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 126–150 of 4856 papers

Title	Date	Tasks	Status	Hype
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection	Jun 17, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	2
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects	Jun 16, 2023	Anomaly DetectionSelf-Supervised Learning	CodeCode Available	2
2nd Place Winning Solution for the CVPR2023 Visual Anomaly and Novelty Detection Challenge: Multimodal Prompting for Data-centric Anomaly Detection	Jun 15, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	2
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series	May 30, 2023	Anomaly DetectionClassification	CodeCode Available	2
APRIL-GAN: A Zero-/Few-Shot Anomaly Classification and Segmentation Method for CVPR 2023 VAND Workshop Challenge Tracks 1&2: 1st Place on Zero-shot AD and 4th Place on Few-shot AD	May 27, 2023	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
Anomaly Detection with Conditioned Denoising Diffusion Models	May 25, 2023	Anomaly DetectionDenoising	CodeCode Available	2
Segment Any Anomaly without Training via Hybrid Prompt Regularization	May 18, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	2
SimpleNet: A Simple Network for Image Anomaly Detection and Localization	Mar 27, 2023	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation	Mar 26, 2023	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies	Mar 25, 2023	Anomaly DetectionComputational Efficiency	CodeCode Available	2
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection	Mar 15, 2023	Anomaly DetectionDenoising	CodeCode Available	2
Multimodal Industrial Anomaly Detection via Hybrid Fusion	Mar 1, 2023	3D Anomaly DetectionAnomaly Detection	CodeCode Available	2
One Fits All:Power General Time Series Analysis by Pretrained LM	Feb 23, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	2
LogAI: A Library for Log Analytics and Intelligence	Jan 31, 2023	Anomaly DetectionLog Parsing	CodeCode Available	2
Streaming Anomaly Detection	Jan 30, 2023	Anomaly DetectionDenoising	CodeCode Available	2
IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspective	Sep 16, 2022	Anomaly DetectionAutoML	CodeCode Available	2
SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation	Jul 28, 2022	Anomaly DetectionAnomaly Segmentation	CodeCode Available	2
Registration based Few-Shot Anomaly Detection	Jul 15, 2022	Anomaly Detection	CodeCode Available	2
AnoDDPM: Anomaly Detection With Denoising Diffusion Probabilistic Models Using Simplex Noise	Jun 30, 2022	Anomaly DetectionDenoising	CodeCode Available	2
A Unified Model for Multi-class Anomaly Detection	Jun 8, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	2
Rethinking Graph Neural Networks for Anomaly Detection	May 31, 2022	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	2
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities	May 2, 2022	Anomaly DetectionDefect Detection	CodeCode Available	2
Log-based Anomaly Detection with Deep Learning: How Far Are We?	Feb 9, 2022	Anomaly DetectionDeep Learning	CodeCode Available	2
Anomaly Detection via Reverse Distillation from One-Class Embedding	Jan 26, 2022	Anomaly Classification	CodeCode Available	2
TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data	Jan 18, 2022	Anomaly DetectionMeta-Learning	CodeCode Available	2

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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	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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