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 1111–1120 of 4856 papers

Title	Date	Tasks	Status	Hype
Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection	Jun 11, 2024	Anomaly DetectionDefect Detection	—Unverified	0
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection	Jun 11, 2024	Anomaly DetectionDenoising	CodeCode Available	2
RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection	Jun 11, 2024	Anomaly DetectionBenchmarking	CodeCode Available	1
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving	Jun 10, 2024	Anomaly DetectionAutonomous Driving	—Unverified	0
fSEAD: a Composable FPGA-based Streaming Ensemble Anomaly Detection Library	Jun 10, 2024	Anomaly DetectionCPU	CodeCode Available	0
UMAD: Unsupervised Mask-Level Anomaly Detection for Autonomous Driving	Jun 10, 2024	Anomaly DetectionAutonomous Driving	—Unverified	0
RAPID: Robust APT Detection and Investigation Using Context-Aware Deep Learning	Jun 8, 2024	Anomaly DetectionComputational Efficiency	—Unverified	0
VisionAD, a software package of performant anomaly detection algorithms, and Proportion Localised, an interpretable metric	Jun 7, 2024	Anomaly DetectionBenchmarking	CodeCode Available	0
Higher-order Structure Based Anomaly Detection on Attributed Networks	Jun 7, 2024	Anomaly DetectionAttribute	—Unverified	0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical Applications	Jun 7, 2024	Anomaly DetectionImage Generation	CodeCode Available	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	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