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 3861–3870 of 4856 papers

Title	Date	Tasks	Status	Hype
Explainable Deep One-Class Classification	Jul 3, 2020	Anomaly DetectionClassification	CodeCode Available	1
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-Decoding	Jul 3, 2020	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	0
Deep Learning Models for Visual Inspection on Automotive Assembling Line	Jul 2, 2020	Anomaly DetectionDeep Learning	—Unverified	0
Laplacian Change Point Detection for Dynamic Graphs	Jul 2, 2020	Anomaly DetectionChange Point Detection	CodeCode Available	1
Subject-Aware Contrastive Learning for Biosignals	Jun 30, 2020	Anomaly DetectionContrastive Learning	CodeCode Available	1
Feature Extraction for Novelty Detection in Network Traffic	Jun 30, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Random Partitioning Forest for Point-Wise and Collective Anomaly Detection -- Application to Intrusion Detection	Jun 29, 2020	Anomaly DetectionIntrusion Detection	CodeCode Available	1
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation	Jun 29, 2020	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition	Jun 29, 2020	Anomaly DetectionClustering	—Unverified	0
Generative Damage Learning for Concrete Aging Detection using Auto-flight Images	Jun 27, 2020	Anomaly DetectionImage-to-Image Translation	—Unverified	0

Show:10 25 50

← PrevPage 387 of 486Next →

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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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