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 801–810 of 4856 papers

Title	Date	Tasks	Status	Hype
Extreme Value Modelling of Feature Residuals for Anomaly Detection in Dynamic Graphs	Oct 8, 2024	Anomaly DetectionTime Series	—Unverified	0
Can LLMs Understand Time Series Anomalies?	Oct 7, 2024	Anomaly DetectionTime Series	CodeCode Available	1
Neural Fourier Modelling: A Highly Compact Approach to Time-Series Analysis	Oct 7, 2024	16kAnomaly Detection	CodeCode Available	1
Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution	Oct 5, 2024	Anomaly DetectionDecision Making	—Unverified	0
Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods	Oct 5, 2024	Anomaly DetectionSelf-Supervised Anomaly Detection	—Unverified	0
Applying Quantum Autoencoders for Time Series Anomaly Detection	Oct 5, 2024	Anomaly DetectionFraud Detection	—Unverified	0
BlockFound: Customized blockchain foundation model for anomaly detection	Oct 5, 2024	Anomaly Detectionmodel	—Unverified	0
Did You Hear That? Introducing AADG: A Framework for Generating Benchmark Data in Audio Anomaly Detection	Oct 4, 2024	Anomaly DetectionAudio Generation	—Unverified	0
Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representations	Oct 4, 2024	Anomaly DetectionTest-time Adaptation	CodeCode Available	0
Domain-Specific Retrieval-Augmented Generation Using Vector Stores, Knowledge Graphs, and Tensor Factorization	Oct 3, 2024	Anomaly DetectionAttribute	—Unverified	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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	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