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M. Bhargava, C.-C. Chen, M. S. Ryoo, 2007, Detection of abandoned objects in crowded environments, in Proceedings of AVSS, pp. 271-276DOI
H.-H. Liao, J.-Y. Chang, 2008, A Localized Approach to Abandoned Luggage Detection with Foreground- Mask Sampling, in Proceedings of AVSS, pp. 132-139DOI
F. Porikli, Y. Ivanov, 2008, Robust abandoned object detection using dual foregrounds, EURASIP Journal on Advances in Signal Processing, Vol. 2008, pp. 30Google Search
S. Kwak, G. Bae, 2010, Abandoned luggage detection using a finite state automaton in surveillance video, Optical Engineering, Vol. 49, No. 2, pp. 027 007–1-027 007–10DOI
G. Szwoch, P. Dalka, 2010, A Framework for Automatic Detection of Abandoned Luggage in Airport Terminal., Springer, pp. 13-22DOI
Y. Tian, R. S. Feris, H. Liu, A. Hampapur, 2011, Robust Detection of Abandoned and Removed Objects in Complex Surveillance Videos, IEEE Transactions on Systems Man and Cybernetics, Vol. 41, No. 5, pp. 565-576DOI
G. Szwoch, 2016, Extraction of stable foreground image regions for unattended luggage detection, Multimedia Tools and Applications, Vol. 75, No. 2, pp. 761-786Google Search
J. Wen, H. Gong, X. Zhang, W. Hu, 2009, Generative model for abandoned object detection, in Proceedings of ICIP, pp. 853-856DOI
S. Smeureanuz, R. T. Ionescu, 2018, Real-Time Deep Learning Method for Abandoned Luggage Detection in Video, in Proceedings of European Signal Processing Conference 2018 In 2018 26th European Signal Processing Conference (EUSIPCO), pp. 1775-1779DOI
S. Akcay, A. Atapour-Abarghouei, T. P. Breckon, 2018 December, Ganomaly: Semi-supervised anomaly detection via adversarial training., In Asian conference on computer vision, pp. 622-637DOI
M. abokrou, M. Khalooei, M. Fathy, E. Adeli, 2018, Adversarially learned one-class classifier for novelty detection., In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3379-3388Google Search
T. Schlegl, P. Seeböck, S. M. Waldstein, U. Schmidt-Erfurth, G. Langs, 2017 June, Unsupervised anomaly detection with generative adversarial networks to guide marker discovery., In International conference on information processing in medical imaging, pp. 146-157DOI
A. Bochkovskiy, C. Y. Wang, H. Y. M. Liao, 2020, YOLOv4: Optimal Speed and Accuracy of Object Detection., arXiv preprint arXiv:2004.10934.Google Search
Abnormal Event CCTV Video AI Training Dataset, Search
O. Ronneberger, P. Fischer, T. Brox, 2015 October, U-net: Convolutional networks for biomedical image segmentation., In International Conference on Medical image computing and computer-assisted intervention, pp. 234-241DOI
Y. Yamanaka, T. Iwata, H. Takahashi, M. Yamada, S. Kanai, 2019 August, Autoencoding binary classifiers for supervised anomaly detection., In Pacific Rim International Conference on Artificial Intelligence, pp. 647-659DOI
J. Kim, K. Jeong, H. Choi, K. Seo, January 2020, GAN-based Anomaly Detection in Imbalance Problems, ECCV-2020 Workshops Lecture Notes in Computer Science Springer-VerlagDOI