXiv:2607.20789 [cs.CV]
(or arXiv:2607.20789v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2607.20789
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Xuening Tian [view email] [v1] Wed, 22 Jul 2026 23:27:20 UTC (37,965 KB)
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