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An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos

arXiv 1801.03149 ↗First posted 9 Jan 2018cs.CVcited by 45

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Abstract (arXiv)

Videos represent the primary source of information for surveillance applications and are available in large amounts but in most cases contain little or no annotation for supervised learning. This article reviews the state-of-the-art deep learning based methods for video anomaly detection and categorizes them based on the type of model and criteria of detection. We also perform simple studies to understand the different approaches and provide the criteria of evaluation for spatio-temporal anomaly detection.

Key facts. Cited by 45 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jan 2018.

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Citing papers per year: 2021: 15; 2022: 12; 2023: 9; 2024: 6; 2025: 3.

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  1. 2022ADBench: Anomaly Detection Benchmarkcited by 230
  2. 2023Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Modelscited by 59
  3. 2024A Closer Look at AUROC and AUPRC under Class Imbalancecited by 56
  4. 2022TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysiscited by 48
  5. 2022Self-Supervised Masking for Unsupervised Anomaly Detection and Localizationcited by 43
  6. 2022Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Seriescited by 42
  7. 2021Unsupervised Deep Anomaly Detection for Multi-Sensor Time-Series Signalscited by 41
  8. 2022Self-Supervised Anomaly Detection in Computer Vision and Beyond: A Survey and Outlookcited by 24
  9. 2023TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detectioncited by 23
  10. 2023Federated Learning for Computer Visioncited by 22
  11. 2021DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detectioncited by 21
  12. 2021Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinementcited by 21
33 more
  1. 2024Networking Systems for Video Anomaly Detection: A Tutorial and Surveycited by 21
  2. 2021Reconstruction Student with Attention for Student-Teacher Pyramid Matchingcited by 20
  3. 2022Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detectioncited by 18
  4. 2024Video Anomaly Detection in 10 Years: A Survey and Outlookcited by 18
  5. 2021EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG with An Application to Emotion Recognitioncited by 15
  6. 2021Deep Video Anomaly Detection: Opportunities and Challengescited by 14
  7. 2023Generating and Reweighting Dense Contrastive Patterns for Unsupervised Anomaly Detectioncited by 14
  8. 2021TIMo -- A Dataset for Indoor Building Monitoring with a Time-of-Flight Cameracited by 9
  9. 2021A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methodscited by 7
  10. 2022Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Datasetcited by 7
  11. 2022Unsupervised Anomaly Detection from Time-of-Flight Depth Imagescited by 6
  12. 2022Overlooked Video Classification in Weakly Supervised Video Anomaly Detectioncited by 6
  13. 2021Bayesian Autoencoders: Analysing and Fixing the Bernoulli likelihood for Out-of-Distribution Detectioncited by 4
  14. 2021Anomaly Crossing: New Horizons for Video Anomaly Detection as Cross-domain Few-shot Learningcited by 3
  15. 2022AnoDFDNet: A Deep Feature Difference Network for Anomaly Detectioncited by 2
  16. 2023Industrial and Medical Anomaly Detection Through Cycle-Consistent Adversarial Networkscited by 2
  17. 2023Anomaly detection with semi-supervised classification based on risk estimatorscited by 2
  18. 2025ALARM: Automated MLLM-Based Anomaly Detection in Complex-EnviRonment Monitoring with Uncertainty Quantificationcited by 2
  19. 2021Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Losscited by 1
  20. 2021Training Deep Normalizing Flow Models in Highly Incomplete Data Scenarios with Prior Regularizationcited by 1
  21. 2021Unsupervised Learning of Multi-level Structures for Anomaly Detectioncited by 1
  22. 2022Spatio-Temporal Relation Learning for Video Anomaly Detectioncited by 1
  23. 2023Deep Neural Networks in Video Human Action Recognition: A Reviewcited by 1
  24. 2024Benchmarking Anomaly Detection Algorithms: Deep Learning and Beyondcited by 1
  25. 2021"Forget" the Forget Gate: Estimating Anomalies in Videos using Self-contained Long Short-Term Memory Networkscited by 0
  26. 2021Exploring the Intrinsic Probability Distribution for Hyperspectral Anomaly Detectioncited by 0
  27. 2022Statistics and Deep Learning-based Hybrid Model for Interpretable Anomaly Detectioncited by 0
  28. 2023Parkinson gait modelling from an anomaly deep representationcited by 0
  29. 2023Unleashing the Potential of Unsupervised Deep Outlier Detection through Automated Training Stoppingcited by 0
  30. 2024An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw Cyclecited by 0
  31. 2024Abnormal Event Detection In Videos Using Deep Embeddingcited by 0
  32. 2025A Radon-Nikod'ym Perspective on Anomaly Detection: Theory and Implicationscited by 0
  33. 2025Artificial Intelligence and Deep Learning Algorithms for Epigenetic Sequence Analysis: A Review for Epigeneticists and AI Expertscited by 0