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 propose a multistage model to address the face alignment task in unconstrained scenarios. The model first utilizes a spatial transformer

Keyphrases: face alignment images unconstrained

Dataset description:
iFakeFaceDB: iFakeFaceDB is a face image dataset for the study of synthetic face manipulation detection, comprising about 87,000 synthetic face images generated by the Style-GAN model and transformed with the GANprintR approach. All images were aligned and resized to the size of 224 x 224.
PG-19: A new open-vocabulary language modelling benchmark derived from books.
AFW: AFW (Annotated Faces in the Wild) is a face detection dataset that contains 205 images with 468 faces. Each face image is labeled with at most 6 landmarks with visibility labels, as well as a bounding box.
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.
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.
UFDD: Unconstrained Face Detection Dataset (UFDD) aims to fuel further research in unconstrained face detection.

Options:- A: iFakeFaceDB  B: PG-19  C: AFW  D: WFLW  E: COFW  F: UFDD
["AFW", "WFLW", "COFW"]