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)。
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Updated
Jun 12, 2024
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)。
Eddy current tomography for metal defect imaging
本项目实现了一种基于 VAE-CycleGAN 的图像重建无监督缺陷检测算法。该算法结合了变分自编码器 (VAE) 和 CycleGAN 的优势,无需标注数据即可检测图像中的缺陷/异常。This project implements an unsupervised defect detection algorithm for image reconstruction based on VAE-CycleGAN. This algorithm combines the advantages of variational autoencoders (VAE) and CycleGAN to detect defects in images without any supervision.
Computer Vision: Defect Detection | Summer 2022
Classification of automotive parts as defective and non-defective with transfer learning.
Official PyTorch implementation of the paper "Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images", IEEE TIM2024. CSBSR is an advanced version of our previous work CSSR [MVA'21].
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.
[ICSE 2024 Industry Challenge Track] Official implementation of "ReposVul: A Repository-Level High-Quality Vulnerability Dataset".
Concealed Object Detection (SINet-V2, IEEE TPAMI 2022). Code is implemented by PyTorch/Jittor frameworks.
The target dataset is aligned to the reference dataset using a time series alignment method called "Dynamic Time Warping" (DTW).The One-Class classifier model was effectively utilized in accurately classifying defect-free and defective fabrics.
Camouflaged Object Detection, CVPR 2020 (Oral)
This repo contains implementation of uncertainty estimation, rectification, and minimization for guiding the pseudo-label learning in semi-supervised defect segmentation setting.
Multi-label defect detection for Solar Cells from Electroluminescence images of the modules, using Deep Learning
[Computers and Electronics in Agriculture 2024] FastSegFormer: A knowledge distillation-based method for real-time semantic segmentation of surface defects in navel oranges.
This repository contains implementation of ResNet for surface defect classification, with detailed analysis of results.
Magnetic tile surface defect detection, NHA12D road/pavement crack detection
IRT defect depth detection with Yolov5
Collection of methods for the analysis of solar modules
Inspection of Power Line Assets Dataset (InsPLAD)
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