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: We propose a deep CVAE based approach to synthesize

Keyphrases: monocular 3d human-pose estimation static images

Dataset description:
iHarmony4: iHarmony4 is a synthesized dataset for Image Harmonization. It contains 4 sub-datasets: HCOCO, HAdobe5k, HFlickr, and Hday2night (based on COCO, Adobe5k, Flickr, day2night datasets respectively), each of which contains synthesized composite images, foreground masks of composite images and corresponding real images.
Slakh2100: The Synthesized Lakh (Slakh) Dataset is a dataset for audio source separation that is synthesized from the Lakh MIDI Dataset v0.1 using professional-grade sample-based virtual instruments. This first release of Slakh, called Slakh2100, contains 2100 automatically mixed tracks and accompanying MIDI files synthesized using a professional-grade sampling engine.
MPII: The MPII Human Pose Dataset for single person pose estimation is composed of about 25K images of which 15K are training samples, 3K are validation samples and 7K are testing samples (which labels are withheld by the authors). The images are taken from YouTube videos covering 410 different human activities and the poses are manually annotated with up to 16 body joints.
D-HAZY: The D-HAZY dataset is generated from NYU depth indoor image collection. D-HAZY contains depth map for each indoor hazy image.

Options:- A: iHarmony4  B: Slakh2100  C: MPII  D: D-HAZY
MPII