Cross-modal spatio-temporal fusion weakly supervised video anomaly detection based on large-scale vision-language models

Key Points

• Video anomaly detection significantly improves using spatio-temporal fusion techniques, enhancing detection accuracy.
• The analysis leverages large-scale vision-language models to achieve effectiveness in detecting anomalies.
• Weakly supervised methods are utilized to reduce the need for extensive labeled datasets, making the approach more accessible.
• This technique may enable better surveillance systems and automated monitoring in various domains, enhancing safety and security.