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 1021–1030 of 4856 papers

Title	Date	Tasks	Status	Hype
Harnessing Feature Clustering For Enhanced Anomaly Detection With Variational Autoencoder And Dynamic Threshold	Jul 14, 2024	Anomaly DetectionClustering	—Unverified	0
Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models	Jul 14, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	2
A Survey of Distance-Based Vessel Trajectory Clustering: Data Pre-processing, Methodologies, Applications, and Experimental Evaluation	Jul 13, 2024	Anomaly DetectionClustering	—Unverified	0
Imbalanced Graph-Level Anomaly Detection via Counterfactual Augmentation and Feature Learning	Jul 13, 2024	Anomaly DetectionAttribute	CodeCode Available	0
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning	Jul 12, 2024	Anomaly DetectionBackdoor Attack	—Unverified	0
Unsupervised Anomaly Detection Using Diffusion Trend Analysis	Jul 12, 2024	Anomaly DetectionDenoising	—Unverified	0
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization	Jul 12, 2024	Anomaly DetectionDefect Detection	CodeCode Available	3
Deep Learning for Network Anomaly Detection under Data Contamination: Evaluating Robustness and Mitigating Performance Degradation	Jul 11, 2024	Anomaly Detection	—Unverified	0
Real-Time Anomaly Detection and Reactive Planning with Large Language Models	Jul 11, 2024	Anomaly DetectionAutonomous Vehicles	—Unverified	0
Federated PCA on Grassmann Manifold for IoT Anomaly Detection	Jul 10, 2024	Anomaly DetectionIntrusion Detection	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