Anomaly Detection

1730 papers with code • 76 benchmarks • 120 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	GLASS	See all
VisA	UniNet	See all
MVTec LOCO AD	CSAD	See all
One-class CIFAR-10	CLIP (OE)	See all
CUHK Avenue	MULDE-object-centric-micro	See all
ShanghaiTech	DAC(STG-NF + Jigsaw)	See all
UCR Anomaly Archive	Auto-Encoder with Regression (AER)	See all
Fishyscapes L&F	cDNP+OE	See all
MPDD	GLASS	See all
One-class CIFAR-100	GeneralAD	See all
BTAD	UniNet	See all
UBnormal	STG-NF - Supervised	See all
UCSD Ped2	DMAD	See all
Unlabeled CIFAR-10 vs CIFAR-100	PsudoLabels ViT	See all
Fashion-MNIST	GAN based Anomaly Detection in Imbalance Problems	See all
One-class ImageNet-30	BCE-Clip (OE)	See all
Numenta Anomaly Benchmark	our	See all
Road Anomaly	OodDINO	See all
Anomaly Detection on Unlabeled CIFAR-10 vs LSUN (Fix)	PsudoLabels ViT	See all
Fishyscapes	RPL+CoroCL	See all
AeBAD-S	MSFR	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
Surface Defect Saliency of Magnetic Tile	HETMM	See all
Lost and Found	Mask2Anomaly	See all
MVTEC AD textures	DualModel	See all
PHEVA	MPED-RNN	See all
UCSD Peds2	Background-Agnostic Framework	See all
Corridor	Two-stream	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
Vehicle Claims	Random Forest	See all
MVTec 3D-AD (RGB)	UniNet	See all
PAD Dataset	SplatPose	See all
SMD	USAD	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
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
UCF-Crime	MULDE-frame-centric-micro-one-class-classification	See all
WFDD	GLASS	See all
ShanghaiTech Campus	TSGAD	See all
IITB Corridor	VideoPatchCore	See all
Street Scene	PGM	See all
ITDD	CRAS	See all
Real 3D-AD	Reg 3D-AD	See all

Show all 76 benchmarks

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Libraries

Use these libraries to find Anomaly Detection models and implementations

xuhongzuo/DeepOD

15 papers

527

openvinotoolkit/anomalib

11 papers

4,484

WenjieDu/PyPOTS

10 papers

1,599

yzhao062/pyod

7 papers

9,351

See all 6 libraries.

Datasets

Subtasks

Graph Anomaly Detection

Anomaly Detection In Surveillance Videos

Image Manipulation Detection

Anomaly Classification

Multi-class Anomaly Detection

3D Anomaly Detection

Weakly-supervised Anomaly Detection

Abnormal Event Detection In Video

Self-Supervised 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

Cold-Start Anomaly Detection

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

Auto-Encoding Variational Bayes

microsoft/recommenders • • 20 Dec 2013

First, we show that a reparameterization of the variational lower bound yields a lower bound estimator that can be straightforwardly optimized using standard stochastic gradient methods.

144

Paper
Code

EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies

openvinotoolkit/anomalib • • 25 Mar 2023

We train a student network to predict the extracted features of normal, i. e., anomaly-free training images.

Paper
Code

PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

openvinotoolkit/anomalib • • 17 Nov 2020

We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting.

Paper
Code

Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

LeeDoYup/AnoGAN • • 17 Mar 2017

Obtaining models that capture imaging markers relevant for disease progression and treatment monitoring is challenging.

Paper
Code

Towards Total Recall in Industrial Anomaly Detection

amazon-research/patchcore-inspection • • CVPR 2022

Being able to spot defective parts is a critical component in large-scale industrial manufacturing.

Paper
Code

Is Space-Time Attention All You Need for Video Understanding?

facebookresearch/TimeSformer • • 9 Feb 2021

We present a convolution-free approach to video classification built exclusively on self-attention over space and time.

Paper
Code

DeepWalk: Online Learning of Social Representations

PaddlePaddle/PaddleRec • • 26 Mar 2014

We present DeepWalk, a novel approach for learning latent representations of vertices in a network.

Paper
Code

A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

hendrycks/error-detection • • 7 Oct 2016

We consider the two related problems of detecting if an example is misclassified or out-of-distribution.

Paper
Code

MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs

pyaf/DenseNet-MURA-PyTorch • • 11 Dec 2017

To evaluate models robustly and to get an estimate of radiologist performance, we collect additional labels from six board-certified Stanford radiologists on the test set, consisting of 207 musculoskeletal studies.

Paper
Code

Transformers in Time Series: A Survey

qingsongedu/time-series-transformers-review • 15 Feb 2022

From the perspective of network structure, we summarize the adaptations and modifications that have been made to Transformers in order to accommodate the challenges in time series analysis.

Paper
Code

Anomaly Detection

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Libraries

Datasets

Subtasks

Most implemented papers

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Benchmarks

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