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: I want to automatically search an efficient network architecture for dense image prediction.

Keyphrases: semantic segmentation images

Dataset description:
Image and Video Advertisements: The Image and Video Advertisements collection consists of an image dataset of 64,832 image ads, and a video dataset of 3,477 ads. The data contains rich annotations encompassing the topic and sentiment of the ads, questions and answers describing what actions the viewer is prompted to take and the reasoning that the ad presents to persuade the viewer ("What should I do according to this ad, and why should I do it?
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.
Chickenpox Cases in Hungary: Chickenpox Cases in Hungary is a spatio-temporal dataset of weekly chickenpox (childhood disease) cases from Hungary. It can be used as a longitudinal dataset for benchmarking the predictive performance of spatiotemporal graph neural network architectures.
NAS-Bench-101: NAS-Bench-101 is the first public architecture dataset for NAS research. To build NASBench-101, the authors carefully constructed a compact, yet expressive, search space, exploiting graph isomorphisms to identify 423k unique convolutional architectures.

Options:- A: Image and Video Advertisements  B: COCO  C: Chickenpox Cases in Hungary  D: NAS-Bench-101
COCO