Digital Twin Catalog：一个大规模的照片级真实感3D物体数字孪生数据集
Digital Twin Catalog: A Large-Scale Photorealistic 3D Object Digital Twin Dataset
AI总结：
针对缺乏数字孪生质量的大规模3D重建数据集及自我中心视角评估基准的问题，研究团队推出包含2000个高质量3D物体与多设备拍摄图像的DTC数据集，为相关方法的评估与改进提供支撑。
摘要：
我们推出了Digital Twin Catalog（DTC，数字孪生目录），这是一个全新的大规模照片级真实感3D物体数字孪生数据集。3D物体的数字孪生是指对物理物体的高度精细、在视觉上几乎无法区分的虚拟表征，能够精准捕捉其形状、外观、物理属性及其他特征。近年来，基于神经渲染的3D重建和逆渲染技术取得了显著进展，大幅提升了3D物体重建的质量。尽管有这些进步，目前仍缺乏具备数字孪生质量的大规模真实世界数据集与基准，无法对不同重建方法的性能进行定量评估和比较，也难以通过训练或微调来提升重建质量。此外，为了推动3D数字孪生创建的普及，必须将创建技术与AR眼镜等下一代以自我为中心的计算平台相结合。目前，尚无可用数据集来评估使用以自我为中心的拍摄图像进行3D物体重建的效果。为填补这些空白，DTC数据集包含2000个经扫描得到的数字孪生质量的3D物体，同时配有分别使用数码单反相机和以自我为中心的AR眼镜在不同光照条件下拍摄的图像序列。该数据集为3D数字孪生创建任务建立了首个全面的真实世界评估基准，为对比和改进现有重建方法提供了坚实基础。DTC数据集已在https://www.projectaria.com/datasets/dtc/ 发布，我们还将开源基线评估结果。
英文摘要：
We introduce the Digital Twin Catalog (DTC), a new large-scale photorealistic 3D object digital twin dataset. A digital twin of a 3D object is a highly detailed, virtually indistinguishable representation of a physical object, accurately capturing its shape, appearance, physical properties, and other attributes. Recent advances in neural-based 3D reconstruction and inverse rendering have significantly improved the quality of 3D object reconstruction. Despite these advancements, there remains a lack of a large-scale, digital twin-quality real-world dataset and benchmark that can quantitatively assess and compare the performance of different reconstruction methods, as well as improve reconstruction quality through training or fine-tuning. Moreover, to democratize 3D digital twin creation, it is essential to integrate creation techniques with next-generation egocentric computing platforms, such as AR glasses. Currently, there is no dataset available to evaluate 3D object reconstruction using egocentric captured images. To address these gaps, the DTC dataset features 2,000 scanned digital twin-quality 3D objects, along with image sequences captured under different lighting conditions using DSLR cameras and egocentric AR glasses. This dataset establishes the first comprehensive real-world evaluation benchmark for 3D digital twin creation tasks, offering a robust foundation for comparing and improving existing reconstruction methods. The DTC dataset is already released at https://www.projectaria.com/datasets/dtc/ and we will also make the baseline evaluations open-source.
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。
