The increasing prevalence of surveillance cameras in smart cities, coupled with the surge of
online video applications, has heightened concerns regarding public security and privacy …

Video Anomaly Detection (VAD) finds widespread applications in security surveillance,
traffic monitoring, industrial monitoring, and healthcare. Despite extensive research efforts …

Few-shot anomaly detection for video surveillance is challenging due to the diverse nature
of target domains. Existing methodologies treat it as a one-class classification problem …

Video anomaly detection (VAD) has witnessed significant advancements through the
integration of large language models (LLMs) and vision-language models (VLMs) …

Almost 85% of companies polled said they were looking into anomaly detection (AD)
technologies for their industrial image anomalies. The present problem concerns detecting …

In the realm of video analytics, the significance of video anomaly detection cannot be
ignored. Many video anomaly detection methods have been introduced in traffic scenarios …

In this paper, we propose a new architecture for real-time anomaly detection in video data,
inspired by human behavior combining spatial and temporal analyses. This approach uses …

Object detectors based on CNNs (Convolutional Neural Networks) have considerable
potential for industrial applications. In the context of the production and transportation …

Abstract Mainstream unsupervised person ReIDentification (ReID) is on the basis of the
alternation of clustering and fine-tuning to promote the task performance, but the clustering …

Recently, violence detection systems developed using unified multimodal models have
achieved significant success and attracted widespread attention. However, most of these …