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 571–580 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly Localization	Aug 30, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
A Survey of World Models for Autonomous Driving	Jan 20, 2025	Anomaly DetectionAutonomous Driving	CodeCode Available	1	5
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT Networks	Dec 23, 2022	Anomaly DetectionPrivacy Preserving	CodeCode Available	1	5
FedTADBench: Federated Time-Series Anomaly Detection Benchmark	Dec 19, 2022	Anomaly DetectionFederated Learning	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
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection	May 22, 2021	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1	5
Anomaly detection in surveillance videos using transformer based attention model	Jun 3, 2022	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1	5
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction	Jun 2, 2023	Anomaly DetectionFraud Detection	CodeCode Available	1	5
Attention-based residual autoencoder for video anomaly detection	May 25, 2022	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1	5
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving	May 13, 2024	Anomaly DetectionAutonomous Driving	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