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AnomalyNet: An Anomaly Detection Network for Video Surveillance, IEEE Trans Information Forensics and Security 2019.

Python 100.00%

anomalynet's Introduction

AnomalyNet

  • Joey Tianyi Zhou, Jiawei Du, Hongyuan Zhu, Xi Peng, Yong Liu, Rick Siow Mong Goh, AnomalyNet: An Anomaly Detection Network for Video Surveillance, IEEE Trans Information Forensics and Security (TIFS), vol: 14, no:10, 2537-2550, OCT., 2019. DOI: 10.1109/TIFS.2019.2900907.
  • Joey Tianyi Zhou, Kai Di, Jiawei Du, Xi Peng, et al., SC2Net: Sparse LSTMs for Sparse Coding, the 32th AAAI Conference on Artificial Intelligence (AAAI'18), New Orleans, Louisiana, 2-7 Feb., 2018.

Requirement

  • numpy 1.10+
  • matplotlib 1.8+
  • tensorflow 1.0+
  • python 2.7
  • scikit-learn 1.16+

Usage

DI input for algorithm is generated by di_gen.py. The network traing is based on our previous project SC2Net.

If you feel this project helpful to your research, please cite the following paper

@paper{AAAI1816822,
	author = {Joey Tianyi Zhou and Kai Di and Jiawei Du and Xi Peng and Hao Yang and Sinno Jialin Pan and Ivor Tsang and Yong Liu and Zheng Qin and Rick Siow Mong Goh},
	title = {SC2Net: Sparse LSTMs for Sparse Coding},
	conference = {AAAI Conference on Artificial Intelligence},
	year = {2018},
	keywords = {sparse representation; LSTM; RNN; model-based optimization},
	url = {https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16822}
}
}

and

@ARTICLE{8649753author = {Joey Tianyi Zhou and Jiawei Du  and Hongyuan Zhu and Xi Peng and Yong Liu and Rick Siow Mong Goh},
journal={IEEE Transactions on Information Forensics and Security}title={AnomalyNet: An Anomaly Detection Network for Video Surveillance}year={2019}volume={14}number={10}pages={2537-2550}doi={10.1109/TIFS.2019.2900907}ISSN={1556-6013}month={Oct},}

anomalynet's People

Contributors

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Stargazers

Renjie Liang avatar Mihai avatar  avatar zuble avatar  avatar  avatar Tianhang Wang avatar Tonyfy avatar  avatar Jinglin Xu avatar Isaac avatar TIAN YE avatar  avatar  avatar CCHong avatar  avatar

Watchers

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