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Please refer to this page.
Considering the increasing number of papers in this field, we roughly summarize some articles and put them into the following categories (they are still listed in this document):
Note that all unpublished arXiv papers are not included in the leaderboard of performance.
- Segmentation-Based Deep-Learning Approach for Surface-Defect (SCI)[paper][code]
- Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows [paper]
- Deep Learning for Anomaly Detection: A Survey [paper][code]
- Few-Shot Defect Segmentation Leveraging Abundant Normal Training Samples Through Normal Background Regularization and Crop-and-Paste Operation [paper]
- Anomaly Detection on X-Rays Using Self-Supervised Aggregation Learning [paper]
- A Versatile Crack Inspection Portable System based on Classifier Ensemble and Controlled Illumination [paper]
- Crack Detection as a Weakly-Supervised Problem: Towards Achieving Less Annotation-Intensive Crack Detectors [papercode]]
- CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation(2021)[paper] [code] -Learning to Detect Multiple Photographic Defects
Earlier ArXiv Papers
- Data Augmentation in Defect Detection of Sanitary Ceramics in Small and Non-i.i.d Datasets(IEEE-TNNLS)[paper]
- BAF-Detector: An Efficient CNN-Based Detector for Photovoltaic Cell Defect Detection(IEEE-TIE)[paper]
- Unsupervised Saliency Detection of Rail Surface Defects Using Stereoscopic Images (IEEE-TII)[paper]
- [FFCNN] A Deep Neural Network for Surface Defect Detection of Magnetic Tile (IEEE-TII)[paper]
- CutPaste: Self-Supervised Learning for Anomaly Detection and Localization (CVPR-2021)[paper][code]
- (RCAG-Net)RCAG-Net Residual Channelwise Attention Gate(IEEE-TIM-2021) [paper][code]
- (SDDNet) A Fast and Accurate Network(IEEE-TIM-2021) [paper]
- A Hybrid Fuzzy Convolutional Neural Network(IEEE-TPDS-2021)[paper]
- A Lightweight Spatial and Temporal Multi-Feature(IEEE-TIP-2021)[paper]
- A Pixel-Level Segmentation Convolutional Neural(IEEE-TIM-2021)[paper]
- A Real-Time Defect Detection Method(IEEE-TII-2021)[paper]
- An Accurate and Real-Time Surface Defects Detection(IEEE-TIM-2021)[paper]
- An End-to-End Defect Detection Method for Mobile(IEEE-TIM-2021)[paper]
- Automatic zipper tape defect detection using two-stage multi-scale-Neurocomputing(sciencedirect)[paper]
- Sparse Low-Rank Tensor Decomposition (IEEE-TII-2021)[paper]
- Mixed supervision for surface-defect detection: from weakly to fully supervised learning(COMPUT-IND)[paper][code]
- A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection(CVPR)[paper][code]
- Deep Learning Based Steel Pipe Weld Defect Detection(CVPR)[paper][code]
- DRÆM – A discriminatively trained reconstruction embedding for surface anomaly detection(ICCV-2021)[paper][code]
- Auto-Annotated Deep Segmentation for Surface Defect Detection(IEEE-TIM)[paper]
- Dense Attention-Guided Cascaded Network for Salient Object Detection of Strip Steel Surface Defects(IEEE-TIM)[paper][code]
- EDRNet: Encoder–Decoder Residual Network for Salient Object Detection of Strip Steel Surface Defects(IEEE-TIM)[paper][code]
- Fabric Defect Segmentation Method Based on Deep Learning(IEEE-TIM)[paper]
- Robust Similarity Measurement Based on a Novel Time Filter for SSVEPs Detection(IEEE-TNNLS)[paper]
- Automated Defect Detection From Ultrasonic Images Using Deep Learning(IEEE-TUFFC)[paper]
- Inspection of Imprint Defects in Stamped Metal Surfaces using Deep Learning and Tracking (IEEE-TIE)[paper]
- [RPAN] Deep Learning-based Solar-Cell Manufacturing Defect Detection with Complementary Attention Network (Network-TII)[paper]
- [PGA-Net] PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection (IEEE-TII)[paper]
- Deep-Learning-Based Small Surface Defect Detection via an Exaggerated Local Variation-Based Generative Adversarial Network (IEEE-TII)[paper]
- [NDT] Multiview Learning for Subsurface Defect Detection in Composite Products: A Challenge on Thermographic Data Analysis (IEEE-TII)[paper]
- [ERSCD] A Surface Defect Detection Framework for Glass Bottle Bottom Using Visual Attention Model and Wavelet Transform (IEEE-TII)[paper]
- [WGANs] A learning-based approach for surface defect detection using small image datasets [paper]
- [Faster VG-RCNN] Detecting textile micro-defects: A novel and efficient method based on visual gain mechanism [paper]
- An Efficient Convolutional Neural Network Model Based on Object-Level Attention Mechanism for Casting Defect Detection on Radiography Images (IEEE-TIE)[paper]
- [GAN] Multistage GAN for Fabric Defect Detection (IEEE-TIP)[paper]
- A simulation-based few samples learning method for surface defect segmentation [paper]
- A Generic Semi-Supervised Deep Learning-Based Approach for Automated Surface Inspection (IEEE-Access)[paper]
- A novel algorithm for defect extraction and classification of mobile phone screen based on machine vision (Inf Fusion)[paper]
