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 1361–1370 of 4856 papers

Title	Date	Tasks	Status	Score
Composite Convolution: a Flexible Operator for Deep Learning on 3D Point Clouds	Sep 23, 2022	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	5
CSCLog: A Component Subsequence Correlation-Aware Log Anomaly Detection Method	Jul 7, 2023	Anomaly Detection	CodeCode Available	5
CKNN: Cleansed k-Nearest Neighbor for Unsupervised Video Anomaly Detection	Aug 6, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	5
Focus or Not: A Baseline for Anomaly Event Detection On the Open Public Places with Satellite Images	Mar 21, 2023	Anomaly DetectionChange Detection	CodeCode Available	5
Few-shot Online Anomaly Detection and Segmentation	Mar 27, 2024	Anomaly Detection	CodeCode Available	5
Anomaly Detection with Selective Dictionary Learning	Jul 17, 2023	Anomaly DetectionDictionary Learning	CodeCode Available	5
Dimensionless Anomaly Detection on Multivariate Streams with Variance Norm and Path Signature	Jun 5, 2020	Anomaly DetectionTime Series	CodeCode Available	5
Fence GAN: Towards Better Anomaly Detection	Apr 2, 2019	Anomaly ClassificationAnomaly Detection	CodeCode Available	5
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain	Jun 12, 2025	Anomaly Detection	CodeCode Available	5
Comparison of Anomaly Detectors: Context Matters	Dec 11, 2020	Anomaly DetectionModel Selection	CodeCode Available	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