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: In this paper, a novel group decision-making network is proposed for person re-identification.

Keyphrases: person re-identification images

Dataset description:
MARS: MARS (Motion Analysis and Re-identification Set) is a large scale video based person reidentification dataset, an extension of the Market-1501 dataset. It has been collected from six near-synchronized cameras.
CUHK02: CUHK02 is a dataset for person re-identification. It contains 1,816 identities from two disjoint camera views.
Covid-HeRA: Covid-HeRA is a dataset for health risk assessment and severity-informed decision making in the presence of COVID19 misinformation. It is a benchmark dataset for risk-aware health misinformation detection, related to the 2019 coronavirus pandemic.
VIPeR: The Viewpoint Invariant Pedestrian Recognition (VIPeR) dataset includes 632 people and two outdoor cameras under different viewpoints and light conditions. Each person has one image per camera and each image has been scaled to be 128×48 pixels.
CUHK03: The CUHK03 consists of 14,097 images of 1,467 different identities, where 6 campus cameras were deployed for image collection and each identity is captured by 2 campus cameras. This dataset provides two types of annotations, one by manually labelled bounding boxes and the other by bounding boxes produced by an automatic detector.

Options:- A: MARS  B: CUHK02  C: Covid-HeRA  D: VIPeR  E: CUHK03
["VIPeR", "CUHK03"]