Review of Deep Learning-Based Video Anomaly Detection
The study of video anomaly detection involves the methods such as probabilistic statistics,machine learning and deep learning.The purpose of this paper is to synthesize the research results of the author's group and other advanced researches with a focus on deep learning-based video anomaly detection methods,comprehensively discussing the background,challenges and solutions in this field.Most relevant papers in the field are synthesized and systematically analyzed to provide the scholars with a fundamental understanding of the current research progress.The deep learning-based video anomaly detection methods are classified and analyzed.The network model selection for different methods is summarized.The commonly used datasets and performance evaluation indexes are introduced in detail.The advantages of various methods are highlighted by the performance comparison,and the future research directions and application scenarios in the field of video anomaly detection are deeply explored and forecasted.
Video Anomaly DetectionDeep LearningPseudo AnomalyConvolutional Neural Net-workMultiple Instance Learning
万方数据
维普
