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 3451–3460 of 4856 papers

Title	Date	Tasks	Status
Unsupervised Anomaly Detection in MR Images using Multi-Contrast Information	May 2, 2021	Anomaly DetectionDensity Estimation	—Unverified
Unsupervised Anomaly Detection in Parole Hearings using Language Models	Nov 1, 2020	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Unsupervised Anomaly Detection in Stream Data with Online Evolving Spiking Neural Networks	Dec 18, 2019	Anomaly DetectionTime Series Analysis	—Unverified
Unsupervised Anomaly Detection in Time-series: An Extensive Evaluation and Analysis of State-of-the-art Methods	Dec 6, 2022	Anomaly DetectionTime Series	—Unverified
Unsupervised Anomaly Detection of Paranasal Anomalies in the Maxillary Sinus	Nov 1, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Unsupervised anomaly detection on cybersecurity data streams: a case with BETH dataset	Mar 6, 2025	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Unsupervised Anomaly Detection on Implicit Shape representations for Sarcopenia Detection	Feb 13, 2025	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Unsupervised Anomaly Detection on Temporal Multiway Data	Sep 20, 2020	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Unsupervised Anomaly Detection Using Diffusion Trend Analysis	Jul 12, 2024	Anomaly DetectionDenoising	—Unverified
Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling	Apr 27, 2024	Anomaly DetectionImage Reconstruction	—Unverified

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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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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