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 CNN-based domain adaptation tracker based on the CNNs.

Keyphrases: domain adaptation video

Dataset description:
McMaster: The McMaster dataset is a dataset for color demosaicing, which contains 18 cropped images of size 500×500.
MMED: Contains 25,165 textual news articles collected from hundreds of news media sites (e.g., Yahoo News, Google News, CNN News.) and 76,516 image posts shared on Flickr social media, which are annotated according to 412 real-world events.
VOT2017: VOT2017 is a Visual Object Tracking dataset for different tasks that contains 60 short sequences annotated with 6 different attributes.
OTB: Object Tracking Benchmark (OTB) is a visual tracking benchmark that is widely used to evaluate the performance of a visual tracking algorithm. The dataset contains a total of 100 sequences and each is annotated frame-by-frame with bounding boxes and 11 challenge attributes.
LAG: Includes 5,824 fundus images labeled with either positive glaucoma (2,392) or negative glaucoma (3,432).
AFLW2000-3D: AFLW2000-3D is a dataset of 2000 images that have been annotated with image-level 68-point 3D facial landmarks. This dataset is used for evaluation of 3D facial landmark detection models.
G3D: The Gaming 3D Dataset (G3D) focuses on real-time action recognition in a gaming scenario. It contains 10 subjects performing 20 gaming actions: “punch right”, “punch left”, “kick right”, “kick left”, “defend”, “golf swing”, “tennis swing forehand”, “tennis swing backhand”, “tennis serve”, “throw bowling ball”, “aim and fire gun”, “walk”, “run”, “jump”, “climb”, “crouch”, “steer a car”, “wave”, “flap” and “clap”.

Options:- A: McMaster  B: MMED  C: VOT2017  D: OTB  E: LAG  F: AFLW2000-3D  G: G3D
["VOT2017", "OTB"]