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 real-time segmentation network for high accuracy segmentation.

Keyphrases: semantic segmentation video

Dataset description:
DAVIS: The Densely Annotation Video Segmentation dataset (DAVIS) is a high quality and high resolution densely annotated video segmentation dataset under two resolutions, 480p and 1080p. There are 50 video sequences with 3455 densely annotated frames in pixel level.
Cityscapes: Cityscapes is a large-scale database which focuses on semantic understanding of urban street scenes. It provides semantic, instance-wise, and dense pixel annotations for 30 classes grouped into 8 categories (flat surfaces, humans, vehicles, constructions, objects, nature, sky, and void).
BraTS 2015: The BraTS 2015 dataset is a dataset for brain tumor image segmentation. It consists of 220 high grade gliomas (HGG) and 54 low grade gliomas (LGG) MRIs.
Trans10K: A large-scale dataset for transparent object segmentation, named Trans10K, consisting of 10,428 images of real scenarios with carefully manual annotations, which are 10 times larger than the existing datasets.

Options:- A: DAVIS  B: Cityscapes  C: BraTS 2015  D: Trans10K
Cityscapes