CULTURE3D：一个用于基于高斯场景渲染的大规模且多样的文化地标与地形数据集
CULTURE3D: A Large-Scale and Diverse Dataset of Cultural Landmarks and Terrains for Gaussian-Based Scene Rendering
AI总结：
本文提出CULTURE3D，一个包含100亿个点、41,006张无人机航拍图像的超大规模细粒度3D数据集，覆盖20个全球文化地标，为大规模Gaussian Splatting方法提供了新基准并支持多种3D重建应用。
摘要：
当前最先进的3D重建模型在构建超大规模室外场景时面临局限，主要原因是缺乏足够大规模和详细的数据集。在本文中，我们提出了一个超大规模的细粒度数据集，包含100亿个点，由41,006张无人机拍摄的高分辨率航拍图像组成，覆盖了来自全球地点的20个多样且具有文化意义的场景，如剑桥大学主楼、金字塔和故宫宫殿。与现有数据集相比，我们的数据集提供了显著更大的规模和更高的细节，独特地适用于细粒度的3D应用。每个场景都包含精确的空间布局和全面的结构信息，支持详细的3D重建任务。通过使用这些详细图像重建环境，我们的数据集支持多种应用，包括以广泛采用的COLMAP格式输出，为评估最先进的大规模Gaussian Splatting方法建立了一个新的基准。数据集的灵活性鼓励创新并支持模型插件，为未来的3D突破铺平了道路。所有数据集和代码将开源供社区使用。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
