用手机拍照就能3D还原文物，自动分割每件展品。
Gaussian Heritage: 3D Digitization of Cultural Heritage with Integrated Object Segmentation
- 结合新视角合成与高斯点阵，从普通照片生成3D模型。
- 无需人工标注，能准确分割场景中每件文物。
- 适合博物馆数字化，手机拍摄即能完成，成本低。
数字复刻实物对保护和传播有形文化遗产具有重要价值。然而，现有方法通常耗时、昂贵且需专业知识。本文提出一种仅使用RGB图像（如博物馆照片）生成场景3D复刻并提取每件感兴趣物品模型的流程。通过利用新视角合成和高斯点阵技术的进展，并对其进行改进以实现高效的3D分割。该方法无需人工标注，视觉输入可通过普通智能手机获取，兼具低成本与易部署性。本文提供了方法概述及对象分割准确性的基准评估。代码已公开于 https://mahtaabdn.github.io/gaussian_heritage.github.io/。
原文摘要 · Abstract (English)
The creation of digital replicas of physical objects has valuable applications for the preservation and dissemination of tangible cultural heritage. However, existing methods are often slow, expensive, and require expert knowledge. We propose a pipeline to generate a 3D replica of a scene using only RGB images (e.g. photos of a museum) and then extract a model for each item of interest (e.g. pieces in the exhibit). We do this by leveraging the advancements in novel view synthesis and Gaussian Splatting, modified to enable efficient 3D segmentation. This approach does not need manual annotation, and the visual inputs can be captured using a standard smartphone, making it both affordable and easy to deploy. We provide an overview of the method and baseline evaluation of the accuracy of object segmentation. The code is available at https://mahtaabdn.github.io/gaussian_heritage.github.io/.
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