Anomaly detection, aka outlier detection or novelty detection, has been a lasting yet active
research area in various research communities for several decades. There are still some …

Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance
systems, enabling the temporal or spatial identification of anomalous events within videos …

We aim at constructing a high performance model for defect detection that detects unknown
anomalous patterns of an image without anomalous data. To this end, we propose a two …

Anomaly detection is commonly pursued as a one-class classification problem, where
models can only learn from normal training samples, while being evaluated on both normal …

Anomaly detection in video is a challenging computer vision problem. Due to the lack of
anomalous events at training time, anomaly detection requires the design of learning …

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 …

Visual anomaly detection, an important problem in computer vision, is usually formulated as
a one-class classification and segmentation task. The student-teacher (ST) framework has …

Abnormal event detection in video is a challenging vision problem. Most existing
approaches formulate abnormal event detection as an outlier detection task, due to the …

Detecting abnormal events in video is commonly framed as a one-class classification task,
where training videos contain only normal events, while test videos encompass both normal …

A popular method for anomaly detection is to use the generator of an adversarial network to
formulate anomaly score over reconstruction loss of input. Due to the rare occurrence of …