Dual contrast discriminator with sharing attention for video anomaly detection
Y Zeng, Y Chen, S Yu, M Yang, R Chen… - Machine Vision and …, 2024 - Springer
The detection of video anomalies is a well-known issue in the realm of visual research. The
volume of normal and abnormal sample data in this field is unbalanced, hence …
volume of normal and abnormal sample data in this field is unbalanced, hence …
Comprehensive regularization in a bi-directional predictive network for video anomaly detection
Video anomaly detection aims to automatically identify unusual objects or behaviours by
learning from normal videos. Previous methods tend to use simplistic reconstruction or …
learning from normal videos. Previous methods tend to use simplistic reconstruction or …
Dual discriminator generative adversarial network for video anomaly detection
F Dong, Y Zhang, X Nie - IEEE Access, 2020 - ieeexplore.ieee.org
Video anomaly detection is an essential task because of its numerous applications in
various areas. Because of the rarity of abnormal events and the complicated characteristic of …
various areas. Because of the rarity of abnormal events and the complicated characteristic of …
Object-based video anomaly detection using multi-attention and adaptive velocity attribute representation learning
X Ren, H Xia, Y Zhan - Multimedia Systems, 2024 - Springer
Video anomaly detection is an important topic in multimedia technology. Multiscale features
and cross-learning between low-level and high-level features in the existing prediction …
and cross-learning between low-level and high-level features in the existing prediction …
Video Anomaly Detection Using Dual Discriminator Based Generative Adversarial Network
J Xu, Z Miao, W Xu, J Wang, Q Zhang… - 2021 20th IEEE …, 2021 - ieeexplore.ieee.org
Video anomaly detection is of great significance due to its wide applications in video
surveillance. Recently, there is a trend of using a video prediction framework to tackle this …
surveillance. Recently, there is a trend of using a video prediction framework to tackle this …
Learning attention augmented spatial-temporal normality for video anomaly detection
Y Liu, S Li, J Liu, H Yang, M Zhao… - … on Smart and …, 2021 - ieeexplore.ieee.org
Video anomaly detection is an essential and challenging task in the computer vision
community, which aims to automatically detect and localize abnormal events in videos. In …
community, which aims to automatically detect and localize abnormal events in videos. In …
Multi-scale Spatial-temporal Interaction Network for Video Anomaly Detection
Z Ning, Z Li, L Song - arXiv preprint arXiv:2306.10239, 2023 - arxiv.org
Video anomaly detection (VAD) is an essential yet challenge task in signal processing.
Since certain anomalies cannot be detected by analyzing temporal or spatial information …
Since certain anomalies cannot be detected by analyzing temporal or spatial information …
Anomaly detection with prototype-guided discriminative latent embeddings
Recent efforts towards video anomaly detection (VAD) try to learn a deep autoencoder to
describe normal event patterns with small reconstruction errors. The video inputs with large …
describe normal event patterns with small reconstruction errors. The video inputs with large …
An explainable and efficient deep learning framework for video anomaly detection
Deep learning-based video anomaly detection methods have drawn significant attention in
the past few years due to their superior performance. However, almost all the leading …
the past few years due to their superior performance. However, almost all the leading …
Bi-READ: Bi-Residual AutoEncoder based feature enhancement for video anomaly detection
R Kommanduri, M Ghorai - Journal of Visual Communication and Image …, 2023 - Elsevier
Video anomaly detection (VAD) refers to identifying abnormal events in the surveillance
video. Typically, reconstruction based video anomaly detection techniques employ …
video. Typically, reconstruction based video anomaly detection techniques employ …