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 371–380 of 4856 papers

Title	Date	Tasks	Status	Hype
Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection	Oct 22, 2023	Anomaly DetectionMulti-class Anomaly Detection	CodeCode Available	1
FLTracer: Accurate Poisoning Attack Provenance in Federated Learning	Oct 20, 2023	Anomaly DetectionFederated Learning	CodeCode Available	1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection	Oct 19, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection	Oct 18, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis	Oct 18, 2023	Anomaly DetectionImputation	CodeCode Available	1
TRANSOM: An Efficient Fault-Tolerant System for Training LLMs	Oct 16, 2023	Anomaly DetectionGPU	CodeCode Available	1
Does Graph Distillation See Like Vision Dataset Counterpart?	Oct 13, 2023	Anomaly DetectionDataset Distillation	CodeCode Available	1
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining	Oct 11, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
Learning a Cross-modality Anomaly Detector for Remote Sensing Imagery	Oct 11, 2023	Anomaly DetectionDiversity	CodeCode Available	1
A Discrepancy Aware Framework for Robust Anomaly Detection	Oct 11, 2023	Anomaly DetectionDecoder	CodeCode Available	1

Show:10 25 50

← PrevPage 38 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