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: We annotate several in-the-wild [DATASET] datasets with pose and occlusion attributes. To address the

Keyphrases: facial expression recognition images

Dataset description:
COFW: The Caltech Occluded Faces in the Wild (COFW) dataset is designed to present faces in real-world conditions. Faces show large variations in shape and occlusions due to differences in pose, expression, use of accessories such as sunglasses and hats and interactions with objects (e.g.
WFLW: The Wider Facial Landmarks in the Wild or WFLW database contains 10000 faces (7500 for training and 2500 for testing) with 98 annotated landmarks. This database also features rich attribute annotations in terms of occlusion, head pose, make-up, illumination, blur and expressions.
AffectNet: AffectNet is a large facial expression dataset with around 0.4 million images manually labeled for the presence of eight (neutral, happy, angry, sad, fear, surprise, disgust, contempt) facial expressions along with the intensity of valence and arousal.
SFEW: The Static Facial Expressions in the Wild (SFEW) dataset is a dataset for facial expression recognition. It was created by selecting static frames from the AFEW database by computing key frames based on facial point clustering.
Aff-Wild: Aff-Wild is a dataset for emotion recognition from facial images in a variety of head poses, illumination conditions and occlusions.
FER2013: Fer2013 contains approximately 30,000 facial RGB images of different expressions with size restricted to 48×48, and the main labels of it can be divided into 7 types: 0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral. The Disgust expression has the minimal number of images – 600, while other labels have nearly 5,000 samples each.

Options:- A: COFW  B: WFLW  C: AffectNet  D: SFEW  E: Aff-Wild  F: FER2013
["AffectNet", "SFEW", "FER2013"]