Dong-Xuan Liu

TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding

TAU-Bench is introduced, a track-centric benchmark for jointly evaluating anomaly instance tracking and fine-grained anomaly understanding, and shows that models producing plausible anomaly interpretations may still fail to localize and track the correct instance reliably, revealing a persistent gap between semantic reasoning and visual grounding.