CAP-DATA is a large-scale benchmark consisting of 11,727 in-the-wild accident videos with over 2.19 million frames together with labeled fact-effect-reason-introspection description and temporal accident frame label. It can support many useful tasks for accident inference, such as accident detection and prediction (AccidentDet/Pre), causal inference of accident (Accident-Causal), accident classification (Accident-Cla), text-video based accident retrieval (Accident-Retri), and question answering in an accident (Accident-QA) of the driving scene.
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Car Crash Dataset (CCD) is collected for traffic accident analysis. It contains real traffic accident videos captured by dashcam mounted on driving vehicles, which is critical to developing safety-guaranteed self-driving systems. CCD is distinguished from existing datasets for diversified accident annotations, including environmental attributes (day/night, snowy/rainy/good weather conditions), whether ego-vehicles involved, accident participants, and accident reason descriptions.
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