- A Steel Surface Defect Recognition Algorithm Based on Improved Deep Learning Network Model Using Feature Visualization and Quality Evaluation (IEEE-Access)[paper]
- Automated defect inspection system for metal surfaces based on deep learning and data augmentation (Inf Fusion)[paper]
- [CADN] CADN: A weakly supervised learning-based category-aware object detection network for surface defect detection (PR)[paper]
- [PDDNet] Defect Detection of Pantograph Slide Based on Deep Learning and Image Processing Technology (IEEE-TITS)[paper]
- Detection of PCB Surface Defects With Improved Faster-RCNN and Feature Pyramid Network (IEEE Access)[paper]
- Detection of PV Solar Panel Surface Defects using Transfer Learning of the Deep Convolutional Neural Networks (ASET)[paper]
- Electronic Product Surface Defect Detection Based on a MSSD Network (IEEE-ITNEC)[paper]
- Research on Defect Detection Method for Steel Metal Surface based on Deep Learning (IEEE-ITOEC)[paper]
- Surface damage detection for steel wire ropes using deep learning and computer vision techniques [paper]
- A Data-Flow Oriented Deep Ensemble Learning Method for Real-Time Surface Defect Inspection (IEEE-TIM)[paper]
- A Deep Learning-Based Surface Defect Inspection System Using Multiscale and Channel-Compressed Features (IEEE-TIM)[paper]
- EDRNet: Encoder–Decoder Residual Network for Salient Object Detection of Strip Steel Surface Defects (IEEE-TIM)[paper]
- A Two-Stage Multiscale Residual Attention Network for Light Guide Plate Defect Detection (IEEE)[paper]
- RetinaNet With Difference Channel Attention and Adaptively Spatial Feature Fusion for Steel Surface Defect Detection (IEEE-TIM)[paper]
- A Pixel-Level Segmentation Convolutional Neural Network Based on Deep Feature Fusion for Surface Defect Detection (IEEE-TIM)[paper]
- A Lightweight Spatial and Temporal Multi-Feature Fusion Network for Defect Detection (IEEE-TIP)[paper]
- DefGAN: Defect Detection GANs With Latent Space Pitting for High-Speed Railway Insulator (IEEE-TIM)[paper]
- Semi-supervised Anomaly Detection using AutoEncoders (CVPR-2020) [paper][code]
- A Compact Convolutional Neural Network for Surface Defect Inspection (MDPI)[paper][code]
- A Defect-Detection Method of Split Pins in the Catenary Fastening Devices of High-Speed Railway Based on Deep Learning(IEEE-TIM)[paper]
- A Novel Pixel-Wise Defect Inspection Method Based on Stable Background Reconstruction(IEEE-TIM)[paper]
- MCnet: Multiple Context Information Segmentation Network of No-Service Rail Surface Defects(IEEE-TIM)[paper][code]
- Polycrystalline silicon wafer defect segmentation based on deep convolutional neural networks(sciencedirect)[paper]
- An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features(IEEE-TIM)[paper]
- Detecting textile micro-defects: A novel and efficient method based on visual gain mechanism(sciencedirect)[paper]
- [ESP] Surface Defect Detection via Entity Sparsity Pursuit With Intrinsic Priors (IEEE-TII)[paper]
- [CODEBRIM] Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset(CVPR-2019)[paper][code]
- [SDD-CNN] applsci-SDD-CNN Small Data-Driven Convolution Neural Networks for Subtle Roller Defect Inspection(Applied Sciences) [paper]
- An End-to-End Steel Surface Defect Detection Approach via Fusing Multiple Hierarchical Features (IEEE-TIM)[paper]
- A New Self-Reference Image Decomposition Algorithm for Strip Steel Surface Defect Detection(IEEE-TIM) [paper]
- Automatic fabric defect detection with a wide-and-compact network [paper]
- AnomalyNet: An Anomaly Detection Network for Video Surveillance (IEEE-TIFS)[paper]
- Anomaly Detection in Images (CVPR-2019)[paper]
- A Smart Monitoring System for Automatic(TIE-2019)[paper]
- Multiscale Feature-Clustering-Based Fully Convolutional Autoencoder for Fast Accurate Visual Inspection of Texture Surface Defects(IEEE-TASE)[paper]
- PGA-Net: Pyramid Feature Fusion and Global Context Attention Network for Automated Surface Defect Detection(IEEE-TII)[paper][code]
- Segmentation-Based Deep-Learning Approach for Surface-Defect Detection()[paper][code]
- Surface Defects Detection Based on Adaptive Multiscale Image Collection and Convolutional Neural Networks(IEEE-TIM)[paper]
- [CTFM] A Coarse-to-Fine Model for Rail Surface Defect Detection (IEEE-TIM)[paper]
- [MIL] Real-world Anomaly Detection in Surveillance Videos (CVPR-2018)[paper][code]
- Surface Defect Saliency of Magnetic Tile(IEEE-CASE)[paper][code]
- A Compact Convolutional Neural Network for Textured Surface Anomaly Detection(WACV)[paper][code]
- Surface Defect Saliency of Magnetic Tile(IEEE-CASE)[paper]
-Dimensionality Reduction-Based Diagnosis of (IEEE-SMC-2017)[paper]
-Sequential Score Adaptation with Extreme Value Theory for Robust Railway Track Inspection(CVRSUAD 2015)[paper][code]
The section is being continually updated. Note that some values have superscript, which indicates their source.