Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3031–3040 of 4856 papers

Title	Date	Tasks	Status	Hype
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation	Dec 19, 2021	Anomaly DetectionKnowledge Distillation	CodeCode Available	1
A Deep Learning Approach for Ontology Enrichment from Unstructured Text	Dec 16, 2021	Anomaly DetectionDeep Learning	—Unverified	0
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization	Dec 16, 2021	3D Anomaly Detection and SegmentationAnomaly Detection	CodeCode Available	1
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data	Dec 15, 2021	Anomaly DetectionAstronomy	—Unverified	0
Utilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP)	Dec 14, 2021	Anomaly DetectionExplainable artificial intelligence	—Unverified	0
Noise Reduction and Driving Event Extraction Method for Performance Improvement on Driving Noise-based Surface Anomaly Detection	Dec 14, 2021	Anomaly DetectionComputational Efficiency	—Unverified	0
Approaches Toward Physical and General Video Anomaly Detection	Dec 14, 2021	Anomaly DetectionDensity Estimation	CodeCode Available	0
Out-of-Distribution Detection Without Class Labels	Dec 14, 2021	Anomaly DetectionClustering	—Unverified	0
Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions	Dec 13, 2021	Anomaly DetectionDefect Detection	—Unverified	0
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection	Dec 13, 2021	Anomaly DetectionAttribute	CodeCode Available	0

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All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified