Given a short query with keyphrases about a research idea in 2019 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: A method for jointly localising container-like objects and estimating their dimensions

Keyphrases: 3d object localisation dimension estimation rgb

Dataset description:
ISTD: The Image Shadow Triplets dataset (ISTD) is a dataset for shadow understanding that contains 1870 image triplets of shadow image, shadow mask, and shadow-free image.
FAT: Falling Things (FAT) is a dataset for advancing the state-of-the-art in object detection and 3D pose estimation in the context of robotics. It consists of generated photorealistic images with accurate 3D pose annotations for all objects in 60k images.
OCID: Developing robot perception systems for handling objects in the real-world requires computer vision algorithms to be carefully scrutinized with respect to the expected operating domain. This demands large quantities of ground truth data to rigorously evaluate the performance of algorithms.
COCO: The MS COCO (Microsoft Common Objects in Context) dataset is a large-scale object detection, segmentation, key-point detection, and captioning dataset. The dataset consists of 328K images.

Options:- A: ISTD  B: FAT  C: OCID  D: COCO
COCO