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: PointNet++ is an efficient and effective network for point set feature learning.

Keyphrases: point set feature learning clouds

Dataset description:
ModelNet: The ModelNet40 dataset contains synthetic object point clouds. As the most widely used benchmark for point cloud analysis, ModelNet40 is popular because of its various categories, clean shapes, well-constructed dataset, etc.
Decagon: Bio-decagon is a dataset for polypharmacy side effect identification problem framed as a multirelational link prediction problem in a two-layer multimodal graph/network of two node types: drugs and proteins. Protein-protein interaction network describes relationships between proteins.
Email-EU: EmailEU is a directed temporal network constructed from email exchanges in a large European research institution for a 803-day period. It contains 986 email addresses as nodes and 332,334 emails as edges with timestamps.
HIGGS Data Set: The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator.
ScanNet: ScanNet is an instance-level indoor RGB-D dataset that includes both 2D and 3D data. It is a collection of labeled voxels rather than points or objects.
BraTS 2017: The BRATS2017 dataset. It contains 285 brain tumor MRI scans, with four MRI modalities as T1, T1ce, T2, and Flair for each scan.
Goldfinch: Goldfinch is a dataset for fine-grained recognition challenges. It contains a list of bird, butterfly, aircraft, and dog categories with relevant Google image search and Flickr search URLs.

Options:- A: ModelNet  B: Decagon  C: Email-EU  D: HIGGS Data Set  E: ScanNet  F: BraTS 2017  G: Goldfinch
["ModelNet", "ScanNet"]