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 3871–3880 of 4856 papers

Title	Date	Tasks	Status
A Survey on Deep Learning Techniques for Video Anomaly Detection	Sep 29, 2020	Anomaly DetectionDeep Learning	—Unverified
A comparison of classical and variational autoencoders for anomaly detection	Sep 29, 2020	Anomaly Detection	—Unverified
Anomaly Detection and Sampling Cost Control via Hierarchical GANs	Sep 28, 2020	Anomaly DetectionTime Series Analysis	—Unverified
STAN: Synthetic Network Traffic Generation with Generative Neural Models	Sep 27, 2020	Anomaly Detection	CodeCode Available
Deep Autoencoding GMM-based Unsupervised Anomaly Detection in Acoustic Signals and its Hyper-parameter Optimization	Sep 25, 2020	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
A Unifying Review of Deep and Shallow Anomaly Detection	Sep 24, 2020	Anomaly DetectionOne-Class Classification	—Unverified
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering	Sep 21, 2020	Anomaly DetectionQuestion Answering	—Unverified
Out-Of-Bag Anomaly Detection	Sep 20, 2020	Anomaly Detection	—Unverified
Unsupervised Anomaly Detection on Temporal Multiway Data	Sep 20, 2020	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
A deep learning-based approach for the automated surface inspection of copper clad laminate images	Sep 19, 2020	Anomaly DetectionDefect Detection	—Unverified

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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	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