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 441–450 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection	Apr 7, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1	5
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection	Jul 17, 2023	Anomaly DetectionGraph Learning	CodeCode Available	1	5
Active Anomaly Detection via Ensembles	Sep 17, 2018	Active LearningAnomaly Detection	CodeCode Available	1	5
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature	Jun 11, 2020	Anomaly DetectionArticles	CodeCode Available	1	5
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection	Mar 27, 2020	Anomaly DetectionBinary Classification	CodeCode Available	1	5
IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing	Jan 31, 2023	Anomaly DetectionContinual Learning	CodeCode Available	1	5
Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection	Jul 22, 2022	Anomaly DetectionDiversity	CodeCode Available	1	5
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots	Sep 20, 2022	Anomaly Detection	CodeCode Available	1	5
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization	Apr 8, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1	5
Dual-path Frequency Discriminators for Few-shot Anomaly Detection	Mar 7, 2024	Anomaly 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