14 papers
SENSE-VAD: Sentient and Semantic Video Anomaly Detection for Autonomous Driving
Nghia T. Nguyen, Lokman Bekit, Yasin Yilmaz
Autonomous vehicles (AVs) must navigate not only motion-based hazards but also socially complex situations whose danger is constituted by inter-agent relationships rather than move…
Submission Responsibility Matters: Role-Aware Submission Quotas under Coauthorship
Furkan Mumcu, Yasin Yilmaz
Author-level submission quotas are increasingly used to control growing peer-review load. Recent coauthorship-sensitive quota rules improve over fixed per-author limits by reducing…
Learning Where and When: Patch-Based Spatiotemporal Localization in Weakly Supervised Video Anomaly Detection
Hamza Karim, Nghia Nguyen, Lokman Bekit +1
Weakly supervised video anomaly detection (WSVAD) has predominantly focused on temporal localization, identifying when anomalies occur while largely neglecting their spatial extent…
Is Video Anomaly Detection Misframed? Evidence from LLM-Based and Multi-Scene Models
Furkan Mumcu, Michael J. Jones, Anoop Cherian +1
Recent video anomaly detection research has expanded rapidly with an emphasis on general models of normality intended to work across many different scenes. While this focus has led…
Detecting Adversarial Data via Provable Adversarial Noise Amplification
Furkan Mumcu, Yasin Yilmaz
The nonuniform and growing impact of adversarial noise across the layers of deep neural networks has been used in the literature, without a formal mathematical justification, to de…
QVAD: A Question-Centric Agentic Framework for Efficient and Training-Free Video Anomaly Detection
Lokman Bekit, Hamza Karim, Nghia T Nguyen +1
Video Anomaly Detection (VAD) is a fundamental challenge in computer vision, particularly due to the open-set nature of anomalies. While recent training-free approaches utilizing V…