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 391–400 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Anomaly localization by modeling perceptual features	Aug 12, 2020	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality Detection	Dec 19, 2024	Anomaly DetectionEEG	CodeCode Available	1	5
Broiler-Net: A Deep Convolutional Framework for Broiler Behavior Analysis in Poultry Houses	Jan 22, 2024	Anomaly Detection	CodeCode Available	1	5
FewSOME: One-Class Few Shot Anomaly Detection with Siamese Networks	Jan 17, 2023	Anomaly Detection	CodeCode Available	1	5
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection	Oct 19, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1	5
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1	5
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset	Sep 30, 2024	Anomaly Detection	CodeCode Available	1	5
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting	Dec 22, 2023	Anomaly DetectionTime Series	CodeCode Available	1	5
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models	May 13, 2024	Anomaly DetectionEdge Detection	CodeCode Available	1	5
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly Detection	Apr 16, 2025	Anomaly DetectionLarge Language Model	CodeCode Available	1	5

Show:10 25 50

← PrevPage 40 of 486Next →

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