Enhancing Video Anomaly Detection Using a Transformer Spatiotemporal Attention Unsupervised Framework for Large Datasets

This work introduces an unsupervised framework for video anomaly detection, leveraging a hybrid deep learning model that combines a vision transformer (ViT) with a convolutional spatiotemporal relationship (STR) attention block. The proposed model addresses the challenges of anomaly detection in vid...

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Detalles Bibliográficos

Autores principales:	Mohamed H. Habeb, May Salama, Lamiaa A. Elrefaei
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-07-01
Colección:	Algorithms
Materias:	video anomaly detection unsupervised learning spatiotemporal modeling large datasets
Acceso en línea:	https://www.mdpi.com/1999-4893/17/7/286
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