视频异常检测是指对偏离正常行为事件的检测识别, 在监控视频中有着广泛的应用.
对基于深度学习的视频异常检测算法进行了深入的调查研究和全面的梳理与总结. 首先 …

Weakly-supervised Video Anomaly Detection (W-VAD) aims to detect abnormal events in
videos given only video-level labels for training. Recent methods relying on multiple …

We propose a lightweight and accurate method for detecting anomalies in videos. Existing
methods used multiple-instance learning (MIL) to determine the normal/abnormal status of …

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 …

Unsupervised video anomaly detection (UVAD) has gained significant attention due to its
label-free nature. Typically, UVAD methods can be categorized into two branches, ie the one …

We study weakly-supervised anomaly detection where only video-level
“anomalous”/“normal” labels are available in training, while anomaly events should be …

Although deep neural networks (DNNs) enable great progress in video abnormal event
detection (VAD), existing solutions typically suffer from two issues:(1) The localization of …

Deep Metric Learning trains a neural network to map input images to a lower-dimensional
embedding space such that similar images are closer together than dissimilar images. When …

In outdoor crimes such as robbery and kidnapping, suspects generally secretly follow their
victims in public places and then look for opportunities to commit crimes. Video anomaly …

Temporal action localization (TAL) is a prevailing task due to its great application potential.
Existing works in this field mainly suffer from two weaknesses:(1) They often neglect the …