SSMTL++: Revisiting self-supervised multi-task learning for video anomaly detection

• Published in: Computer vision and image understanding Vol. 229; p. 103656
• Main Authors: Barbalau, Antonio, Ionescu, Radu Tudor, Georgescu, Mariana-Iuliana, Dueholm, Jacob, Ramachandra, Bharathkumar, Nasrollahi, Kamal, Khan, Fahad Shahbaz, Moeslund, Thomas B., Shah, Mubarak
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.03.2023
• Subjects: Anomaly detection; Multi-task learning; Neural networks; Self-supervised learning; Transformers; 68T01; 68T45; 68U10; 62M45; Neural networks; Self-supervised learning; Transformers; Multi-task learning; Anomaly detection

A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature. Due to its highly accurate results, the method attracted the attention of many researchers. In this work, we revisit the self-supervised multi-task learning framework, proposing...