An Exploratory Study on Human-Centric Video Anomaly Detection Through Variational Autoencoders and Trajectory Prediction
Abstract Video Anomaly Detection (VAD) represents a challenging and prominent research
task within computer vision. In recent years, Pose-based Video Anomaly Detection (PAD) …
task within computer vision. In recent years, Pose-based Video Anomaly Detection (PAD) …
Synthetic temporal anomaly guided end-to-end video anomaly detection
Due to the limited availability of anomaly examples, video anomaly detection is often seen
as one-class classification (OCC) problem. A popular way to tackle this problem is by …
as one-class classification (OCC) problem. A popular way to tackle this problem is by …
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 …
Self-trained deep ordinal regression for end-to-end video anomaly detection
Video anomaly detection is of critical practical importance to a variety of real applications
because it allows human attention to be focused on events that are likely to be of interest, in …
because it allows human attention to be focused on events that are likely to be of interest, in …
Video anomaly detection via predictive autoencoder with gradient-based attention
Video anomaly detection is a challenging problem due to the ambiguity and diversity of
anomalies in different scenes. In this paper, we present a novel framework to detect …
anomalies in different scenes. In this paper, we present a novel framework to detect …
Attribute-based representations for accurate and interpretable video anomaly detection
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 …
applications. As anomalies are inherently ambiguous, it is essential for users to understand …
Bidirectional retrospective generation adversarial network for anomaly detection in videos
Anomaly detection in videos is the task of identifying frames from a video sequence that
depict events that do not conform to expected behavior, which is an extremely challenging …
depict events that do not conform to expected behavior, which is an extremely challenging …
Feature prediction diffusion model for video anomaly detection
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 …
applications. Due to the unavailability of large-scale annotated anomaly events, most …
Progressive prediction: Video anomaly detection via multi‐grained prediction
Abstract Video Anomaly Detection (VAD) has been an active research field for several
decades. However, most existing approaches merely extract a single type of feature from …
decades. However, most existing approaches merely extract a single type of feature from …
Video anomaly detection based on a multi-layer reconstruction autoencoder with a variance attention strategy
S Li, Y Cheng, L Zhang, X Luo, R Zhang - Image and Vision Computing, 2024 - Elsevier
In this paper, we propose a comprehensive framework for detecting anomalies in videos
based on autoencoder (AE). Traditional AE models solely rely on input and final …
based on autoencoder (AE). Traditional AE models solely rely on input and final …