How do you test AI video search? What the IPVM ranking leaves open
2026-11-09 · Karl Wang
IPVM's 2026 ranking of generative AI models for video surveillance analytics compares 12 foundation models on two tasks: video search and event description. The full methodology is paywalled, so I can't quote its scores — but the two tasks themselves are worth unpacking, because most vendor demos blur them together.
Video search is temporal grounding, not image search
Given a clip and a question like "a person in a red jacket approaching the exit after 10 pm", the model must return a time range, not a frame. The standard way to score that is:
- IoU (Intersection over Union): how much the predicted range overlaps the true range. IoU ≥ 0.5 usually counts as a hit.
- Recall@1 / Recall@5 / Recall@10: whether the right moment is in the model's top 1, 5 or 10 answers.
- False positives on negative queries: questions about events that are not in the video. This is where models hallucinate most.
That last point matters more than the first two. A model that always finds something looks great on positive queries and terrible in production. Every test set I build includes negative queries — for example, "someone climbing over the fence" in a clip where nobody does.
Event description needs a fact checklist, not BLEU
For event description, n-gram scores like BLEU or ROUGE reward fluent text, not correct text. The honest way to score it is a human fact checklist: who, where, what, in what order — and a hallucination rate for details that were never visible.
The test setup I use
- Staged clips: 30-second MP4s, one scenario each, with ground truth time ranges marked by hand first.
- Tiered queries: easy (one obvious event), hard (sequence — "opens the door, then enters"), and negative (event absent).
- One platform, all models: the same clip and the same question go to each model, and results are stored in the same format so they can be compared side by side.
- Token and latency logging: a model that is twice as accurate at ten times the cost is a product decision, not just a benchmark win.
That is what this site is: the test platform, opened up. Upload a clip, ask a question, and see the timestamped answer — including the cases where the honest answer is "not found".