Datasets › Labelling for Explosions and Road accidents from UCF-Crime
Labelling for Explosions and Road accidents from UCF-Crime
The whole UCF-Crime dataset consists of real-world 240 × 320 RGB videos with 13 realistic anomaly types such as explosion, road accident, burglary, etc., and normal examples. The CPD specific requires a change in data distribution. We suppose that explosions and road accidents correspond to such a scenario, while most other types correspond to point anomalies. For example, data, obviously, com from a normal regime before the explosion. After it, we can see fire and smoke, which last for some time. Thus, the first moment when an explosion appears is a change point. Along with a volunteer, the authors carefully labelled chosen anomaly types. Their opinions were averaged. We provide the obtained markup, so other researchers can use it to validate their CPD algorithm for video.
Benchmarks archive 2025-07-28
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Papers archive 2025-07-28
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Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
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Variants archive 2025-07-28
- Labelling for Explosions and Road accidents from UCF-Crime
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