Feature prediction diffusion model for video anomaly detection

C Yan, S Zhang, Y Liu, G Pang… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Anomaly detection in the video is an important research area and a challenging task in real
applications. Due to the unavailability of large-scale annotated anomaly events, most …

Memory-augmented appearance-motion network for video anomaly detection

L Wang, J Tian, S Zhou, H Shi, G Hua - Pattern Recognition, 2023‏ - Elsevier
Video anomaly detection is a promising yet challenging task, where only normal events are
observed in the training phase. Without any explicit classification boundary between normal …

A new comprehensive benchmark for semi-supervised video anomaly detection and anticipation

C Cao, Y Lu, P Wang, Y Zhang - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
Semi-supervised video anomaly detection (VAD) is a critical task in the intelligent
surveillance system. However, an essential type of anomaly in VAD named scene …

Open-vocabulary video anomaly detection

P Wu, X Zhou, G Pang, Y Sun, J Liu… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Current video anomaly detection (VAD) approaches with weak supervisions are inherently
limited to a closed-set setting and may struggle in open-world applications where there can …

Follow the rules: reasoning for video anomaly detection with large language models

Y Yang, K Lee, B Dariush, Y Cao, SY Lo - European Conference on …, 2024‏ - Springer
Abstract Video Anomaly Detection (VAD) is crucial for applications such as security
surveillance and autonomous driving. However, existing VAD methods provide little …

Deep learning for video anomaly detection: A review

P Wu, C Pan, Y Yan, G Pang, P Wang… - arxiv preprint arxiv …, 2024‏ - arxiv.org
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 …

Attribute-based representations for accurate and interpretable video anomaly detection

T Reiss, Y Hoshen - arxiv preprint arxiv:2212.00789, 2022‏ - arxiv.org
Video anomaly detection (VAD) is a challenging computer vision task with many practical
applications. As anomalies are inherently ambiguous, it is essential for users to understand …

Normalizing flows for human pose anomaly detection

O Hirschorn, S Avidan - Proceedings of the IEEE/CVF …, 2023‏ - openaccess.thecvf.com
Video anomaly detection is an ill-posed problem because it relies on many parameters such
as appearance, pose, camera angle, background, and more. We distill the problem to …

Advancing video anomaly detection: A concise review and a new dataset

L Zhu, L Wang, A Raj, T Gedeon… - The Thirty-eight …, 2024‏ - openreview.net
Video Anomaly Detection (VAD) finds widespread applications in security surveillance,
traffic monitoring, industrial monitoring, and healthcare. Despite extensive research efforts …

Semantic-driven dual consistency learning for weakly supervised video anomaly detection

Y Su, Y Tan, S An, M **ng, Z Feng - Pattern Recognition, 2025‏ - Elsevier
Video anomaly detection presents a significant challenge in computer vision, with the aim of
distinguishing various anomaly events from numerous normal ones. Weakly supervised …