Given a short query with keyphrases about a research idea in 2019 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 want to learn a surface normal estimation network from synthetic data.

Keyphrases: surface normal estimation single image

Dataset description:
EDEN: EDEN (Enclosed garDEN) is a multimodal synthetic dataset, a dataset for nature-oriented applications. The dataset features more than 300K images captured from more than 100 garden models.
SUNCG: SUNCG is a large-scale dataset of synthetic 3D scenes with dense volumetric annotations. The dataset is currently not available.
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.
IntrA: IntrA is an open-access 3D intracranial aneurysm dataset that makes the application of points-based and mesh-based classification and segmentation models available. This dataset can be used to diagnose intracranial aneurysms and to extract the neck for a clipping operation in medicine and other areas of deep learning, such as normal estimation and surface reconstruction.

Options:- A: EDEN  B: SUNCG  C: ModelNet  D: IntrA
SUNCG