A unifying review of deep and shallow anomaly detection

L Ruff, JR Kauffmann, RA Vandermeulen… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …

Deep learning for anomaly detection: A review

G Pang, C Shen, L Cao, AVD Hengel - ACM computing surveys (CSUR), 2021 - dl.acm.org
Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …

Self-supervised predictive convolutional attentive block for anomaly detection

NC Ristea, N Madan, RT Ionescu… - Proceedings of the …, 2022 - openaccess.thecvf.com
Anomaly detection is commonly pursued as a one-class classification problem, where
models can only learn from normal training samples, while being evaluated on both normal …

Anomaly detection in video via self-supervised and multi-task learning

MI Georgescu, A Barbalau… - Proceedings of the …, 2021 - openaccess.thecvf.com
Anomaly detection in video is a challenging computer vision problem. Due to the lack of
anomalous events at training time, anomaly detection requires the design of learning …

Not only look, but also listen: Learning multimodal violence detection under weak supervision

P Wu, J Liu, Y Shi, Y Sun, F Shao, Z Wu… - Computer Vision–ECCV …, 2020 - Springer
Violence detection has been studied in computer vision for years. However, previous work
are either superficial, eg, classification of short-clips, and the single scenario, or …

Video event restoration based on keyframes for video anomaly detection

Z Yang, J Liu, Z Wu, P Wu, X Liu - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Video anomaly detection (VAD) is a significant computer vision problem. Existing deep
neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or …

Generalized video anomaly event detection: Systematic taxonomy and comparison of deep models

Y Liu, D Yang, Y Wang, J Liu, J Liu… - ACM Computing …, 2024 - dl.acm.org
Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …

A comprehensive review on deep learning-based methods for video anomaly detection

R Nayak, UC Pati, SK Das - Image and Vision Computing, 2021 - Elsevier
Video surveillance systems are popular and used in public places such as market places,
shopping malls, hospitals, banks, streets, education institutions, city administrative offices …

Ubnormal: New benchmark for supervised open-set video anomaly detection

A Acsintoae, A Florescu… - Proceedings of the …, 2022 - openaccess.thecvf.com
Detecting abnormal events in video is commonly framed as a one-class classification task,
where training videos contain only normal events, while test videos encompass both normal …

Exploiting completeness and uncertainty of pseudo labels for weakly supervised video anomaly detection

C Zhang, G Li, Y Qi, S Wang, L Qing… - Proceedings of the …, 2023 - openaccess.thecvf.com
Weakly supervised video anomaly detection aims to identify abnormal events in videos
using only video-level labels. Recently, two-stage self-training methods have achieved …