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 2151–2160 of 4856 papers

Title	Date	Tasks	Status	Hype
Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers	Mar 29, 2023	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation	Mar 29, 2023	Anomaly DetectionMedical Image Analysis	—Unverified	0
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection	Mar 29, 2023	Anomaly DetectionFraud Detection	CodeCode Available	1
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection	Mar 29, 2023	Anomaly DetectionFederated Learning	—Unverified	0
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly Detection	Mar 28, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	1
Attention Boosted Autoencoder for Building Energy Anomaly Detection	Mar 28, 2023	Anomaly Detection	—Unverified	0
Searching for long faint astronomical high energy transients: a data driven approach	Mar 28, 2023	Anomaly DetectionPathfinder	CodeCode Available	1
Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection	Mar 27, 2023	Anomaly DetectionSemi-supervised Anomaly Detection	—Unverified	0
SimpleNet: A Simple Network for Image Anomaly Detection and Localization	Mar 27, 2023	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation	Mar 26, 2023	Anomaly ClassificationAnomaly Detection	CodeCode Available	2

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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