POLIMI-ITW-S: A large-scale dataset for human activity recognition in the wild

Human activity recognition is attracting increasing research attention. Many activity recognition datasets have been cre-ated to support the development and evaluation of new al-gorithms. Given the lack of datasets collected in real environ-ments (In The Wild) to support human activity recognition in public spaces, we introduce a large-scale video dataset for activity recognition In The Wild: POLIMI-ITW-S. The fully labeled dataset consists of 22,161 RGB video clips (about 46 h) including 37 activity classes performed by 50 K+ sub-jects in real shopping malls. We evaluated the state-of-the-art models on this dataset and get relatively low accuracy. We release the dataset including the annotations composed by person tracking bounding boxes, 2-D skeleton, and ac-tivity labels for research use at: https://airlab.deib.polimi.it/ polimi- itw- s- a- shopping- mall- dataset-in -the -wild .(c) 2022 Published by Elsevier Inc. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )