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 231–240 of 4856 papers

Title	Date	Tasks	Status	Hype
Deep Anomaly Detection Using Geometric Transformations	May 28, 2018	Anomaly Detection	CodeCode Available	1
Deep Anomaly Detection with Outlier Exposure	Dec 11, 2018	Anomaly DetectionOut-of-Distribution Detection	CodeCode Available	1
Deep Contrastive One-Class Time Series Anomaly Detection	Jul 4, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	1
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds	Jun 18, 2020	Anomaly DetectionTask 2	CodeCode Available	1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection	Mar 28, 2022	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection	Feb 15, 2022	Anomaly DetectionMissing Values	CodeCode Available	1
CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting	Sep 27, 2024	Anomaly DetectionTime Series	CodeCode Available	1
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation	Dec 19, 2021	Anomaly DetectionKnowledge Distillation	CodeCode Available	1
Challenges in Visual Anomaly Detection for Mobile Robots	Sep 22, 2022	Anomaly Detection	CodeCode Available	1
CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection	Dec 9, 2022	Anomaly DetectionMultiple Instance Learning	CodeCode Available	1

Show:10 25 50

← PrevPage 24 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	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