A unifying review of deep and shallow anomaly detection
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 …
the art in detection performance on complex data sets, such as large collections of images or …
Deep learning for anomaly detection: A review
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 …
research area in various research communities for several decades. There are still some …
Self-supervised predictive convolutional attentive block for anomaly detection
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 …
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
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 …
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
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 …
are either superficial, eg, classification of short-clips, and the single scenario, or …
Video event restoration based on keyframes for video anomaly detection
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 …
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
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 …
systems, enabling the temporal or spatial identification of anomalous events within videos …
A comprehensive review on deep learning-based methods for video anomaly detection
Video surveillance systems are popular and used in public places such as market places,
shop** malls, hospitals, banks, streets, education institutions, city administrative offices …
shop** 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 …
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
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 …
using only video-level labels. Recently, two-stage self-training methods have achieved …