Given a short query with keyphrases about a research idea in 2017 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: I want to learn the correlation between visual and textual modalities and apply it to improve the image search

Keyphrases: image search images text

Dataset description:
WebVision: The WebVision dataset is designed to facilitate the research on learning visual representation from noisy web data. It is a large scale web images dataset that contains more than 2.4 million of images crawled from the Flickr website and Google Images search.
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.
Flightmare Simulator: Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation. Those two components are totally decoupled and can run independently from each other.
VQA-CP: The VQA-CP dataset was constructed by reorganizing VQA v2 such that the correlation between the question type and correct answer differs in the training and test splits. For example, the most common answer to questions starting with What sport… is tennis in the training set, but skiing in the test set.

Options:- A: WebVision  B: COCO  C: Flightmare Simulator  D: VQA-CP
COCO