  This notebook paper presents an overview and comparative analysis of our
system designed for activity detection in extended videos (ActEV-PC) in
ActivityNet Challenge 2019. Specifically, we exploit person/vehicle detections
in spatial level and action localization in temporal level for action detection
in surveillance videos. The mechanism of different tubelet generation and model
decomposition methods are studied as well. The detection results are finally
predicted by late fusing the results from each component.
