GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
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Summary
This work introduces a novel anomaly detection model, by using a conditional generative adversarial network that jointly learns the generation of high-dimensional image space and the inference of latent space and shows the model efficacy and superiority over previous state-of-the-art approaches.
- Type
- preprint
- Published
- 2018-05-17
- Cited by
- 1,767
- References
- 55
- Access
- Open access
- OpenAlex
- https://openalex.org/W2803446235
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:21688963
Keywords
Anomaly detection, Artificial intelligence, Computer science, Inference, Benchmark (surveying)
References
- Automated X-ray image analysis for cargo security: Critical review and future promise
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- A review of automated image understanding within 3D baggage computed tomography security screening
- Real-time anomaly detection and localization in crowded scenes
- Anomaly detection
- Novelty detection: a review - part 1: statistical approaches
- A review of novelty detection
- Anomaly detection: A survey
- Conditional Generative Adversarial Nets
- A Survey of Outlier Detection Methodologies
- A survey of network anomaly detection techniques
- Data fusion
- Learning Temporal Regularity in Video Sequences
- Context Encoders: Feature Learning by Inpainting
- Improved Techniques for Training GANs
- InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
- Spatial-temporal convolutional neural networks for anomaly detection and localization in crowded scenes
- Fraud detection system: A survey
- Image-to-Image Translation with Conditional Adversarial Networks
- Anomaly Detection in Video Using Predictive Convolutional Long Short-Term Memory Networks
Cited by
- Learning Fast and Slow: Propedeutica for Real-Time Malware Detection
- Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data
- Generative Adversarial Active Learning for Unsupervised Outlier Detection
- Deep embeddings for novelty detection in myopathy
- Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detection
- Coupled IGMM-GANs for improved generative adversarial anomaly detection
- AnomalyNet: An Anomaly Detection Network for Video Surveillance
- Anomaly Detection with Adversarial Dual Autoencoders
- Fence GAN: Towards Better Anomaly Detection
- Towards an Explainable Threat Detection Tool
- Detecting the Unexpected via Image Resynthesis
- Supervised Anomaly Detection based on Deep Autoregressive Density Estimators
- Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery
- Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training
- Spatio-temporal adversarial learning for detecting unseen falls
- Anomaly Detection in Images
- Deep Semi-Supervised Anomaly Detection
- Exploring High-Order Correlations for Industry Anomaly Detection
- A Novel and Efficient CVAE-GAN-Based Approach With Informative Manifold for Semi-Supervised Anomaly Detection
- A Survey on GANs for Anomaly Detection
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