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 821–830 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure	Jul 12, 2020	Anomaly DetectionAttribute	CodeCode Available	1	5
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection	May 22, 2021	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1	5
AnoDFDNet: A Deep Feature Difference Network for Anomaly Detection	Mar 29, 2022	Anomaly Detectionobject-detection	CodeCode Available	1	5
Federated Foundation Models on Heterogeneous Time Series	Dec 12, 2024	Anomaly DetectionFederated Learning	CodeCode Available	1	5
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection	May 3, 2024	Anomaly DetectionAttribute	CodeCode Available	1	5
A SAM-guided Two-stream Lightweight Model for Anomaly Detection	Feb 29, 2024	Anomaly DetectionDecoder	CodeCode Available	1	5
InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV Images	Nov 2, 2023	Anomaly DetectionImage Classification	CodeCode Available	1	5
FedTADBench: Federated Time-Series Anomaly Detection Benchmark	Dec 19, 2022	Anomaly DetectionFederated Learning	CodeCode Available	1	5
Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy	Jun 26, 2020	Anomaly Detection	CodeCode Available	1	5
Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly Detection	Jan 24, 2024	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