English

vireoJD-MM at Activity Detection in Extended Videos

Computer Vision and Pattern Recognition 2019-06-21 v1
Authors: Fuchen Long , Qi Cai , Zhaofan Qiu , Zhijian Hou , Yingwei Pan , Ting Yao , Chong-Wah Ngo
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Abstract

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.

Keywords

activity detection extended videos person detection vehicle detection action localization tubelet generation late fusion

Cite

@article{arxiv.1906.08547,
  title  = {vireoJD-MM at Activity Detection in Extended Videos},
  author = {Fuchen Long and Qi Cai and Zhaofan Qiu and Zhijian Hou and Yingwei Pan and Ting Yao and Chong-Wah Ngo},
  journal= {arXiv preprint arXiv:1906.08547},
  year   = {2019}
}

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