Given a short query with keyphrases about a research idea in 2020 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: This paper proposes a domain adaptation approach to eliminate estimation errors in the background areas, which is

Keyphrases: pixel-level crowd understanding images

Dataset description:
ImageCLEF-DA: The ImageCLEF-DA dataset is a benchmark dataset for ImageCLEF 2014 domain adaptation challenge, which contains three domains: Caltech-256 (C), ImageNet ILSVRC 2012 (I) and Pascal VOC 2012 (P). For each domain, there are 12 categories and 50 images in each category.
Libri-Adapt: Libri-Adapt aims to support unsupervised domain adaptation research on speech recognition models.
ShanghaiTech: The Shanghaitech dataset is a large-scale crowd counting dataset. It consists of 1198 annotated crowd images.
TableBank: To address the need for a standard open domain table benchmark dataset, the author propose a novel weak supervision approach to automatically create the TableBank, which is orders of magnitude larger than existing human labeled datasets for table analysis. Distinct from traditional weakly supervised training set, our approach can obtain not only large scale but also high quality training data.

Options:- A: ImageCLEF-DA  B: Libri-Adapt  C: ShanghaiTech  D: TableBank
ShanghaiTech