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 911–920 of 4856 papers

Title	Date	Tasks	Status	Hype
Active Anomaly Detection via Ensembles	Sep 17, 2018	Active LearningAnomaly Detection	CodeCode Available	1
How To Backdoor Federated Learning	Jul 2, 2018	Anomaly DetectionData Poisoning	CodeCode Available	1
Future Frame Prediction for Anomaly Detection â A New Baseline	Jun 1, 2018	Anomaly DetectionOptical Flow Estimation	CodeCode Available	1
Deep Anomaly Detection Using Geometric Transformations	May 28, 2018	Anomaly Detection	CodeCode Available	1
Real-world Anomaly Detection in Surveillance Videos	Jan 12, 2018	Abnormal Event Detection In VideoActivity Recognition	CodeCode Available	1
Future Frame Prediction for Anomaly Detection -- A New Baseline	Dec 28, 2017	Anomaly DetectionOptical Flow Estimation	CodeCode Available	1
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs	Dec 11, 2017	Anomaly DetectionSpecificity	CodeCode Available	1
Deep and Confident Prediction for Time Series at Uber	Sep 6, 2017	Anomaly DetectionPrediction	CodeCode Available	1
Incorporating Feedback into Tree-based Anomaly Detection	Aug 30, 2017	Anomaly Detection	CodeCode Available	1
Unsupervised Body Part Regression via Spatially Self-ordering Convolutional Neural Networks	Jul 12, 2017	Anomaly Detectionregression	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	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