GIAD: Generative Inpainting-Based Anomaly Detection via Self-Supervised Learning for Human Monitoring
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Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-030-89363-7_32
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1. Cross-Modal Self-Supervised Feature Extraction for Anomaly Detection in Human Monitoring;2023 IEEE 19th International Conference on Automation Science and Engineering (CASE);2023-08-26
2. GIAD-ST: Detecting anomalies in human monitoring based on generative inpainting via self-supervised multi-task learning;Journal of Intelligent Information Systems;2022-06-30
3. Detecting Video Anomalous Events with an Enhanced Abnormality Score;Lecture Notes in Computer Science;2022
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