Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …

The current concept of smart cities influences urban planners and researchers to provide
modern, secured and sustainable infrastructure and gives a decent quality of life to its …

Video anomaly detection (VAD) refers to the discrimination of unexpected events in videos.
The deep generative model (DGM)-based method learns the regular patterns on normal …

Surveillance video anomaly detection (SVAD) is a challenging task due to the variations in
object scale, discrimination and unexpected events, the impact of the background, and the …

The recent contrastive language-image pre-training (CLIP) model has shown great success
in a wide range of image-level tasks, revealing remarkable ability for learning powerful …

Semi-supervised video anomaly detection (VAD) is a critical task in the intelligent
surveillance system. However, an essential type of anomaly in VAD named scene …

As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

As an important and challenging task for intelligent video surveillance systems, video
anomaly detection is generally referred to as automatic recognition of video frames that …

In this paper, we propose a scene-aware context reasoning method that exploits context
information from visual features for unsupervised abnormal event detection in videos, which …

Anomaly detection is one of the most challenging tasks in visual understanding because
anomalous events are diverse and complicated. In this paper, we propose a future frame …