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 3591–3600 of 4856 papers

Title	Date	Tasks	Status	Hype
Learning Deep Latent Variable Models via Amortized Langevin Dynamics	Jan 1, 2021	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Sparse Coding-inspired GAN for Weakly Supervised Hyperspectral Anomaly Detection	Jan 1, 2021	Anomaly DetectionDecoder	—Unverified	0
GenAD: General Representations of Multivariate Time Series for Anomaly Detection	Jan 1, 2021	Anomaly DetectionManagement	—Unverified	0
Understanding Bias in Anomaly Detection: A Semi-Supervised View with PAC Guarantees	Jan 1, 2021	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	0
Domain Adaptation via Anaomaly Detection	Jan 1, 2021	Anomaly DetectionDomain Adaptation	—Unverified	0
Anomaly detection in dynamical systems from measured time series	Jan 1, 2021	Anomaly DetectionBenchmarking	—Unverified	0
Data Transformer for Anomalous Trajectory Detection	Jan 1, 2021	Anomaly Detection	—Unverified	0
Unsupervised Anomaly Detection by Robust Collaborative Autoencoders	Jan 1, 2021	Anomaly DetectionMissing Values	CodeCode Available	1
A General Framework for Unsupervised Anomaly Detection	Jan 1, 2021	Anomaly DetectionOut-of-Distribution Detection	—Unverified	0
Dynamic Graph-Based Anomaly Detection in the Electrical Grid	Dec 30, 2020	Anomaly Detection	CodeCode Available	1

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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	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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