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We develop a novel framework for single-scene video anomaly localization that allows for human-understandable reasons for the decisions the system makes.
Learning patterns of activity using real-time tracking
Chris Stauffer and W. Eric L. Grimson · 2000
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A duality based approach for realtime tv-l 1 optical flow
Christopher Zach, Thomas Pock, and Horst Bischof · 2007
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Robust real-time unusual event detection using multiple fixed-location monitors
Amit Adam, Ehud Rivlin, Ilan Shimshoni, and Daviv Reinitz · 2008
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Anomaly detection: A survey
Varun Chandola, Arindam Banerjee, and Vipin Kumar · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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Abnormal crowd behavior detection using social force model
Ramin Mehran, Alexis Oyama, and Mubarak Shah · 2009
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Anomaly detection in crowded scenes
Vijay Mahadevan, Weixin Li, Viral Bhalodia, and Nuno Vasconcelos · 2010
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Video anomaly identification
Venkatesh Saligrama, Janusz Konrad, and Pierre-Marc Jodoin · 2010
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Chaotic invariants of lagrangian particle trajectories for anomaly detection in crowded scenes
Shandong Wu, Brian E Moore, and Mubarak Shah · 2010
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Video parsing for abnormality detection
Borislav Antić and Björn Ommer · 2011
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Video anomaly detection based on local statistical aggregates
Venkatesh Saligrama and Zhu Chen · 2012
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Abnormal event detection in crowded scenes using sparse representation
Yang Cong, Junsong Yuan, and Ji Liu · 2013
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Anomaly detection and localization in crowded scenes
Weixin Li, Vijay Mahadevan, and Nuno Vasconcelos · 2013
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Abnormal event detection at 150 fps in matlab
Cewu Lu, Jianping Shi, and Jiaya Jia · 2013
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Anomaly detection in crowded scenes using dense trajectories
Ke Ma, Michael Doescher, and Christopher Bodden · 2015
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Learning deep representations of appearance and motion for anomalous event detection
Dan Xu, Elisa Ricci, Yan Yan, Jingkuan Song, and Nicu Sebe · 2015
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Learning temporal regularity in video sequences
Mahmudul Hasan, Jonghyun Choi, Jan Neumann, Amit K Roy-Chowdhury, and Larry S Davis · 2016
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Exemplar learning for extremely efficient anomaly detection in real-valued time series
Michael Jones, Daniel Nikovski, Makoto Imamura, and Takahisa Hirata · 2016
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Comput. Vis. Image Underst
Detecting anomalous events in videos by learning deep representations of appearance and motion · 2017
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Joint detection and recounting of abnormal events by learning deep generic knowledge
Ryota Hinami, Tao Mei, and Shin’ichi Satoh · 2017
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A revisit of sparse coding based anomaly detection in stacked rnn framework
Weixin Luo, Wen Liu, and Shenghua Gao · 2017
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Abnormal event detection in videos using generative adversarial nets
Mahdyar Ravanbakhsh, Moin Nabi, Enver Sangineto, Lucio Marcenaro, Carlo Regazzoni, and Nicu Sebe · 2017
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Deep-cascade: Cascading 3d deep neural networks for fast anomaly detection and localization in crowded scenes
Dual discriminator generative adversarial network for video anomaly detection
Fei Dong, Yu Zhang, and Xiushan Nie · 2020
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Any-shot sequential anomaly detection in surveillance videos
Keval Doshi and Yasin Yilmaz · 2020
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Continual learning for anomaly detection in surveillance videos
Keval Doshi and Yasin Yilmaz · 2020
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Few-shot scene-adaptive anomaly detection
Yiwei Lu, Frank Yu, Mahesh Kumar Krishna Reddy, and Yang Wang · 2020
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Learning memory-guided normality for anomaly detection
Hyunjong Park, Jongyoun Noh, and Bumsub Ham · 2020
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Street scene: A new dataset and evaluation protocol for video anomaly detection
Bharathkumar Ramachandra and Michael Jones · 2020
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Mohammad Sabokrou, Mohsen Fayyaz, Mahmood Fathy, and Reinhard Klette · 2017
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Deep appearance features for abnormal behavior detection in video
Sorina Smeureanu, Radu Tudor Ionescu, Marius Popescu, and Bogdan Alexe · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Future frame prediction for anomaly detection–a new baseline
Wen Liu, Weixin Luo, Dongze Lian, and Shenghua Gao · 2018
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
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Mio-tcd: A new benchmark dataset for vehicle classification and localization
Zhiming Luo, Frederic Branchaud-Charron, Carl Lemaire, Janusz Konrad, Shaozi Li, Akshaya Mishra, Andrew Achkar, Justin Eichel, and Pierre-Marc Jodoin · 2018
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Plug-and-play cnn for crowd motion analysis: An application in abnormal event detection
Mahdyar Ravanbakhsh, Moin Nabi, Hossein Mousavi, Enver Sangineto, and Nicu Sebe · 2018
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Learning a distance function with a siamese network to localize anomalies in videos
Bharathkumar Ramachandra, Michael Jones, and Ranga Vatsavai · 2020
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A survey of single-scene video anomaly detection
Bharathkumar Ramachandra, Michael Jones, and Ranga Raju Vatsavai · 2020
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Synthetic temporal anomaly guided end-to-end video anomaly detection
Marcella Astrid, Muhammad Zaigham Zaheer, and Seung-Ik Lee · 2021
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An efficient approach for anomaly detection in traffic videos
Keval Doshi and Yasin Yilmaz · 2021
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Anomaly detection in video via self-supervised and multi-task learning
Mariana-Iuliana Georgescu, Antonio Barbalau, Radu Tudor Ionescu, Fahad Shahbaz Khan, Marius Popescu, and Mubarak Shah · 2021
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A background-agnostic framework with adversarial training for abnormal event detection in video
Mariana Iuliana Georgescu, Radu Ionescu, Fahad Shahbaz Khan, Marius Popescu, and Mubarak Shah · 2021
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A hybrid video anomaly detection framework via memory-augmented flow reconstruction and flow-guided frame prediction
Zhian Liu, Yongwei Nie, Chengjiang Long, Qing Zhang, and Guiqing Li · 2021
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Self-supervised predictive convolutional attentive block for anomaly detection
Nicolae-Catalin Ristea, Neelu Madan, Radu Tudor Ionescu, Kamal Nasrollahi, Fahad Shahbaz Khan, Thomas B Moeslund, and Mubarak Shah · 2021
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Video anomaly detection method based on future frame prediction and attention mechanism
Chenxu Wang, Yanxin Yao, and Han Yao · 2021
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An explainable and efficient deep learning framework for video anomaly detection
Chongke Wu, Sicong Shao, Cihan Tunc, Pratik Satam, and Salim Hariri · 2021
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