You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: A generative adversarial network that models moving objects in images without any supervision whatsoever.

Keyphrases: moving object detection images

Dataset description:
ISTD: The Image Shadow Triplets dataset (ISTD) is a dataset for shadow understanding that contains 1870 image triplets of shadow image, shadow mask, and shadow-free image.
Raindrop: Raindrop is a set of image pairs, where each pair contains exactly the same background scene, yet one is degraded by raindrops and the other one is free from raindrops. To obtain this, the images are captured through two pieces of exactly the same glass: one sprayed with water, and the other is left clean.
FDF: A diverse dataset of human faces, including unconventional poses, occluded faces, and a vast variability in backgrounds.
FBMS: The Freiburg-Berkeley Motion Segmentation Dataset (FBMS-59) is an extension of the BMS dataset with 33 additional video sequences. A total of 720 frames is annotated.
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.
TAO: TAO is a federated dataset for Tracking Any Object, containing 2,907 high resolution videos, captured in diverse environments, which are half a minute long on average. A bottom-up approach was used for discovering a large vocabulary of 833 categories, an order of magnitude more than prior tracking benchmarks.

Options:- A: ISTD  B: Raindrop  C: FDF  D: FBMS  E: DAVIS  F: TAO
["FBMS", "DAVIS"]