An analysis of artificial intelligence techniques in surveillance video anomaly detection: A comprehensive survey
Surveillance cameras have recently been utilized to provide physical security services
globally in diverse private and public spaces. The number of cameras has been increasing …
globally in diverse private and public spaces. The number of cameras has been increasing …
Self-training multi-sequence learning with transformer for weakly supervised video anomaly detection
Abstract Weakly supervised Video Anomaly Detection (VAD) using Multi-Instance Learning
(MIL) is usually based on the fact that the anomaly score of an abnormal snippet is higher …
(MIL) is usually based on the fact that the anomaly score of an abnormal snippet is higher …
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 …
Vision transformer attention with multi-reservoir echo state network for anomaly recognition
Anomalous event recognition requires an instant response to reduce the loss of human life
and property; however, existing automated systems show limited performance due to …
and property; however, existing automated systems show limited performance due to …
Sequential attention mechanism for weakly supervised video anomaly detection
Surveillance cameras are installed across various sectors of a smart city in order to capture
ongoing events for monitoring purposes. The analysis of these surveillance videos is an …
ongoing events for monitoring purposes. The analysis of these surveillance videos is an …
A comprehensive review for video anomaly detection on videos
Video Surveillance Systems (VSS) are widely utilized in public and private areas to increase
public safety, such as shopping malls, markets, banks, hospitals, educational institutions …
public safety, such as shopping malls, markets, banks, hospitals, educational institutions …
MSAF: Multimodal supervise-attention enhanced fusion for video anomaly detection
The complementarity of multimodal signal is essential for video anomaly detection.
However, existing methods either lack exploration to multimodal data or ignore the implicit …
However, existing methods either lack exploration to multimodal data or ignore the implicit …
Cross-domain video anomaly detection without target domain adaptation
Most cross-domain unsupervised Video Anomaly Detection (VAD) works assume that at
least few task-relevant target domain training data are available for adaptation from the …
least few task-relevant target domain training data are available for adaptation from the …
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 …
Normality guided multiple instance learning for weakly supervised video anomaly detection
Abstract Weakly supervised Video Anomaly Detection (wVAD) aims to distinguish anomalies
from normal events based on video-level supervision. Most existing works utilize Multiple …
from normal events based on video-level supervision. Most existing works utilize Multiple …