InHARD (Industrial Human Action Recognition Dataset in the Context of Industrial Collaborative Robotics)

We introduce a RGB+S dataset named “Industrial Human Action Recognition Dataset” (InHARD) from a real-world setting for industrial human action recognition with over 2 million frames, collected from 16 distinct subjects. This dataset contains 13 different industrial action classes and over 4800 action samples. The introduction of this dataset should allow us the study and development of various learning techniques for the task of human actions analysis inside industrial environments involving human robot collaborations.

More details on the dataset at Zenodo: https://zenodo.org/records/4003541
Github: https://github.com/vhavard/InHARD
Publication: https://doi.org/10.1109/ICHMS49158.2020.9209531