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Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving (2406.06423v3)
Published 10 Jun 2024 in cs.CV and cs.RO
Abstract: In autonomous driving, the most challenging scenarios can only be detected within their temporal context. Most video anomaly detection approaches focus either on surveillance or traffic accidents, which are only a subfield of autonomous driving. We present HF$2$-VAD$_{AD}$, a variation of the HF$2$-VAD surveillance video anomaly detection method for autonomous driving. We learn a representation of normality from a vehicle's ego perspective and evaluate pixel-wise anomaly detections in rare and critical scenarios.