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 present a deep architecture for predictive domain adaptation that uses a graph structure for incorporating information from auxiliary domains

Keyphrases: predictive domain adaptation images

Dataset description:
Dialogue State Tracking Challenge: The Dialog State Tracking Challenges 2 & 3 (DSTC2&3) were research challenge focused on improving the state of the art in tracking the state of spoken dialog systems. State tracking, sometimes called belief tracking, refers to accurately estimating the user's goal as a dialog progresses.
Office-Home: Office-Home is a benchmark dataset for domain adaptation which contains 4 domains where each domain consists of 65 categories. The four domains are: Art – artistic images in the form of sketches, paintings, ornamentation, etc.
CompCars: The Comprehensive Cars (CompCars) dataset contains data from two scenarios, including images from web-nature and surveillance-nature. The web-nature data contains 163 car makes with 1,716 car models.
Syn2Real: Syn2Real, a synthetic-to-real visual domain adaptation benchmark meant to encourage further development of robust domain transfer methods. The goal is to train a model on a synthetic "source" domain and then update it so that its performance improves on a real "target" domain, without using any target annotations.

Options:- A: Dialogue State Tracking Challenge  B: Office-Home  C: CompCars  D: Syn2Real
CompCars