Scene Anomaly

Scene anomaly detection focuses on identifying unusual events or objects within visual scenes, particularly in videos and images from diverse sources like UAV surveillance and disaster monitoring. Current research emphasizes unsupervised and semi-supervised approaches, employing deep learning models such as fully convolutional networks and novel architectures designed to handle variations in viewpoint and scene context, often incorporating memory banks or view synthesis techniques to improve robustness and accuracy. This field is crucial for applications ranging from infrastructure inspection and disaster response to autonomous driving, enabling faster, more efficient, and potentially safer systems for various safety-critical tasks.