Training Adversarial Discriminators for Cross-Channel Abnormal Event Detection in Crowds
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Nicu Sebe | Enver Sangineto | Mahdyar Ravanbakhsh | Moin Nabi | N. Sebe | E. Sangineto | Mahdyar Ravanbakhsh | Moin Nabi
[1] Chuan Li,et al. Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks , 2016, ECCV.
[2] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Hossein Mousavi,et al. Crowd behavior representation: an attribute-based approach , 2016, SpringerPlus.
[4] Alessio Del Bue,et al. Temporal Poselets for Collective Activity Detection and Recognition , 2013, 2013 IEEE International Conference on Computer Vision Workshops.
[5] Kristen Grauman,et al. Observe locally, infer globally: A space-time MRF for detecting abnormal activities with incremental updates , 2009, CVPR.
[6] Mahmood Fathy,et al. Deep-Cascade: Cascading 3D Deep Neural Networks for Fast Anomaly Detection and Localization in Crowded Scenes , 2017, IEEE Transactions on Image Processing.
[7] Nuno Vasconcelos,et al. Anomaly detection in crowded scenes , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[8] Jonghyun Choi,et al. Learning Temporal Regularity in Video Sequences , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Mubarak Shah,et al. Abnormal crowd behavior detection using social force model , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[10] Junsong Yuan,et al. Sparse reconstruction cost for abnormal event detection , 2011, CVPR 2011.
[11] K. Grauman,et al. Observe locally, infer globally: A space-time MRF for detecting abnormal activities with incremental updates , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[12] Venkatesh Saligrama,et al. Video anomaly detection based on local statistical aggregates , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[13] Nicu Sebe,et al. Detecting anomalous events in videos by learning deep representations of appearance and motion , 2017, Comput. Vis. Image Underst..
[14] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[15] Thomas Brox,et al. High Accuracy Optical Flow Estimation Based on a Theory for Warping , 2004, ECCV.
[16] Benjamin Schrauwen,et al. Factoring Variations in Natural Images with Deep Gaussian Mixture Models , 2014, NIPS.
[17] Nicu Sebe,et al. Abnormal event detection in videos using generative adversarial nets , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[18] Cewu Lu,et al. Abnormal Event Detection at 150 FPS in MATLAB , 2013, 2013 IEEE International Conference on Computer Vision.
[19] Hamid R. Rabiee,et al. Novel dataset for fine-grained abnormal behavior understanding in crowd , 2016, 2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
[20] Hamid R. Rabiee,et al. Detection and localization of crowd behavior using a novel tracklet-based model , 2018, Int. J. Mach. Learn. Cybern..
[21] Carlo S. Regazzoni,et al. Fast but Not Deep: Efficient Crowd Abnormality Detection with Local Binary Tracklets , 2018, 2018 15th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
[22] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[23] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[24] Nuno Vasconcelos,et al. Anomaly Detection and Localization in Crowded Scenes , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[25] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[26] Yoshua Bengio,et al. Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Alessandro Perina,et al. Crowd motion monitoring using tracklet-based commotion measure , 2015, 2015 IEEE International Conference on Image Processing (ICIP).
[28] Mahmood Fathy,et al. Video anomaly detection and localisation based on the sparsity and reconstruction error of auto-encoder , 2016 .
[29] Nicu Sebe,et al. Emotion-Based Crowd Representation for Abnormality Detection , 2016, ArXiv.
[30] Xiaoqiang Lu,et al. Learning deep event models for crowd anomaly detection , 2017, Neurocomputing.
[31] Alessandro Perina,et al. Analyzing Tracklets for the Detection of Abnormal Crowd Behavior , 2015, 2015 IEEE Winter Conference on Applications of Computer Vision.
[32] Mahmood Fathy,et al. Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes , 2016, Comput. Vis. Image Underst..
[33] Nicu Sebe,et al. Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection , 2016, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[34] Jiwen Lu,et al. PCANet: A Simple Deep Learning Baseline for Image Classification? , 2014, IEEE Transactions on Image Processing.
[35] Nicu Sebe,et al. Abnormal Event Recognition in Crowd Environments , 2018 .
[36] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[37] Alessandro Perina,et al. Abnormality Detection with Improved Histogram of Oriented Tracklets , 2015, ICIAP.