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: This paper proposes an end-to-end convolutional network for boundary flow estimation in video sequences.

Keyphrases: boundary flow estimation video

Dataset description:
BSDS500: Berkeley Segmentation Data Set 500 (BSDS500) is a standard benchmark for contour detection. This dataset is designed for evaluating natural edge detection that includes not only object contours but also object interior boundaries and background boundaries.
iSUN: iSUN is a ground truth of gaze traces on images from the SUN dataset. The collection is partitioned into 6,000 images for training, 926 for validation and 2,000 for test.
DeeperForensics-1.0: DeeperForensics-1.0 represents the largest face forgery detection dataset by far, with 60,000 videos constituted by a total of 17.6 million frames, 10 times larger than existing datasets of the same kind. The full dataset includes 48,475 source videos and 11,000 manipulated videos.
DPED: A large-scale dataset that consists of real photos captured from three different phones and one high-end reflex camera.

Options:- A: BSDS500  B: iSUN  C: DeeperForensics-1.0  D: DPED
BSDS500