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 421–430 of 4856 papers

Title	Date	Tasks	Status	Hype
Unmasking Anomalies in Road-Scene Segmentation	Jul 25, 2023	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision	Jul 25, 2023	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	1
Towards Video Anomaly Retrieval from Video Anomaly Detection: New Benchmarks and Model	Jul 24, 2023	Anomaly DetectionRetrieval	CodeCode Available	1
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection	Jul 24, 2023	Anomaly DetectionDefect Detection	CodeCode Available	1
Optimizing PatchCore for Few/many-shot Anomaly Detection	Jul 20, 2023	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly Detection	Jul 19, 2023	Anomaly DetectionDenoising	CodeCode Available	1
Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection	Jul 17, 2023	Anomaly DetectionGraph Learning	CodeCode Available	1
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection	Jul 14, 2023	2D Human Pose EstimationAnomaly Detection	CodeCode Available	1
Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images	Jul 14, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation	Jul 11, 2023	Anomaly ClassificationAnomaly 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