Anomaly Detection

1259 papers with code • 66 benchmarks • 95 datasets

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

Benchmarks

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These leaderboards are used to track progress in Anomaly Detection

Dataset	Best Model	Compare
MVTec AD	ReConPatch Ensemble (+RefineNet)	See all
MVTec LOCO AD	PSAD	See all
One-class CIFAR-10	CLIP (OE)	See all
CUHK Avenue	AMSRC	See all
VisA	DiffusionAD	See all
ShanghaiTech	DAC (STG-NF + Jigsaw)	See all
Fishyscapes L&F	cDNP+OE	See all
One-class CIFAR-100	Transformaly	See all
Unlabeled CIFAR-10 vs CIFAR-100	PsudoLabels ViT	See all
Fashion-MNIST	GAN based Anomaly Detection in Imbalance Problems	See all
UBnormal	STG-NF - Supervised	See all
One-class ImageNet-30	BCE-Clip (OE)	See all
Numenta Anomaly Benchmark	our	See all
BTAD	CPR	See all
UCSD Ped2	DMAD	See all
Anomaly Detection on Unlabeled CIFAR-10 vs LSUN (Fix)	PsudoLabels ViT	See all
Fishyscapes	RPL+CoroCL	See all
Road Anomaly	RbA	See all
AeBAD-S	MMR	See all
AeBAD-V	MMR	See all
MNIST	GAN-based Anomaly Detection in Imbalance Problems	See all
Hyper-Kvasir Dataset	CCD	See all
Leave-One-Class-Out CIFAR-10	BCE-CLIP	See all
Leave-One-Class-Out ImageNet-30	BCE-CLIP (OE)	See all
Anomaly Detection on Unlabeled ImageNet-30 vs CUB-200	PsudoLabels CLIP ViT	See all
Anomaly Detection on Anomaly Detection on Unlabeled ImageNet-30 vs Flowers-102	PsudoLabels CLIP ViT	See all
LAG	CCD	See all
InsPLAD	AttentDifferNet (SENet-AlexNet)	See all
Cats-and-Dogs	PANDA	See all
DIOR	PANDA-OE	See all
Lost and Found	Mask2Anomaly	See all
MVTEC AD textures	DualModel	See all
Surface Defect Saliency of Magnetic Tile	CS-Flow (unsupervised)	See all
UCSD Peds2	Background-Agnostic Framework	See all
ODDS	kNN	See all
UEA time-series datasets	SINBAD	See all
MVTec AD Textures Domain Generalization	FABLE	See all
voraus-AD	MVT-Flow	See all
Thyroid	DevNet	See all
MVTEC 3D-AD	CDO	See all
Corridor	Two-stream	See all
Vehicle Claims	Random Forest	See all
PAD Dataset	SplatPose	See all
Census	DevNet	See all
MNIST-test	OGNET	See all
CIFAR-10	RCALAD	See all
AG News	DATE	See all
ASSIRA Cat Vs Dog	Shell-based Anomaly (supervisered)	See all
STL-10	Shell-based Anomaly (supervised)	See all
Forest CoverType	DIF	See all
Kaggle-Credit Card Fraud Dataset	DIF	See all
NB15-Analysis	DIF	See all
NB15-Backdoor	DIF	See all
NB15-DoS	DIF	See all
BottleCap	DFC	See all
kdd 99	PCA via oversampling	See all
MVTec 3D-AD (RGB)	CPR	See all
KDD Cup 1999	RCALAD	See all
MIT-BIH Arrhythmia Database	RCALAD	See all
Musk v1	RCALAD	See all
SVHN	RCALAD	See all
KSDD2	SAA+	See all
TII-SSRC-23	Deep SVDD	See all
ADNI	Brainomaly	See all
COCO-OOC	GCRN	See all
Real 3D-AD	Reg 3D-AD	See all

Show all 66 benchmarks

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Libraries

Use these libraries to find Anomaly Detection models and implementations

xuhongzuo/DeepOD

15 papers

304

openvinotoolkit/anomalib

8 papers

3,256

WenjieDu/PyPOTS

6 papers

738

sintel-dev/orion

5 papers

977

See all 7 libraries.

Datasets

Subtasks

Anomaly Detection In Surveillance Videos

Graph Anomaly Detection

Image Manipulation Detection

Weakly-supervised Anomaly Detection

Abnormal Event Detection In Video

Self-Supervised Anomaly Detection

3D Anomaly Detection

3D Anomaly Detection and Segmentation

RGB+3D Anomaly Detection and Segmentation

Contextual Anomaly Detection

Depth Anomaly Detection and Segmentation

Group Anomaly Detection

RGB+Depth Anomaly Detection and Segmentation

Damaged Tissue Detection

Unsupervised Anomaly Detection In Sound

3D Anomaly Segmentation

Depth Anomaly Segmentation

3D + RGB Anomaly Segmentation

Depth + RGB Anomaly Segmentation

Depth + RGB Anomaly Detection

3D + RGB Anomaly Detection

DepthAnomaly Detection

Most implemented papers

Most implemented Social Latest No code

Anomaly Detection via Reverse Distillation from One-Class Embedding

hq-deng/RD4AD • • CVPR 2022

Knowledge distillation (KD) achieves promising results on the challenging problem of unsupervised anomaly detection (AD). The representation discrepancy of anomalies in the teacher-student (T-S) model provides essential evidence for AD.

Paper
Code

WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation

caoyunkang/WinClip • • CVPR 2023

Visual anomaly classification and segmentation are vital for automating industrial quality inspection.

Paper
Code

PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series

WenjieDu/PyPOTS • • 30 May 2023

PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series, i. e. incomplete time series with missing values, A. K. A.

Paper
Code

Robust random cut forest based anomaly detection on streams

kLabUM/rrcf • 19 Jun 2016

In this paper we focus on the anomaly detection problem for dynamic data streams through the lens of random cut forests.

Paper
Code

Real-Time Anomaly Detection for Streaming Analytics

numenta/NAB • 8 Jul 2016

Much of the worlds data is streaming, time-series data, where anomalies give significant information in critical situations.

Paper
Code

Automatic Anomaly Detection in the Cloud Via Statistical Learning

nachonavarro/seasonal-esd-anomaly-detection • 24 Apr 2017

Although there exists a large body of prior research in anomaly detection, existing techniques are not applicable in the context of social network data, owing to the inherent seasonal and trend components in the time series data.

Paper
Code