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/
@article{arxiv.2404.05641,
title = {3D-COCO: extension of MS-COCO dataset for image detection and 3D reconstruction modules},
author = {Maxence Bideaux and Alice Phe and Mohamed Chaouch and Bertrand Luvison and Quoc-Cuong Pham},
journal= {arXiv preprint arXiv:2404.05641},
year = {2024}
}