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 …
Deep learning-based anomaly detection in video surveillance: A survey
Anomaly detection in video surveillance is a highly developed subject that is attracting
increased attention from the research community. There is great demand for intelligent …
increased attention from the research community. There is great demand for intelligent …
Attention-based residual autoencoder for video anomaly detection
Automatic anomaly detection is a crucial task in video surveillance system intensively used
for public safety and others. The present system adopts a spatial branch and a temporal …
for public safety and others. The present system adopts a spatial branch and a temporal …
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 …
SACF-Net: Skip-attention based correspondence filtering network for point cloud registration
Rigid registration is a transformation estimation problem between two point clouds. The two
point clouds captured may partially overlap owing to different viewpoints and acquisition …
point clouds captured may partially overlap owing to different viewpoints and acquisition …
TransCNN: Hybrid CNN and transformer mechanism for surveillance anomaly detection
Surveillance video anomaly detection (SVAD) is a challenging task due to the variations in
object scale, discrimination and unexpected events, the impact of the background, and the …
object scale, discrimination and unexpected events, the impact of the background, and the …
Amp-net: Appearance-motion prototype network assisted automatic video anomaly detection system
As essential tools for industry safety protection, automatic video anomaly detection systems
(AVADS) are designed to detect anomalous events of concern in surveillance videos …
(AVADS) are designed to detect anomalous events of concern in surveillance videos …
SSMTL++: Revisiting self-supervised multi-task learning for video anomaly detection
A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was
recently introduced in literature. Due to its highly accurate results, the method attracted the …
recently introduced in literature. Due to its highly accurate results, the method attracted the …
Unsupervised video anomaly detection via normalizing flows with implicit latent features
In contemporary society, surveillance anomaly detection, ie, spotting anomalous events
such as crimes or accidents in surveillance videos, is a critical task. As anomalies occur …
such as crimes or accidents in surveillance videos, is a critical task. As anomalies occur …
Prime: privacy-preserving video anomaly detection via motion exemplar guidance
Y Su, H Zhu, Y Tan, S An, M Xing - Knowledge-Based Systems, 2023 - Elsevier
Video anomaly detection (VAD) involves identifying events or behaviours in video
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …
sequences that deviate from expected patterns. Most VAD models to date focus on seeking …