Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I am learning to classify 3D shapes in an unsupervised manner.

Keyphrases: shape classification point cloud

Dataset description:
3D Shapes Dataset: 3dshapes is a dataset of 3D shapes procedurally generated from 6 ground truth independent latent factors. These factors are floor colour, wall colour, object colour, scale, shape and orientation.
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.
3DFAW: 3DFAW contains 23k images with 66 3D face keypoint annotations.
2D-3D-S: The 2D-3D-S dataset provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. It covers over 6,000 m2 collected in 6 large-scale indoor areas that originate from 3 different buildings.

Options:- A: 3D Shapes Dataset  B: ModelNet  C: 3DFAW  D: 2D-3D-S
ModelNet