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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 …
Networking systems for video anomaly detection: A tutorial and survey
The increasing utilization of surveillance cameras in smart cities, coupled with the surge of
online video applications, has heightened concerns regarding public security and privacy …
online video applications, has heightened concerns regarding public security and privacy …
De-confounded data-free knowledge distillation for handling distribution shifts
Abstract Data-Free Knowledge Distillation (DFKD) is a promising task to train high-
performance small models to enhance actual deployment without relying on the original …
performance small models to enhance actual deployment without relying on the original …
Memory-enhanced appearance-motion consistency framework for video anomaly detection
Modern network communication systems extensively utilize video data for various
applications, creating a pressing need for efficient Video Anomaly Detection (VAD) …
applications, creating a pressing need for efficient Video Anomaly Detection (VAD) …
Self-cooperation knowledge distillation for novel class discovery
Abstract Novel Class Discovery (NCD) aims to discover unknown and novel classes in an
unlabeled set by leveraging knowledge already learned about known classes. Existing …
unlabeled set by leveraging knowledge already learned about known classes. Existing …
Feature reconstruction with disruption for unsupervised video anomaly detection
Unsupervised video anomaly detection (UVAD) has gained significant attention due to its
label-free nature. Typically, UVAD methods can be categorized into two branches, ie the one …
label-free nature. Typically, UVAD methods can be categorized into two branches, ie the one …
Deep learning for video anomaly detection: A review
Video anomaly detection (VAD) aims to discover behaviors or events deviating from the
normality in videos. As a long-standing task in the field of computer vision, VAD has …
normality in videos. As a long-standing task in the field of computer vision, VAD has …
Memory-enhanced spatial-temporal encoding framework for industrial anomaly detection system
The development of modern manufacturing has raised greater demands on the accuracy,
response speed, and operating cost of industrial accident warnings. Compared to …
response speed, and operating cost of industrial accident warnings. Compared to …
Normality learning reinforcement for anomaly detection in surveillance videos
Abstract Video Anomaly Detection (VAD) is a key technology that enables automatic
anomaly detection in surveillance video systems. Due to the considerable dimensions and …
anomaly detection in surveillance video systems. Due to the considerable dimensions and …
Sampling to distill: Knowledge transfer from open-world data
Data-Free Knowledge Distillation (DFKD) is a novel task that aims to train high-performance
student models using only the pre-trained teacher network without original training data …
student models using only the pre-trained teacher network without original training data …