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 221–230 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Active Anomaly Detection via Ensembles	Sep 17, 2018	Active LearningAnomaly Detection	CodeCode Available	1	5
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving	May 13, 2024	Anomaly DetectionAutonomous Driving	CodeCode Available	1	5
Coniferest: a complete active anomaly detection framework	Oct 22, 2024	Anomaly DetectionOutlier Detection	CodeCode Available	1	5
Anomaly Detection using Score-based Perturbation Resilience	Jan 1, 2023	Anomaly DetectionDenoising	CodeCode Available	1	5
A Principled Approach to Enriching Security-related Data for Running Processes through Statistics and Natural Language Processing	Apr 11, 2021	Anomaly Detection	CodeCode Available	1	5
Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images	Mar 5, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame Detection	Mar 23, 2022	Anomaly DetectionMultiple Instance Learning	CodeCode Available	1	5
ARCADe: A Rapid Continual Anomaly Detector	Aug 10, 2020	Anomaly Detectioncontinual anomaly detection	CodeCode Available	1	5
ARC: A Generalist Graph Anomaly Detector with In-Context Learning	May 27, 2024	Anomaly DetectionARC	CodeCode Available	1	5
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video Dataset	Jul 5, 2024	Action RecognitionAnomaly Detection	CodeCode Available	1	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