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Anomaly Detection in Video Sequences: A Benchmark and Computational Model
[article]
2021
arXiv
pre-print
Anomaly detection has attracted considerable search attention. However, existing anomaly detection databases encounter two major problems. Firstly, they are limited in scale. Secondly, training sets contain only video-level labels indicating the existence of an abnormal event during the full video while lacking annotations of precise time durations. To tackle these problems, we contribute a new Large-scale Anomaly Detection (LAD) database as the benchmark for anomaly detection in video
arXiv:2106.08570v1
fatcat:oeju32uh65fpliiewsfmhupu44