3D Gaussian Editing with A Single Image
Guan Luo, Tian-Xing Xu, Ying-Tian Liu, Xiao-Xiong Fan, Fang-Lue Zhang,, Song-Hai Zhang

TL;DR
This paper introduces a novel method for 3D scene editing from a single image using 3D Gaussian Splatting, enabling intuitive, flexible, and high-quality manipulation of 3D content without requiring reconstructed meshes.
Contribution
The proposed approach allows direct 2D image plane editing of 3D scenes via 3D Gaussian Splatting, incorporating new optimization, occlusion handling, and deformation strategies for improved editing capabilities.
Findings
Effective handling of geometric details and long-range deformation.
Superior editing flexibility and quality over previous methods.
Robust performance in non-rigid deformation scenarios.
Abstract
The modeling and manipulation of 3D scenes captured from the real world are pivotal in various applications, attracting growing research interest. While previous works on editing have achieved interesting results through manipulating 3D meshes, they often require accurately reconstructed meshes to perform editing, which limits their application in 3D content generation. To address this gap, we introduce a novel single-image-driven 3D scene editing approach based on 3D Gaussian Splatting, enabling intuitive manipulation via directly editing the content on a 2D image plane. Our method learns to optimize the 3D Gaussians to align with an edited version of the image rendered from a user-specified viewpoint of the original scene. To capture long-range object deformation, we introduce positional loss into the optimization process of 3D Gaussian Splatting and enable gradient propagation…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · 3D Shape Modeling and Analysis · Computer Graphics and Visualization Techniques
MethodsALIGN
