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 301–310 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Deep Contrastive One-Class Time Series Anomaly Detection	Jul 4, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	1	5
Anomaly Detection with Score Distribution Discrimination	Jun 26, 2023	Anomaly Detection	CodeCode Available	1	5
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition Sounds	Jun 18, 2020	Anomaly DetectionTask 2	CodeCode Available	1	5
Anomaly localization by modeling perceptual features	Aug 12, 2020	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection	Feb 3, 2023	Anomaly DetectionDomain Adaptation	CodeCode Available	1	5
Deep Dual Support Vector Data Description for Anomaly Detection on Attributed Networks	Sep 1, 2021	Anomaly DetectionAttribute	CodeCode Available	1	5
Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection	Feb 15, 2022	Anomaly DetectionMissing Values	CodeCode Available	1	5
Deep Learning in Latent Space for Video Prediction and Compression	Jun 19, 2021	Anomaly DetectionDeep Learning	CodeCode Available	1	5
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection	Nov 21, 2022	Anomaly DetectionDecoder	CodeCode Available	1	5
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection	Oct 26, 2023	Anomaly DetectionOne-Class Classification	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