7 papers · 1 filter
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…
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…
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…
Leveraging Multimodal LLM Descriptions of Activity for Explainable Semi-Supervised Video Anomaly Detection
Furkan Mumcu, Michael J. Jones, Anoop Cherian +1
Existing semi-supervised video anomaly detection (VAD) methods often struggle with detecting complex anomalies involving object interactions and generally lack explainability. To o…
MLLM-Guided Autonomous Object Detection for Open-World Understanding
Furkan Mumcu, Michael J. Jones, Anoop Cherian +1
Object detection typically relies on predefined category vocabularies, while open-world and open-vocabulary approaches remain limited by generic unknown labels or externally specif…
ComplexVAD: Detecting Interaction Anomalies in Video
Furkan Mumcu, Michael J. Jones, Yasin Yilmaz +1
Existing video anomaly detection datasets are inadequate for representing complex anomalies that occur due to the interactions between objects. The absence of complex anomalies in…