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 551–560 of 4856 papers

Title	Date	Tasks	Status	Hype
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection	Nov 1, 2022	Anomaly DetectionDomain Adaptation	CodeCode Available	1
Tree Detection and Diameter Estimation Based on Deep Learning	Oct 31, 2022	Anomaly DetectionDeep Learning	CodeCode Available	1
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detection	Oct 26, 2022	Anomaly DetectionDenoising	CodeCode Available	1
Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings	Oct 25, 2022	Anomaly DetectionContrastive Learning	CodeCode Available	1
Self-supervised Sparse Representation for Video Anomaly Detection	Oct 23, 2022	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection	Oct 19, 2022	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
Anomaly Detection Requires Better Representations	Oct 19, 2022	3D Anomaly Detection and SegmentationAnomaly Detection	CodeCode Available	1
DAGAD: Data Augmentation for Graph Anomaly Detection	Oct 18, 2022	Anomaly DetectionData Augmentation	CodeCode Available	1
Graph Anomaly Detection with Unsupervised GNNs	Oct 18, 2022	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	1
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis	Oct 18, 2022	Anomaly DetectionData Augmentation	CodeCode Available	1

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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