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：我们提出3D-COCO，这是原始MS-COCO数据集的扩展版本，提供了三维模型及二维-三维对齐标注。3D-COCO旨在实现可通过文本、二维图像和三维CAD模型查询配置的计算机视觉任务，如三维重建或图像检测。我们利用从ShapeNet和Objaverse收集的28K个三维模型，对现有MS-COCO数据集进行补充。通过基于IoU的方法，将每个MS-COCO标注与最优三维模型匹配，实现二维-三维对齐。3D-COCO的开源特性开创了先河，将为三维相关领域的新研究铺平道路。该数据集及其源代码可在https://kalisteo.cea.fr/index.php/coco3d-object-detection-and-reconstruction/获取。