ACCIDENT: A Benchmark Dataset for Vehicle Accident Detection from Traffic Surveillance Videos
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Abstract (arXiv)
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
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 26 of its 44 references that are in the map. First posted on arXiv 10 Apr 2026.
Builds on
26 of 44 references.
References · 26
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14 more
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Citing papers per year: 2026: 7.
7 papers.
- 2026Zoom In, Reason Out: Efficient Far-field Anomaly Detection in Expressway Surveillance Videos via Focused VLM Reasoning Guided by Bayesian Inferencecited by 0
- 2026Two-Pass Zero-Shot Temporal-Spatial Grounding of Rare Traffic Events in Surveillance Videocited by 0
- 2026Multi-Stage VLM Pipeline for Zero-Shot Traffic Accident Understandingcited by 0
- 2026Metadata-Aware Multi-Prompt Reasoning for Zero-Shot Accident Understandingcited by 0
- 2026Zero-Shot Traffic Accident Detection via a Coarse-to-Fine VLM-Tracking Pipelinecited by 0
- 2026SynCrash: A Multi-Stage Pipeline for Zero-Shot Accident Detection and Localization in Traffic Surveillance Videocited by 0
- 2026FPV-CRASH: A Dataset for Offline Crash Moment Localization in Drone First-Person-View Videoscited by 0
- 2026FPV-CRASH: A Dataset for Offline Crash Moment Localization in Drone First-Person-View Videos14 Oct 2026
- 2026SynCrash: A Multi-Stage Pipeline for Zero-Shot Accident Detection and Localization in Traffic Surveillance Video30 Aug 2026
- 2026Zero-Shot Traffic Accident Detection via a Coarse-to-Fine VLM-Tracking Pipeline9 Aug 2026
- 2026Metadata-Aware Multi-Prompt Reasoning for Zero-Shot Accident Understanding10 Jun 2026
- 2026Multi-Stage VLM Pipeline for Zero-Shot Traffic Accident Understanding28 May 2026
- 2026Two-Pass Zero-Shot Temporal-Spatial Grounding of Rare Traffic Events in Surveillance Video2 May 2026
- 2026Zoom In, Reason Out: Efficient Far-field Anomaly Detection in Expressway Surveillance Videos via Focused VLM Reasoning Guided by Bayesian Inference26 Apr 2026