Towards Open Set Video Anomaly Detection

نویسندگان

چکیده

AbstractOpen Set Video Anomaly Detection (OpenVAD) aims to identify abnormal events from video data where both known anomalies and novel ones exist in testing. Unsupervised models learned solely normal videos are applicable any testing but suffer a high false positive rate. In contrast, weakly supervised methods effective detecting could fail an open world. We develop method for the OpenVAD problem by integrating evidential deep learning (EDL) normalizing flows (NFs) into multiple instance (MIL) framework. Specifically, we propose use graph neural networks triplet loss learn discriminative features training EDL classifier, is capable of identifying unknown quantifying uncertainty. Moreover, uncertainty-aware selection strategy obtain clean anomaly instances NFs module generate pseudo anomalies. Our superior existing approaches inheriting advantages unsupervised weakly-supervised MIL Experimental results on real-world datasets show effectiveness our method. KeywordsVideo detectionWeakly learningOpen set recognitionNormalizing

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Energy-based Models for Video Anomaly Detection

Automated detection of abnormalities in data has been studied in research area in recent years because of its diverse applications in practice including video surveillance, industrial damage detection and network intrusion detection. However, building an effective anomaly detection system is a non-trivial task since it requires to tackle challenging issues of the shortage of annotated data, ina...

متن کامل

Video Behaviour Profiling for Anomaly Detection

This paper aims to address the problem of modelling video behaviour captured in surveillance videos for the applications of online normal behaviour recognition and anomaly detection. A novel framework is developed for automatic behaviour profiling and online anomaly sampling/detection without any manual labelling of the training dataset. The framework consists of the following key components: (...

متن کامل

Modeling Local Video Statistics for Anomaly Detection

MODELING LOCAL VIDEO STATISTICS FOR ANOMALY DETECTION

متن کامل

Crowd Anomaly Detection for Automated Video Surveillance

Video-based crowd behaviour detection aims at tackling challenging problems such as automating and identifying changing crowd behaviours under complex real life situations. In this paper, real-time crowd anomaly detection algorithms have been investigated. Based on the spatio-temporal video volume concept, an innovative spatio-temporal texture model has been proposed in this research for its ri...

متن کامل

Towards combining ontology matchers via anomaly detection

In ontology alignment, there is no single best performing matching algorithm for every matching problem. Thus, most modern matching systems combine several base matchers and aggregate their results into a final alignment. This combination is often based on simple voting or averaging, or uses existing matching problems for learning a combination policy in a supervised setting. In this paper, we ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Lecture Notes in Computer Science

سال: 2022

ISSN: ['1611-3349', '0302-9743']

DOI: https://doi.org/10.1007/978-3-031-19830-4_23