Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。

Camouflaged Object Detection, CVPR 2020 (Oral)

Official PyTorch implementation for "Mixed supervision for surface-defect detection: from weakly to fully supervised learning"

Concealed Object Detection (SINet-V2, IEEE TPAMI 2022). Code is implemented by PyTorch/Jittor frameworks.

Visual Defect Detection on Boiler Water Wall Tube Using Small Dataset

👷胶囊表面缺陷检测withTensorflow，主要检测了凹陷和缺失部分，涉及到GPU加速

基于RetinaFace的目标检测方法，适用于人脸、缺陷、小目标、行人等

IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练

This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.

Multi-label defect detection for Solar Cells from Electroluminescence images of the modules, using Deep Learning

Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"

Inspection of Power Line Assets Dataset (InsPLAD)

Detect Defects in Products from their Images using Amazon SageMaker

This github repository contains the sample code and exercises of btp-ai-sustainability-bootcamp, which showcases how to build Intelligence and Sustainability into Your Solutions on SAP Business Technology Platform with SAP AI Core and SAP Analytics Cloud for Planning.

Textile defect detection using OpenCVSharp

This project aims to automatically detect surface defects in Hot-Rolled Steel Strips such as rolled-in scale, patches, crazing, pitted surface, inclusion and scratches. A CNN is trained on the NEU Metal Surface Defects Database which contains 1800 grayscale images with 300 samples of each of the six different kinds of surface defects.

TFT-LCD defects detecter based on the improved saliency model

MATLAB code and data for "Automatic image thresholding using Otsu’s method and entropy weighting scheme for surface defect detection"

Visual inspection of bridges is customarily used to identify and evaluate faults. However, current procedures followed by human inspectors demand long inspection times to examine large and difficult to access bridges. To address these limitations, we investigate a computer vision‐based approach that employs SIFT keypoint matching on collected im…

Imaging system for analyzing defects of semiconductor wafers and chips