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 4191–4200 of 4856 papers

Title	Date	Tasks	Status
Invertible Neural Networks for Graph Prediction	Jun 2, 2022	Anomaly DetectionGraph Neural Network	CodeCode Available
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities	Oct 5, 2018	Anomaly DetectionClustering	CodeCode Available
Attribute Restoration Framework for Anomaly Detection	Nov 25, 2019	Anomaly DetectionAttribute	CodeCode Available
DINAMO: Dynamic and INterpretable Anomaly MOnitoring for Large-Scale Particle Physics Experiments	Jan 31, 2025	Anomaly Detection	CodeCode Available
ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features	Jun 1, 2019	Anomaly DetectionFake Image Detection	CodeCode Available
TransformerG2G: Adaptive time-stepping for learning temporal graph embeddings using transformers	Jul 5, 2023	Anomaly DetectionComputational Efficiency	CodeCode Available
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly Detection	May 10, 2024	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available
Mapper Comparison with Wasserstein Metrics	Dec 15, 2018	Anomaly DetectionOpen-Ended Question Answering	CodeCode Available
Margin-Aware Intra-Class Novelty Identification for Medical Images	Jul 31, 2021	Anomaly DetectionMedical Image Analysis	CodeCode Available
Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks	Aug 14, 2023	Anomaly Detection	CodeCode Available

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