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 661–670 of 4856 papers

Title	Date	Tasks	Status	Hype
FrAug: Frequency Domain Augmentation for Time Series Forecasting	Feb 18, 2023	Anomaly DetectionData Augmentation	CodeCode Available	1
Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection	Dec 4, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow	May 16, 2023	Anomaly DetectionOut-of-Distribution Detection	CodeCode Available	1
Deep and Confident Prediction for Time Series at Uber	Sep 6, 2017	Anomaly DetectionPrediction	CodeCode Available	1
Anomaly Detection in Medical Imaging with Deep Perceptual Autoencoders	Jun 23, 2020	Anomaly DetectionMedical Image Analysis	CodeCode Available	1
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis	Oct 18, 2023	Anomaly DetectionImputation	CodeCode Available	1
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset	Sep 30, 2024	Anomaly Detection	CodeCode Available	1
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction	Jun 2, 2023	Anomaly DetectionFraud Detection	CodeCode Available	1
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection	Mar 29, 2023	Anomaly DetectionFraud Detection	CodeCode Available	1
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting	Dec 22, 2023	Anomaly DetectionTime Series	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