Official PyTorch code for WACV 2022 paper "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"

unoffical and work in progress PyTorch implementation of CutPaste

Repository for the Explainable Deep One-Class Classification paper

Vanilla torch and timm industrial knn-based anomaly detection for images.

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Official Implementation for the "Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection" paper.

Code underlying our publication "Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection" at ICPR2020

This is an unofficial implementation of Reconstruction by inpainting for visual anomaly detection (RIAD).

Anomaly detection method that incorporates multi-scale features to sparse coding

Code to reproduce 'Combining GANs and AutoEncoders for efficient anomaly detection'

🐬 Re-implementation of PaDiM and code for the article "Weakly Supervised Detection of Marine Animals in High Resolution Aerial Images"

Semi-Orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation

🪥 Unofficial re-implementation of Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation

This is an unofficial implementation of ' Anomaly localization by modeling perceptual features'

PatchCore method for Industrial Anomaly Detection + CLIP

EfficientNetV2 based PaDiM

The code for "Self-supervised Context Learning for Visual Inspection of Industrial Defects"

The solutions for the dacon competition (1st place).

Repository for the Exposing Outlier Exposure paper

Thesis project about Visual Anomaly Detection based on Self Supervised Learning. The model identifies anomalies from information acquired during training, where normality and anomaly patterns are built using syntetic data