UBI-Fights (Abnormal Event Detection Dataset)
Introduced by Degardin et al. in Iterative weak/self-supervised classification framework for abnormal events detection
UBI-Fights - Concerning a specific anomaly detection and still providing a wide diversity in fighting scenarios, the UBI-Fights dataset is a unique new large-scale dataset of 80 hours of video fully annotated at the frame level. Consisting of 1000 videos, where 216 videos contain a fight event, and 784 are normal daily life situations. All unnecessary video segments (e.g., video introductions, news, etc.) that could disturb the learning process were removed.
Benchmarks
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UBI-Fights
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SS-Model + WS-Model + Sultani et al.
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UBI-Fights
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GMM
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Papers
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