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 771–780 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile Robots	Aug 26, 2020	Anomaly DetectionSegmentation	CodeCode Available	1	5
Few-shot Network Anomaly Detection via Cross-network Meta-learning	Feb 22, 2021	Anomaly DetectionFew-Shot Learning	CodeCode Available	1	5
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images	Aug 9, 2020	AnatomyAnomaly Detection	CodeCode Available	1	5
Raising the Bar in Graph-level Anomaly Detection	May 27, 2022	Anomaly DetectionFraud Detection	CodeCode Available	1	5
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study	Nov 5, 2023	Anomaly Detection	CodeCode Available	1	5
Enhancing the Analysis of Software Failures in Cloud Computing Systems with Deep Learning	Jun 29, 2021	Anomaly DetectionCloud Computing	CodeCode Available	1	5
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection	Oct 14, 2022	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1	5
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language Processing	Apr 11, 2021	Anomaly Detection	CodeCode Available	1	5
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters	Aug 19, 2020	Anomaly DetectionFraud Detection	CodeCode Available	1	5
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection	Jul 3, 2023	Anomaly DetectionImputation	CodeCode Available	1	5

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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