3 papers
cs.CV2026
TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding
Yuqiang Lin, Yan Shi, Sam Lockyer +5
Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To address this challenge, we propos…
cs.CV2026
TAU-R1: Visual Language Model for Traffic Anomaly Understanding
Yuqiang Lin, Kehua Chen, Sam Lockyer +12
Traffic Anomaly Understanding (TAU) is important for traffic safety in Intelligent Transportation Systems. Recent vision-language models (VLMs) have shown strong capabilities in vi…
cs.CV2025
RoundaboutHD: High-Resolution Real-World Urban Environment Benchmark for Multi-Camera Vehicle Tracking
Yuqiang Lin, Sam Lockyer, Mingxuan Sui +6
The multi-camera vehicle tracking (MCVT) framework holds significant potential for smart city applications, including anomaly detection, traffic density estimation, and suspect veh…