Image Models

Image Models#

CFA

Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization

CFA
C-Flow

Real-Time Unsupervised Anomaly Detection via Conditional Normalizing Flows

C-Flow
CS-Flow

Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection

CS-Flow
DFKDE

Deep Feature Kernel Density Estimation

DFKDE
DFM

Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection

DFM
DRAEM

DRÆM – A discriminatively trained reconstruction embedding for surface anomaly detection

DRAEM
DSR

DSR – A Dual Subspace Re-Projection Network for Surface Anomaly Detection

DSR
Efficient AD

EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies

Efficient AD
FastFlow

FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows

FastFlow
FRE

FRE: A Fast Method For Anomaly Detection And Segmentation

FRE
GANomaly

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

GANomaly
PaDiM

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

Padim
Patchcore

Towards Total Recall in Industrial Anomaly Detection

PatchCore
Reverse Distillation

Anomaly Detection via Reverse Distillation from One-Class Embedding.

Reverse Distillation
STFPM

Student-Teacher Feature Pyramid Matching for Unsupervised Anomaly Detection

STFPM
SuperSimpleNet

SuperSimpleNet: Unifying Unsupervised and Supervised Learning for Fast and Reliable Surface Defect Detection

SuperSimpleNet
U-Flow

U-Flow: A U-shaped Normalizing Flow for Anomaly Detection with Unsupervised Threshold

U-Flow
VLM-AD

VLM-AD: Vision-Language Model for Anomaly Detection

VLM-AD
WinCLIP

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

WinCLIP