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 761–770 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays	Jun 8, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available	1	5
Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images	Oct 9, 2022	Anomaly DetectionSelf-Supervised Learning	CodeCode Available	1	5
Dual-path Frequency Discriminators for Few-shot Anomaly Detection	Mar 7, 2024	Anomaly Detection	CodeCode Available	1	5
Dual Task Learning by Leveraging Both Dense Correspondence and Mis-Correspondence for Robust Change Detection With Imperfect Matches	Jan 1, 2022	Anomaly DetectionChange Detection	CodeCode Available	1	5
Dynamic Distinction Learning: Adaptive Pseudo Anomalies for Video Anomaly Detection	Apr 7, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1	5
Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms	Mar 3, 2021	Anomaly DetectionSelf-Driving Cars	CodeCode Available	1	5
A Survey of World Models for Autonomous Driving	Jan 20, 2025	Anomaly DetectionAutonomous Driving	CodeCode Available	1	5
Hybrid Open-set Segmentation with Synthetic Negative Data	Jan 19, 2023	Anomaly DetectionSegmentation	CodeCode Available	1	5
A Survey of Visual Sensory Anomaly Detection	Feb 14, 2022	Anomaly DetectionSurvey	CodeCode Available	1	5
Learning a Cross-modality Anomaly Detector for Remote Sensing Imagery	Oct 11, 2023	Anomaly DetectionDiversity	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