Detection of anomaly in surveillance videos using quantum convolutional neural networks
Anomalous behavior identification is the process of detecting behavior that differs from its
normal. These incidents will vary from violence to war, road crashes to kidnapping, and so …
normal. These incidents will vary from violence to war, road crashes to kidnapping, and so …
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 …
Pull & push: Leveraging differential knowledge distillation for efficient unsupervised anomaly detection and localization
Recently, much attention has been paid to segmenting subtle unknown defect regions by
knowledge distillation in an unsupervised setting. Most previous studies concentrated on …
knowledge distillation in an unsupervised setting. Most previous studies concentrated on …
Skeletal video anomaly detection using deep learning: Survey, challenges, and future directions
The existing methods for video anomaly detection mostly utilize videos containing
identifiable facial and appearance-based features. The use of videos with identifiable faces …
identifiable facial and appearance-based features. The use of videos with identifiable faces …
Hierarchical graph embedded pose regularity learning via spatio-temporal transformer for abnormal behavior detection
Abnormal behavior detection in surveillance video is a fundamental task in modern public
security. Different from typical pixel-based solutions, pose-based approaches leverage low …
security. Different from typical pixel-based solutions, pose-based approaches leverage low …
[HTML][HTML] Abnormal event detection for video surveillance using an enhanced two-stream fusion method
Abnormal event detection is a critical component of intelligent surveillance systems, focusing
on identifying abnormal objects or unusual human behaviours in video sequences …
on identifying abnormal objects or unusual human behaviours in video sequences …
Context recovery and knowledge retrieval: A novel two-stream framework for video anomaly detection
Video anomaly detection aims to find the events in a video that do not conform to the
expected behavior. The prevalent methods mainly detect anomalies by snippet …
expected behavior. The prevalent methods mainly detect anomalies by snippet …
Confused and disentangled distribution alignment for unsupervised universal adaptive object detection
W Shi, D Liu, Z Wu, B Zheng - Knowledge-Based Systems, 2024 - Elsevier
Universal domain adaptive object detection (UniDAOD) is a more challenging and realistic
problem than traditional domain adaptive object detection (DAOD), aiming to transfer the …
problem than traditional domain adaptive object detection (DAOD), aiming to transfer the …
Surveillance video-and-language understanding: from small to large multimodal models
Surveillance videos play a crucial role in public security. However, current tasks related to
surveillance videos primarily focus on classifying and localizing anomalous events. Despite …
surveillance videos primarily focus on classifying and localizing anomalous events. Despite …
Robust tracking via learning model update with unsupervised anomaly detection philosophy
J Gao, B Zhong, Y Chen - … on Circuits and Systems for Video …, 2022 - ieeexplore.ieee.org
Template tracking is a typical paradigm to adaptively locate arbitrary objects in the tracking
literature. Although existing works present diverse template updating approaches, one of the …
literature. Although existing works present diverse template updating approaches, one of the …