构建100亿点的大规模文化地标数据集，支持高精度3D场景重建。
CULTURE3D: A Large-Scale and Diverse Dataset of Cultural Landmarks and Terrains for Gaussian-Based Scene Rendering
- 基于4.1万张航拍图像构建100亿点的精细3D数据集。
- 覆盖20个全球文化地标，含大英、金字塔等，细节丰富。
- 支持高斯溅射模型测试，适合3D重建与生成研究者使用。
当前先进的3D重建模型在构建超大规模室外场景时受限于缺乏足够规模和细节的数据集。本文提出一个包含100亿点的超大规模细粒度数据集，由41,006张无人机拍摄的高分辨率航拍图像组成，涵盖全球20个具有文化重要性的场景，如剑桥大学主建筑、埃及金字塔和故宫。相比现有数据集，本数据集在规模和细节上均有显著提升，特别适用于细粒度3D应用。每个场景均具备精确的空间布局与完整的结构信息，支持高精度3D重建任务。通过这些高精度图像重建环境，数据集输出符合广泛使用的COLMAP格式，为评估前沿大规模高斯溅射方法建立了新基准。数据集灵活性强，支持模型插件与创新，推动未来3D技术突破。所有数据与代码将开源供社区使用。
原文摘要 · Abstract (English)
Current state-of-the-art 3D reconstruction models face limitations in building extra-large scale outdoor scenes, primarily due to the lack of sufficiently large-scale and detailed datasets. In this paper, we present a extra-large fine-grained dataset with 10 billion points composed of 41,006 drone-captured high-resolution aerial images, covering 20 diverse and culturally significant scenes from worldwide locations such as Cambridge Uni main buildings, the Pyramids, and the Forbidden City Palace. Compared to existing datasets, ours offers significantly larger scale and higher detail, uniquely suited for fine-grained 3D applications. Each scene contains an accurate spatial layout and comprehensive structural information, supporting detailed 3D reconstruction tasks. By reconstructing environments using these detailed images, our dataset supports multiple applications, including outputs in the widely adopted COLMAP format, establishing a novel benchmark for evaluating state-of-the-art large-scale Gaussian Splatting methods.The dataset's flexibility encourages innovations and supports model plug-ins, paving the way for future 3D breakthroughs. All datasets and code will be open-sourced for community use.
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