SOURCE-LINKED INTELLIGENCE
Probe-VAD: Ordinal Likelihood Probing for Training-Free Video Anomaly Detection
Video anomaly detection (VAD) aims to localize anomalous events in untrimmed videos. Vision-language models (VLMs) provide rich visual understanding for training-free VAD, but existing approaches impose restrictive interfaces between visual understanding and anomaly scoring. Caption-based pipelines compress visual evidence into text, potentially discarding subtle cues, while direct numerical generation forces the model to express its judgment through a small set of predefined scores. Such interfaces can obscure subtle differences in anomaly severity, causing visually distinct clips to receive
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T13:59:47.000Z
First collected: 2026-09-20T08:40:59.508Z. This is not the publication date.