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
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?	May 4, 2024	Anomaly DetectionBenchmarking	CodeCode Available	1
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection	May 3, 2024	Anomaly DetectionAttribute	CodeCode Available	1
Dr-SAM: An End-to-End Framework for Vascular Segmentation, Diameter Estimation, and Anomaly Detection on Angiography Images	Apr 25, 2024	Anomaly DetectionDiagnostic	CodeCode Available	1
Blind Localization and Clustering of Anomalies in Textures	Apr 18, 2024	Anomaly DetectionAnomaly Localization	CodeCode Available	1
DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series	Apr 17, 2024	Anomaly DetectionContrastive Learning	CodeCode Available	1
FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and Discrimination	Apr 12, 2024	Anomaly DetectionModel Optimization	CodeCode Available	1
SplatPose & Detect: Pose-Agnostic 3D Anomaly Detection	Apr 10, 2024	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection	Apr 7, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline	Apr 1, 2024	Anomaly DetectionPrivacy Preserving	CodeCode Available	1
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection	Mar 20, 2024	Anomaly DetectionMulti-class Anomaly 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