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 291–300 of 4856 papers

Title	Date	Tasks	Status	Hype
Risk-Based Thresholding for Reliable Anomaly Detection in Concentrated Solar Power Plants	Mar 24, 2025	Anomaly Detection	—Unverified	0
Towards Training-free Anomaly Detection with Vision and Language Foundation Models	Mar 24, 2025	Anomaly Detection	CodeCode Available	2
RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data	Mar 24, 2025	Anomaly DetectionContrastive Learning	CodeCode Available	0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos	Mar 24, 2025	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified	0
Anomize: Better Open Vocabulary Video Anomaly Detection	Mar 23, 2025	Anomaly DetectionVideo Anomaly Detection	—Unverified	0
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model	Mar 23, 2025	Anomaly DetectionDrug Discovery	CodeCode Available	0
Anomaly Detection and Localization for Speech Deepfakes via Feature Pyramid Matching	Mar 23, 2025	Anomaly DetectionDeepFake Detection	—Unverified	0
Assessing workflow impact and clinical utility of AI-assisted brain aneurysm detection: a multi-reader study	Mar 22, 2025	Anomaly DetectionSensitivity	—Unverified	0
TRACE: Time SeRies PArameter EffiCient FinE-tuning	Mar 21, 2025	Anomaly Detectionparameter-efficient fine-tuning	—Unverified	0
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series	Mar 21, 2025	Anomaly DetectionBenchmarking	—Unverified	0

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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	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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