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 4401–4410 of 4856 papers

Title	Date	Tasks	Status
Rule Extraction in Unsupervised Anomaly Detection for Model Explainability: Application to OneClass SVM	Nov 21, 2019	Anomaly DetectionDiversity	CodeCode Available
UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring	Nov 19, 2021	Anomaly DetectionData Visualization	CodeCode Available
Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC	May 30, 2025	Anomaly DetectionQuantum Machine Learning	CodeCode Available
Anomaly Detection using Principles of Human Perception	Mar 23, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available
BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection	Jul 5, 2022	Anomaly DetectionAutonomous Driving	CodeCode Available
Graph Laplacian for Image Anomaly Detection	Feb 27, 2018	Anomaly Detection	CodeCode Available
Graph Fairing Convolutional Networks for Anomaly Detection	Oct 20, 2020	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available
An anomaly detection approach for backdoored neural networks: face recognition as a case study	Aug 22, 2022	Anomaly DetectionFace Recognition	CodeCode Available
SADDE: Semi-supervised Anomaly Detection with Dependable Explanations	Nov 18, 2024	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available
Multivariate Time Series Anomaly Detection: Fancy Algorithms and Flawed Evaluation Methodology	Aug 24, 2023	Anomaly DetectionTime Series	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	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