We introduce 3D-COCO, an extension of the original MS-COCO dataset providing 3D models and 2D-3D alignment annotations. 3D-COCO was designed to achieve computer vision tasks such as 3D reconstruction or image detection configurable with textual, 2D image, and 3D CAD model queries. We complete the existing MS-COCO dataset with 28K 3D models collected on ShapeNet and Objaverse. By using an IoU-based method, we match each MS-COCO annotation with the best 3D models to provide a 2D-3D alignment. The open-source nature of 3D-COCO is a premiere that should pave the way for new research on 3D-related topics. The dataset and its source codes is available at https://kalisteo.cea.fr/index.php/coco3d-object-detection-and-reconstruction/

翻译：本文介绍3D-COCO——一个基于原始MS-COCO数据集扩展的、提供三维模型与二维-三维对齐标注的数据集。3D-COCO旨在支持可通过文本、二维图像及三维CAD模型查询配置的计算机视觉任务，例如三维重建或图像检测。我们通过从ShapeNet和Objaverse收集的28K个三维模型对现有MS-COCO数据集进行补充，并采用基于交并比的方法将每个MS-COCO标注与最优三维模型匹配，从而提供二维-三维对齐标注。3D-COCO的开源特性属首创，有望为三维相关领域的新研究开辟道路。数据集及其源代码可通过以下网址获取：https://kalisteo.cea.fr/index.php/coco3d-object-detection-and-reconstruction/