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: I want to train a video classification model with the ability to learn to identify discriminative and informative frames for

Keyphrases: action recognition video

Dataset description:
TrackingNet: TrackingNet is a large-scale tracking dataset consisting of videos in the wild. It has a total of 30,643 videos split into 30,132 training videos and 511 testing videos, with an average of 470,9 frames.
UMDFaces: UMDFaces is a face dataset divided into two parts:   Still Images - 367,888 face annotations for 8,277 subjects. Video Frames - Over 3.7 million annotated video frames from over 22,000 videos of 3100 subjects.
UCF101: UCF101 dataset is an extension of UCF50 and consists of 13,320 video clips, which are classified into 101 categories. These 101 categories can be classified into 5 types (Body motion, Human-human interactions, Human-object interactions, Playing musical instruments and Sports).
DeepFish: DeepFish as a benchmark suite with a large-scale dataset to train and test methods for several computer vision tasks. The dataset consists of approximately 40 thousand images collected underwater from 20 habitats in the marine environments of tropical Australia.
Composable activities dataset: The Composable activities dataset consists of 693 videos that contain activities in 16 classes performed by 14 actors. Each activity is composed of 3 to 11 atomic actions.
ImageNet: The ImageNet dataset contains 14,197,122 annotated images according to the WordNet hierarchy. Since 2010 the dataset is used in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), a benchmark in image classification and object detection.

Options:- A: TrackingNet  B: UMDFaces  C: UCF101  D: DeepFish  E: Composable activities dataset  F: ImageNet
["UCF101", "ImageNet"]