mlsanityData to 7 Oct 2026

A Survey on GANs for Anomaly Detection

arXiv 1906.11632 ↗First posted 27 Jun 2019cs.LG stat.MLcited by 32

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Abstract (arXiv)

Anomaly detection is a significant problem faced in several research areas. Detecting and correctly classifying something unseen as anomalous is a challenging problem that has been tackled in many different manners over the years. Generative Adversarial Networks (GANs) and the adversarial training process have been recently employed to face this task yielding remarkable results. In this paper we survey the principal GAN-based anomaly detection methods, highlighting their pros and cons. Our contributions are the empirical validation of the main GAN models for anomaly detection, the increase of the experimental results on different datasets and the public release of a complete Open Source toolbox for Anomaly Detection using GANs.

Key facts. Cited by 32 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jun 2019.

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Citing papers per year: 2021: 11; 2022: 4; 2023: 1; 2024: 2; 2025: 12; 2026: 2.

32 papers.

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  1. 2024A review on data-driven constitutive laws for solidscited by 35
  2. 2021CreativeGAN: Editing Generative Adversarial Networks for Creative Design Synthesiscited by 24
  3. 2021DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detectioncited by 21
  4. 2021Generative Adversarial Networks (GANs) in Networking: A Comprehensive Survey & Evaluationcited by 11
  5. 2025Mobi-π: Mobilizing Your Robot Learning Policycited by 9
  6. 2022Machine Learning in NextG Networks via Generative Adversarial Networkscited by 8
  7. 2021A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methodscited by 7
  8. 2021Game of GANs: Game-Theoretical Models for Generative Adversarial Networkscited by 6
  9. 2023ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GANcited by 4
  10. 2025We Need to Rethink Benchmarking in Anomaly Detectioncited by 4
  11. 2021PANDA : Perceptually Aware Neural Detection of Anomaliescited by 3
  12. 2021GAN pretraining for deep convolutional autoencoders applied to Software-based Fingerprint Presentation Attack Detectioncited by 3
20 more
  1. 2021Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulatorscited by 3
  2. 2025Unsupervised Surrogate Anomaly Detectioncited by 3
  3. 2021Leveraging 3D Information in Unsupervised Brain MRI Segmentationcited by 2
  4. 2021GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphscited by 2
  5. 2021Margin-Aware Intra-Class Novelty Identification for Medical Imagescited by 2
  6. 2022Alternative Data Augmentation for Industrial Monitoring using Adversarial Learningcited by 2
  7. 2024Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly Detectioncited by 1
  8. 2025Quantifying the uncertainty of model-based synthetic image quality metricscited by 1
  9. 2025Quantum Gated Recurrent GAN with Gaussian Uncertainty for Network Anomaly Detectioncited by 1
  10. 2026Integration of deep generative Anomaly Detection algorithm in high-speed industrial linecited by 1
  11. 2022Driving Anomaly Detection Using Conditional Generative Adversarial Networkcited by 0
  12. 2022Multi-scale Anomaly Detection for Big Time Series of Industrial Sensorscited by 0
  13. 2025Anomaly Detection via Autoencoder Composite Features and NCEcited by 0
  14. 2025A digital eye-fixation biomarker using a deep anomaly scheme to classify Parkisonian patternscited by 0
  15. 2025Adventurer: Exploration with BiGAN for Deep Reinforcement Learningcited by 0
  16. 2025Comparative Study of Generative Models for Early Detection of Failures in Medical Devicescited by 0
  17. 2025A New Spatiotemporal Correlation Anomaly Detection Method that Integrates Contrastive Learning and Few-Shot Learning in Wireless Sensor Networkscited by 0
  18. 2025Dirty and Clean-Label attack detection using GAN discriminatorscited by 0
  19. 2025Towards 6G Intelligence: The Role of Generative AI in Future Wireless Networkscited by 0
  20. 2026Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flowcited by 0