Video Internet of Things (VIoT) has shown full potential in collecting an unprecedented
volume of video data. Learning to schedule perceiving models and analyzing the collected …

Data-driven methods—particularly machine learning techniques—are expected to play a
key role in the headway of Industry 4.0. One increasingly popular application in this context …

Towards open-ended Video Anomaly Detection (VAD), existing methods often exhibit
biased detection when faced with challenging or unseen events and lack interpretability. To …

Video anomaly detection is very challenging, as most anomalies are rare and inconclusive.
Previous weakly supervised learning approaches utilize the classifier trained with video …

The objective of multi-domain image-to-image translation is to learn the mapping from a
source domain to a target domain in multiple image domains while preserving the content …

异常事件检测技术是当前智能监控技术研究领域关注的一个热点, 作为计算机视觉的重要研究
内容, 其主要目标是利用计算机自动检测出可被视为异常的事件. 传统方法存在低层视频特征 …

The anomaly in videos can be considered as a deviation from regular video sequences.
Most existing approaches neglect the imbalanced information distribution between the …

Multi-modal human action segmentation is a critical and challenging task with a wide range
of applications. Nowadays, the majority of approaches concentrate on the fusion of dense …

This paper addresses video anomaly detection problem for videosurveillance. Due to the
inherent rarity and heterogeneity of abnormal events, the problem is viewed as a normality …

In industrial anomaly detection, model efficiency and mobile-friendliness become the
primary concerns in real-world applications. Simultaneously, the impressive generalization …