A dataset is crucial for model learning and evaluation. Choosing the right dataset to use or making a new dataset requires the knowledge of those that are available. In this work, we provide that knowledge, by reviewing twenty datasets that were published in the recent six years and that are directly related to object manipulation. We report on modalities, activities, and annotations for each individual dataset and give our view on its use for object manipulation. We also compare the datasets and summarize them. We conclude with our suggestion on future datasets.
@article{arxiv.1607.00442,
title = {Datasets on object manipulation and interaction: a survey},
author = {Yongqiang Huang and Yu Sun},
journal= {arXiv preprint arXiv:1607.00442},
year = {2016}
}