# ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos Source: [ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos]() Collection index: [llms.txt]() Data updated: 2026-04-15T05:00:04.591Z Authors: Lukas Picek, Michal \\v{C}erm\\'ak, Marek Hanzl, Vojt\\v{e}ch \\v{C}erm\\'ak Published: 2026-04-10T18:51:19.000Z ## Abstract We introduce ACCIDENT, a benchmark dataset for traffic accident detection in CCTV footage, designed to evaluate models in supervised (IID and OOD) and zero-shot settings, reflecting both data-rich and data-scarce scenarios. The benchmark consists of a curated set of 2,027 real and 2,211 synthetic clips annotated with the accident time, spatial location, and high-level collision type. We define three core tasks: (i) temporal localization of the accident, (ii) its spatial localization, and (iii) collision type classification. Each task is evaluated using custom metrics that account for the uncertainty and ambiguity inherent in CCTV footage. In addition to the benchmark, we provide a diverse set of baselines, including heuristic, motion-aware, and vision-language approaches, and show that ACCIDENT is challenging. You can access the ACCIDENT at: https://accidentbench.github.io ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Traffic Accident Understanding on ACCIDENT Leaderboard (private)](): Traffic Accident Understanding; ACCIDENT Leaderboard (private); C: 29.3. ## Original sources and implementation [Original paper]() [PDF]()