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 851–860 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Anomalous Sound Detection as a Simple Binary Classification Problem with Careful Selection of Proxy Outlier Examples	Nov 5, 2020	Anomaly DetectionBinary Classification	CodeCode Available	1	5
GAN Ensemble for Anomaly Detection	Dec 14, 2020	Anomaly Detection	CodeCode Available	1	5
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance	Jan 3, 2024	Anomaly Detection	CodeCode Available	1	5
Iterative weak/self-supervised classification framework for abnormal events detection	Jan 3, 2021	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1	5
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection	Dec 23, 2024	Anomaly DetectionPrompt Learning	CodeCode Available	1	5
Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval	Aug 13, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1	5
Isolation Distributional Kernel: A New Tool for Point & Group Anomaly Detection	Sep 24, 2020	Anomaly DetectionGroup Anomaly Detection	CodeCode Available	1	5
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection	Oct 14, 2022	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1	5
Isolation Mondrian Forest for Batch and Online Anomaly Detection	Mar 8, 2020	Anomaly DetectionEnsemble Learning	CodeCode Available	1	5
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers	Oct 7, 2023	Anomaly DetectionData Augmentation	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