SplatMesh: Interactive 3D Segmentation and Editing Using Mesh-Based Gaussian Splatting
Kaichen Zhou, Lanqing Hong, Xinhai Chang, Yingji Zhong, Enze Xie, Hao, Dong, Zhihao Li, Yongxin Yang, Zhenguo Li, Wei Zhang

TL;DR
SplatMesh is a novel method that combines mesh simplification with Gaussian splatting for efficient, high-quality 3D segmentation and editing, balancing detail, stability, and memory constraints.
Contribution
It introduces a new algorithm that integrates mesh simplification with Gaussian splatting, enabling flexible, high-quality 3D editing under memory constraints.
Findings
Outperforms existing methods in view synthesis quality.
Enables extensive 3D editing with improved stability.
Balances memory use with detailed representation.
Abstract
A key challenge in fine-grained 3D-based interactive editing is the absence of an efficient representation that balances diverse modifications with high-quality view synthesis under a given memory constraint. While 3D meshes provide robustness for various modifications, they often yield lower-quality view synthesis compared to 3D Gaussian Splatting, which, in turn, suffers from instability during extensive editing. A straightforward combination of these two representations results in suboptimal performance and fails to meet memory constraints. In this paper, we introduce SplatMesh, a novel fine-grained interactive 3D segmentation and editing algorithm that integrates 3D Gaussian Splat with a precomputed mesh and could adjust the memory request based on the requirement. Specifically, given a mesh, \method simplifies it while considering both color and shape, ensuring it meets memory…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
Topics3D Shape Modeling and Analysis · Computer Graphics and Visualization Techniques · Advanced Vision and Imaging
