C Wu, S Shao, C Tunc, S Hariri - 2020 IEEE/ACS 17th …, 2020 - ieeexplore.ieee.org
Anomaly detection is critically important for intelligent surveillance systems to detect in a timely manner any malicious activities. Many video anomaly detection approaches using …
S Lei, J Song, T Wang, F Wang, Z Yan - Multimedia Systems, 2024 - Springer
The widespread adoption of video surveillance systems in public security and network security domains has underscored the importance of video anomaly detection as a pivotal …
Surveillance cameras produce vast amounts of video data, posing a challenge for analysts due to the infrequent occurrence of unusual events. To address this, intelligent surveillance …
Z Hongmin, Y Dingding, T Qianqian - Opto-Electronic Engineering, 2024 - oejournal.org
An improved spatio-temporal graph convolutional network for video anomaly detection is proposed to accurately capture the spatio-temporal interactions of objects in anomalous …
X Zeng, Y Jiang, W Ding, H Li, Y Hao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Deep learning models have been widely used for anomaly detection in surveillance videos. Typical models are equipped with the capability to reconstruct normal videos and evaluate …
C Li, Q Qian - Journal of Organizational and End User Computing …, 2024 - igi-global.com
Anomaly detection plays a crucial role in the field of machine learning, as it involves constructing detection models capable of identifying abnormal samples that deviate from …
Security in public spaces is a primary concern across different domains and the deployment of real-time monitoring systems addresses this challenge. Video surveillance systems …
J Ren, F Xia, Y Liu, I Lee - 2021 international conference on …, 2021 - ieeexplore.ieee.org
Anomaly detection is a popular and vital task in various research contexts, which has been studied for several decades. To ensure the safety of people's lives and assets, video …
W Hao, R Zhang, S Li, J Li, F Li… - Security and …, 2020 - Wiley Online Library
Anomaly event detection has been extensively researched in computer vision in recent years. Most conventional anomaly event detection methods can only leverage the single …