Planar-Guided Gaussian Splatting with Texture-Complexity-Based Initialization
文献类型：期刊论文
| 作者 | Zheng, Anhong1,2; Yu, Zhuoyuan1,2 |
| 刊名 | ELECTRONICS
 |
| 出版日期 | 2026-03-09 |
| 卷号 | 15期号:5页码:1137 |
| 关键词 | 3D Gaussian Splatting indoor scene reconstruction geometric priors Manhattan-world assumption dense feature matching surface reconstruction |
| ISSN号 | 2079-9292 |
| DOI | 10.3390/electronics15051137 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Indoor scene reconstruction remains challenging due to the prevalence of low-texture regions such as walls, floors, and ceilings, where weak photometric signals hinder accurate geometric recovery. While 3D Gaussian Splatting (3DGS) achieves impressive novel view synthesis, existing methods struggle with geometric accuracy in textureless areas due to uniform treatment of scene regions. We propose a texture-complexity-based 3D Gaussian Splatting strategy that leverages geometric priors for high-fidelity indoor reconstruction. Our method extracts planar priors through Manhattan frame alignment and refines them with Segment Anything Model (SAM) masks, enabling texture-aware initialization: planar priors guide Gaussian placement in low-texture regions, while dense feature matching ensures accurate initialization in high-detail areas. During optimization, geometric regularization through depth-plane loss, normal-surface loss, and normal-consistency loss maintains structural integrity. Evaluations on ScanNet++, MuSHRoom, and Replica datasets demonstrate state-of-the-art performance, with training completed in under 1 h. Our approach balances geometric accuracy with photometric fidelity, providing a practical solution for high-fidelity indoor mesh extraction from Gaussian representations. |
| URL标识 | 查看原文 |
| WOS研究方向 | Computer Science ; Engineering ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:001713478600001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221309]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Yu, Zhuoyuan |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zheng, Anhong,Yu, Zhuoyuan. Planar-Guided Gaussian Splatting with Texture-Complexity-Based Initialization[J]. ELECTRONICS,2026,15(5):1137. |
| APA | Zheng, Anhong,&Yu, Zhuoyuan.(2026).Planar-Guided Gaussian Splatting with Texture-Complexity-Based Initialization.ELECTRONICS,15(5),1137. |
| MLA | Zheng, Anhong,et al."Planar-Guided Gaussian Splatting with Texture-Complexity-Based Initialization".ELECTRONICS 15.5(2026):1137. |
入库方式： OAI收割
来源：地理科学与资源研究所
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