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: A network that learns to estimate 3D shapes and viewpoints of objects from single RGB images

Keyphrases: shape estimation viewpoint prediction images

Dataset description:
InterHand2.6M: The InterHand2.6M dataset is a large-scale real-captured dataset with accurate GT 3D interacting hand poses, used for 3D hand pose estimation The dataset contains 2.6M labeled single and interacting hand frames.
Kitchen Scenes: Kitchen Scenes is a multi-view RGB-D dataset of nine kitchen scenes, each containing several objects in realistic cluttered environments including a subset of objects from the BigBird dataset. The viewpoints of the scenes are densely sampled and objects in the scenes are annotated with bounding boxes and in the 3D point cloud.
T-LESS: T-LESS is a dataset for estimating the 6D pose, i.e. translation and rotation, of texture-less rigid objects.
ShapeNet: ShapeNet is a large scale repository for 3D CAD models developed by researchers from Stanford University, Princeton University and the Toyota Technological Institute at Chicago, USA. The repository contains over 300M models with 220,000 classified into 3,135 classes arranged using WordNet hypernym-hyponym relationships.

Options:- A: InterHand2.6M  B: Kitchen Scenes  C: T-LESS  D: ShapeNet
ShapeNet