Real-world anomaly detection in surveillance videos
Surveillance videos are able to capture a variety of realistic anomalies. In this paper, we
propose to learn anomalies by exploiting both normal and anomalous videos. To avoid …
propose to learn anomalies by exploiting both normal and anomalous videos. To avoid …
Not only look, but also listen: Learning multimodal violence detection under weak supervision
Violence detection has been studied in computer vision for years. However, previous work
are either superficial, eg, classification of short-clips, and the single scenario, or …
are either superficial, eg, classification of short-clips, and the single scenario, or …
Generative cooperative learning for unsupervised video anomaly detection
Video anomaly detection is well investigated in weakly supervised and one-class
classification (OCC) settings. However, unsupervised video anomaly detection is quite …
classification (OCC) settings. However, unsupervised video anomaly detection is quite …
Graph convolutional label noise cleaner: Train a plug-and-play action classifier for anomaly detection
Video anomaly detection under weak labels is formulated as a typical multiple-instance
learning problem in previous works. In this paper, we provide a new perspective, ie, a …
learning problem in previous works. In this paper, we provide a new perspective, ie, a …
Unbiased multiple instance learning for weakly supervised video anomaly detection
Abstract Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the
binary anomaly label is only given on the video level, but the output requires snippet-level …
binary anomaly label is only given on the video level, but the output requires snippet-level …
Claws: Clustering assisted weakly supervised learning with normalcy suppression for anomalous event detection
Learning to detect real-world anomalous events through video-level labels is a challenging
task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we …
task due to the rare occurrence of anomalies as well as noise in the labels. In this work, we …
Exploring background-bias for anomaly detection in surveillance videos
Anomaly detection in surveillance videos, as a special case of video-based action
recognition, is an important topic in multimedia community and public security. Currently …
recognition, is an important topic in multimedia community and public security. Currently …
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection
Abnormal event detection in video is alternatively known as outlier detection, where
machine learning can be highly effective. While testing an unknown video, the objective of …
machine learning can be highly effective. While testing an unknown video, the objective of …
Deep anomaly detection through visual attention in surveillance videos
This paper describes a method for learning anomaly behavior in the video by finding an
attention region from spatiotemporal information, in contrast to the full-frame learning. In our …
attention region from spatiotemporal information, in contrast to the full-frame learning. In our …
Contrastive attention for video anomaly detection
We consider weakly-supervised video anomaly detection in this work. This task aims to learn
to localize video frames containing anomaly events with only binary video-level annotation …
to localize video frames containing anomaly events with only binary video-level annotation …