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A survey on explainable anomaly detection
In the past two decades, most research on anomaly detection has focused on improving the
accuracy of the detection, while largely ignoring the explainability of the corresponding …
accuracy of the detection, while largely ignoring the explainability of the corresponding …
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 …
Anomaly detection in surveillance videos: a thematic taxonomy of deep models, review and performance analysis
The task of anomaly detection has recently gained much attention in the field of visual
surveillance. Video surveillance data is often available in large quantities, but manual …
surveillance. Video surveillance data is often available in large quantities, but manual …
Multimedia datasets for anomaly detection: a review
Multimedia anomaly datasets play a crucial role in automated surveillance. They have a
wide range of applications expanding from outlier objects/situation detection to the detection …
wide range of applications expanding from outlier objects/situation detection to the detection …
Multi-contextual predictions with vision transformer for video anomaly detection
Video Anomaly Detection (VAD) has been traditionally tackled in two main methodologies:
the reconstruction-based approach and the prediction-based one. As the reconstruction …
the reconstruction-based approach and the prediction-based one. As the reconstruction …
Uncertainty-boosted robust video activity anticipation
Video activity anticipation aims to predict what will happen in the future, embracing a broad
application prospect ranging from robot vision and autonomous driving. Despite the recent …
application prospect ranging from robot vision and autonomous driving. Despite the recent …
Discrete neural representations for explainable anomaly detection
The aim of this work is to detect and automatically generate high-level explanations of
anomalous events in video. Understanding the cause of an anomalous event is crucial as …
anomalous events in video. Understanding the cause of an anomalous event is crucial as …
Deep crowd anomaly detection: state-of-the-art, challenges, and future research directions
Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …
of smart cities. A plethora of deep learning methods have been proposed that generally …
Evidential reasoning for video anomaly detection
Video anomaly detection aims to discriminate events that deviate from normal patterns in a
video. Modeling the decision boundaries of anomalies is challenging, due to the uncertainty …
video. Modeling the decision boundaries of anomalies is challenging, due to the uncertainty …
An adaptive framework for anomaly detection in time-series audio-visual data
Anomaly detection is an integral part of a number of surveillance applications. However,
most of the existing anomaly detection models are statically trained on pre-recorded data …
most of the existing anomaly detection models are statically trained on pre-recorded data …