A Unified GAN-Based Framework for Unsupervised Video Anomaly Detection Using Optical Flow and RGB Cues
Video anomaly detection in unconstrained environments remains a fundamental challenge due to the scarcity of labeled anomalous data and the diversity of real-world scenarios. To address this, we propose a novel unsupervised framework that integrates RGB appearance and optical flow motion via a unifi...
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| Hoofdauteurs: | , |
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| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
MDPI AG
2025-09-01
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| Reeks: | Sensors |
| Onderwerpen: | |
| Online toegang: | https://www.mdpi.com/1424-8220/25/18/5869 |
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