Given a short query with keyphrases about a research idea in 2020 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 study aimed at evaluating how strongly the scanpaths generated with unsupervised gravitational models appear

Keyphrases: saliency prediction scanpath similarity images

Dataset description:
CAT2000: Includes 4000 images; 200 from each of 20 categories covering different types of scenes such as Cartoons, Art, Objects, Low resolution images, Indoor, Outdoor, Jumbled, Random, and Line drawings.
Libri-Adapt: Libri-Adapt aims to support unsupervised domain adaptation research on speech recognition models.
SemArt: SemArt is a multi-modal dataset for semantic art understanding. SemArt is a collection of fine-art painting images in which each image is associated to a number of attributes and a textual artistic comment, such as those that appear in art catalogues or museum collections.
GEM: Generation, Evaluation, and Metrics (GEM) is a benchmark environment for Natural Language Generation with a focus on its Evaluation, both through human annotations and automated Metrics. GEM aims to:   measure NLG progress across 13 datasets spanning many NLG tasks and languages.

Options:- A: CAT2000  B: Libri-Adapt  C: SemArt  D: GEM
CAT2000