###
计算机系统应用英文版:2026,35(8):175-184
←前一篇   |   后一篇→
本文二维码信息
码上扫一扫!
基于2D高斯泼溅的文物三维重建与材质分解
(1.成都信息工程大学 计算机学院, 成都 610225;2.西南财经大学天府学院 艺术与传媒学院, 成都 610052;3.中国建筑西南设计研究院有限公司, 成都 610041;4.医疗虚拟现实与增强现实四川省工程研究中心, 成都 610225)
3D Reconstruction and Material Decomposition of Cultural Relics Based on 2D Gaussian Splatting
(1.School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China;2.School of Art and Communication, Tianfu College of Southwestern University of Finance Economics, Chengdu 610052, China;3.China Southwest Architectural Design and Research Institute Co. Ltd., Chengdu 610041, China;4.Sichuan Provincial Engineering Research Center of Medical Virtual Reality and Augmented Reality, Chengdu 610225, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 21次   下载 35
Received:December 03, 2025    Revised:January 22, 2026
中文摘要: 文物数字化是文化遗产保护与传承的核心手段, 三维重建与材质分解作为关键技术, 需有效复原文物的几何形态与多样材质属性. 现有方法在处理金属、陶瓷等多材质文物时, 易受高光反射干扰导致几何重建模糊, 且材质分解精度不足. 针对该问题, 提出一种基于 2D 高斯泼溅(2D Gaussian splatting, 2DGS)的文物三维重建与材质分解方法. 首先, 融合大规模视觉基础模型提供的深度与法向先验, 通过多约束损失函数优化几何重建, 缓解高光干扰导致的多视角一致性失效问题; 其次, 采用基于物理的渲染(physically-based rendering, PBR)框架与 split-sum 近似, 结合两阶段训练策略: 高斯基元直接着色初始化与G缓冲区延迟着色优化, 可输出反照率、金属度、粗糙度等 PBR 材质参数, 支持符合物理规律的高保真重光照应用. 实验结果表明, 该方法在 PSNR、SSIM、LPIPS 等指标上优于主流对比方法, 能较好地输出文物精细几何细节与材质特性, 支持高保真重光照应用, 为文物数字化保护提供可靠技术支撑.
Abstract:Cultural relic digitization is crucial for cultural heritage protection and continuity, with 3D reconstruction and material decomposition serving as key technologies for effectively restoring geometric morphology and diverse material properties. Existing methods often produce blurred geometric reconstruction due to specular reflections and insufficient material decomposition accuracy when handling multi-material relics (e.g., metals, ceramics). To address this issue, this study proposes a 3D reconstruction and material decomposition method for cultural relics based on 2D Gaussian splatting (2DGS). Depth and normal priors from large-scale visual foundation models are fused, and geometric reconstruction is optimized using a multi-constraint loss function to mitigate multi-view consistency failure caused by specular interference. A physically-based rendering (PBR) framework with split-sum approximation is adopted, combined with a two-stage training strategy: Gaussian primitive direct shading initialization and G-buffer deferred shading optimization, which outputs PBR material parameters including albedo, metalness, and roughness, and supports physically consistent high-fidelity relighting applications. Experimental results show that the proposed method outperforms mainstream counterparts in PSNR, SSIM, and LPIPS, while effectively recovering fine geometric details and material characteristics of cultural relics, supporting high-fidelity relighting applications, and providing reliable technical support for cultural relic digitization.
文章编号:     中图分类号:    文献标志码:
基金项目:中央在川高校院所“聚源兴川”项目(2024ZHCG0190); 四川省科技计划(2024NS-FTD0044); 四川省科技成果转移转化示范项目(2024ZHCG0176)
引用文本:
杨星塬,齐宏,戈文一,胡靖,魏敏.基于2D高斯泼溅的文物三维重建与材质分解.计算机系统应用,2026,35(8):175-184
YANG Xing-Yuan,QI Hong,GE Wen-Yi,HU Jing,WEI Min.3D Reconstruction and Material Decomposition of Cultural Relics Based on 2D Gaussian Splatting.COMPUTER SYSTEMS APPLICATIONS,2026,35(8):175-184