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 251–260 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
DATE: Detecting Anomalies in Text via Self-Supervision of Transformers	Apr 12, 2021	Anomaly Detection	CodeCode Available	1	5
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector	Oct 9, 2024	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	1	5
Deep Anomaly Detection Using Geometric Transformations	May 28, 2018	Anomaly Detection	CodeCode Available	1	5
Auto-Encoding Variational Bayes	Dec 20, 2013	Anomaly DetectionImage Clustering	CodeCode Available	1	5
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis	Feb 20, 2023	Anomaly DetectionDeep Reinforcement Learning	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
A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting	Nov 5, 2022	Anomaly Detectionregression	CodeCode Available	1	5
Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detections	Apr 15, 2025	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
ADNet: Temporal Anomaly Detection in Surveillance Videos	Apr 14, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	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

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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