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 2481–2490 of 4856 papers

Title	Date	Tasks	Status
Refining the Optimization Target for Automatic Univariate Time Series Anomaly Detection in Monitoring Services	Jul 20, 2023	Anomaly DetectionTime Series	—Unverified
Matrix Profile based Anomaly Detection in Streaming Gait Data for Fall Prevention	Jul 18, 2023	Anomaly Detection	—Unverified
You've Got Two Teachers: Co-evolutionary Image and Report Distillation for Semi-supervised Anatomical Abnormality Detection in Chest X-ray	Jul 18, 2023	Anomaly DetectionPseudo Label	—Unverified
Anomaly Detection with Selective Dictionary Learning	Jul 17, 2023	Anomaly DetectionDictionary Learning	CodeCode Available
LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection	Jul 16, 2023	Anomaly DetectionMulti-class Anomaly Detection	—Unverified
Anomaly Detection in Automated Fibre Placement: Learning with Data Limitations	Jul 15, 2023	Anomaly DetectionBinary Classification	—Unverified
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition	Jul 15, 2023	Anomaly DetectionKeyword Spotting	—Unverified
cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations	Jul 14, 2023	Anomaly DetectionBinary Classification	—Unverified
BiGSeT: Binary Mask-Guided Separation Training for DNN-based Hyperspectral Anomaly Detection	Jul 14, 2023	Anomaly Detection	CodeCode Available
DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection	Jul 13, 2023	Anomaly DetectionData Augmentation	CodeCode Available

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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