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 531–540 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
FAPM: Fast Adaptive Patch Memory for Real-time Industrial Anomaly Detection	Nov 14, 2022	Anomaly Detection	CodeCode Available	1	5
Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning	May 25, 2023	Anomaly Detection	CodeCode Available	1	5
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR Data	Mar 14, 2025	Anomaly DetectionDecoder	CodeCode Available	1	5
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection	Sep 13, 2023	Anomaly DetectionDefect Detection	CodeCode Available	1	5
AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving	May 13, 2024	Anomaly DetectionAutonomous Driving	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
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model	Aug 31, 2024	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1	5
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty Detection	May 28, 2022	Anomaly DetectionNovelty Detection	CodeCode Available	1	5
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach	Nov 26, 2020	Anomaly Detection	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