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 641–650 of 4856 papers

Title	Date	Tasks	Status	Hype
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies	Mar 11, 2022	Anomaly DetectionInformation Retrieval	CodeCode Available	1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection	Mar 10, 2022	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
Diffusion Models for Medical Anomaly Detection	Mar 8, 2022	Anomaly DetectionDenoising	CodeCode Available	1
Learning Neural Set Functions Under the Optimal Subset Oracle	Mar 3, 2022	Anomaly DetectionDrug Discovery	CodeCode Available	1
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels	Mar 3, 2022	Anomaly DetectionCardiac Segmentation	CodeCode Available	1
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks	Mar 2, 2022	Anomaly DetectionAutonomous Driving	CodeCode Available	1
Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection	Mar 1, 2022	Anomaly Detectionchannel selection	CodeCode Available	1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form Assessment	Feb 28, 2022	3D Action RecognitionAction Analysis	CodeCode Available	1
ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 code	Feb 21, 2022	Anomaly Detection	CodeCode Available	1
Latent Outlier Exposure for Anomaly Detection with Contaminated Data	Feb 16, 2022	Anomaly DetectionVideo Anomaly Detection	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