Unsupervised Anomaly Detection

The objective of Unsupervised Anomaly Detection is to detect previously unseen rare objects or events without any prior knowledge about these. The only information available is that the percentage of anomalies in the dataset is small, usually less than 1%. Since anomalies are rare and unknown to the user at training time, anomaly detection in most cases boils down to the problem of modelling the normal data distribution and defining a measurement in this space in order to classify samples as anomalous or normal. In high-dimensional data such as images, distances in the original space quickly lose descriptive power (curse of dimensionality) and a mapping to some more suitable space is required.

Source: Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 26–50 of 506 papers

Title	Date	Tasks	Status	Hype	Score
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection	Oct 6, 2021	Anomaly DetectionDefect Detection	CodeCode Available	1	5
Fast Unsupervised Anomaly Detection in Traffic Videos	Jul 28, 2020	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1	5
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images	Mar 5, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization	Apr 8, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1	5
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances	Jul 16, 2020	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
Federated PCA on Grassmann Manifold for IoT Anomaly Detection	Jul 10, 2024	Anomaly DetectionIntrusion Detection	CodeCode Available	1	5
FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data	Nov 25, 2024	Anomaly DetectionOne-Class Classification	CodeCode Available	1	5
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series	Jun 13, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1	5
Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection	Oct 19, 2022	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1	5
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly Detection	Mar 18, 2024	Anomaly DetectionDenoising	CodeCode Available	1	5
Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images	Mar 13, 2024	AnatomyAnomaly Detection	CodeCode Available	1	5
DSR -- A dual subspace re-projection network for surface anomaly detection	Aug 2, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study	Apr 7, 2020	AnatomyAnomaly Detection	CodeCode Available	1	5
Attention-based residual autoencoder for video anomaly detection	May 25, 2022	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1	5
DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection	Aug 17, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1	5
DyEdgeGAT: Dynamic Edge via Graph Attention for Early Fault Detection in IIoT Systems	Jul 7, 2023	Anomaly DetectionFault Detection	CodeCode Available	1	5
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model	Aug 31, 2024	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1	5
A General Framework For Detecting Anomalous Inputs to DNN Classifiers	Jul 29, 2020	Anomaly Detectionimage-classification	CodeCode Available	1	5
Clustered Hierarchical Anomaly and Outlier Detection Algorithms	Feb 9, 2021	Anomaly DetectionClustering	CodeCode Available	1	5
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows	Jul 27, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1	5
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization	Jun 9, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-Decoder	Mar 21, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
AnoShift: A Distribution Shift Benchmark for Unsupervised Anomaly Detection	Jun 30, 2022	Intrusion DetectionNetwork Intrusion Detection	CodeCode Available	1	5
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data	May 25, 2021	Anomaly DetectionConformal Prediction	CodeCode Available	1	5
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms	Apr 21, 2022	Anomaly DetectionFraud Detection	CodeCode Available	1	5

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All datasets AnoShift SMAP Vehicle Claims Fashion-MNIST KolektorSDD2 20NEWS AeBAD-S Caltech-101 DAGM2007 ECG5000 KolektorSDD MNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ACR-NTL (zero-shot, test anomaly ratio=1%)	ROC-AUC FAR	62.5	—	Unverified
2	ACR-DSVDD (zero-shot, anomaly ratio=1%)	ROC-AUC FAR	62	—	Unverified
3	ACR-NTL (zero-shot, test anomaly ratio=20%)	ROC-AUC FAR	62	—	Unverified
4	ACR-DSVDD (zero-shot, anomaly ratio=20%)	ROC-AUC FAR	59.1	—	Unverified
5	COPOD	ROC-AUC FAR	50.42	—	Unverified
6	OC-SVM	ROC-AUC FAR	49.57	—	Unverified
7	SO-GAAL	ROC-AUC FAR	49.35	—	Unverified
8	ECOD Li et al. (2022)	ROC-AUC FAR	49.19	—	Unverified
9	LOF	ROC-AUC FAR	34.96	—	Unverified
10	deepSVDD	ROC-AUC FAR	34.53	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DFM (flow matching)	F1	94.1	—	Unverified
2	ContextFlow++ (Glow-based)	F1	93.62	—	Unverified
3	TranAd	F1	89.15	—	Unverified
4	MTAD-GAT	F1	88.8	—	Unverified
5	CAE-M	F1	88.27	—	Unverified
6	OmniAnomaly	F1	87.28	—	Unverified
7	Glow	F1	86.05	—	Unverified
8	GDN	F1	85.18	—	Unverified
9	USAD	F1	81.86	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SOM	AUC	65.43	—	Unverified
2	Isolation Forest	AUC	59.42	—	Unverified
3	Latent Outlier Exposure	AUC	58.59	—	Unverified
4	NeuTraL-AD	AUC	57.03	—	Unverified
5	RSRAE	AUC	55.38	—	Unverified
6	SOM-DAGMM	AUC	53.82	—	Unverified
7	Local Outlier Factor	AUC	52.86	—	Unverified
8	One Class Support Vector Machines	AUC	51.68	—	Unverified
9	DAGMM	AUC	51.22	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RSRAE	AUC-ROC	0.85	—	Unverified
2	RSRAE	AUC (outlier ratio = 0.5)	0.83	—	Unverified
3	RSRAE	AUC-ROC	0.75	—	Unverified
4	RSRAE	AUC-ROC	0.69	—	Unverified
5	RSRAE	AUC-ROC	0.69	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Semi-orthogonal	Segmentation AUROC	98.1	—	Unverified
2	WeakREST-Un	Segmentation AP	76.9	—	Unverified
3	DSR	Segmentation AP	61.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RSRAE	AUC (outlier ratio = 0.5)	0.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSFR	Detection AUROC	87.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RSRAE	AUC (outlier ratio = 0.5)	0.77	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DiffusionAD	Detection AUROC	99.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VRAE+SVM	AUC	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Semi-orthogonal	Segmentation AUROC	96	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LVAD	AUROC	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DyEdgeGAT	AUC	0.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RSRAE	AUC (outlier ratio = 0.5)	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	TranAD	Precision	92.62	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LVAD	AUC-ROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DyEdgeGAT	AUC	0.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	P-CAE W-MSE (Tilted View)	AUROC	78.1	—	Unverified