A Survey on Industrial Anomaly Detection – from Methodology to Implementation
35
2 commits
updated Mar 4, 2025
A Diffusion-Based Framework for Multi-Class Anomaly Detection [AAAI 2024] [code]
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model [AAAI 2024] [code]
AnomalyGPT: detecting industrial anomalies using large vision-language models [AAAI 2024] [code]
Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt [AAAI 2024] [code]
Hyperbolic Anomaly Detection [CVPR 2024]
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection [CVPR 2024] [code]
Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble [CVPR 2024 Visual Anomaly Detection Workshop] [homepage]
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping [CVPR 2024] [code]
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection [CVPR 2024] [data]
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection [NeurIPS 2024] [code]
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection [NeurIPS 2024] [code]
Generalad: Anomaly detection across domains by attending to distorted features [ECCV 2024] [code]
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization [ECCV 2024] [code]
Continuous Memory Representation for Anomaly Detection [ECCV 2024] [code]
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection [ECCV 2024] [code]
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection [ECCV 2024] [code]
TransFusion – A Transparency-Based Diffusion Model for Anomaly Detection [ECCV 2024] [code]
R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detection [ECCV 2024] [homepage]
Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection [ECCV 2024] [code]
Dual-modeling decouple distillation for unsupervised anomaly detection [ACM MM 2024]
Filo: Zero-shot anomaly detection by fine-grained description and high-quality localization [ACM MM 2024] [code]
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning [ACM MM 2024] [code]
A Survey on Explainable Anomaly Detection [ACM TKDD 2023]
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect [2024]
Deep industrial image anomaly detection: A survey [Machine Intelligence Research 2024] [code]
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection [2024] [code]
Surface Defect Detection based on Improved YOLOv3-Tiny Algorithm [CCC 2022]
Metal surface defect detection based on improved YOLOv5 [Scientific Reports 2023]
Steel Surface Defect Detection Algorithm Based on YOLOv8 [Electronics 2024]
SSCL: Semi-supervised Contrastive Learning for Industrial Anomaly Detection [PRCV 2023]
GANomaly: Semi-supervised Anomaly Detection via Adversarial Training [ACCV 2018] [code]
Same same but differnet: Semi-supervised defect detection with normalizing flows [WACV 2021] [code]
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities [Engineering Applications of Artificial Intelligence 2023] [unofficial code]
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection [CVPR 2023] [code]
Hyperbolic Anomaly Detection [CVPR 2024]
Self-Supervised Autoencoders for Visual Anomaly Detection [Mathematics 2024]
Multilevel saliency-guided self-supervised learning for image anomaly detection [Signal, Image and Video Processing 2024]
TDAD: Self-supervised industrial anomaly detection with a two-stage diffusion model [Computers in Industry 2025]
SMD Anomaly Detection: A Self-Supervised Texture–Structure Anomaly Detection Framework [IEEE TIM 2022]
Self-supervised anomaly detection based on foreground enhancement and autoencoder reconstruction [Signal, Image and Video Processing 2024]
Self-supervised Visual Anomaly Detection with Image Patch Generation and Comparison Networks [ICIC 2024]
Self-supervised anomaly detection in computer vision and beyond: A survey and outlook [Neural Networks 2024]
Industrial Image Anomaly Detection via Self-Supervised Learning with Feature Enhancement Assistance [Applied Sciences 2024]
Self-Supervised Image Anomaly Detection and Localization with Synthetic Anomalies [IOTSMS 2023]
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation [ACCV 2020] [code]
Cutpaste: Self-supervised learning for anomaly detection and localization [CVPR 2021] [unofficial code]
SPot-the-Difference Self-supervised Pre-training for Anomaly Detection and Segmentation [ECCV 2022] [code]
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection [CVPR 2022] [code]
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection [IEEE TPAMI 2023] [code]
A Discrepancy Aware Framework for Robust Anomaly Detection [IEEE TII 2023] [code]
Revisiting Reverse Distillation for Anomaly Detection [CVPR 2023] [code]
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection [2023]
A Reconstruction-Based Feature Adaptation for Anomaly Detection with Self-Supervised Multi-Scale Aggregation [ICASSP 2024]
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Weakly supervised anomaly detection based on sparsity prior [Electronic Research Archive 2024]
Topology-preserving transfer learning for weakly-supervised anomaly detection and segmentation [PR Letters 2023]
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection [CVPR 2022] [code]
Prototypical Residual Networks for Anomaly Detection and Localization [CVPR 2023] [unofficial code]
IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing [IEEE TCYB 2024] [code]
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection [CVPR 2024] [code]
BiaS: Incorporating Biased Knowledge to Boost Unsupervised Image Anomaly Localization [IEEE TSMC 2024]
Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble [CVPR 2024 Visual Anomaly Detection Workshop] [homepage]
Mixed supervision for surface-defect detection: From weakly to fully supervised learning [Computers in Industry 2021] [code]
Unsupervised industrial anomaly detection with diffusion models [J. Vis. Commun. Image R. 2023] [code]
Glancing at the patch: Anomaly localization with global and local feature comparison [CVPR 2021]
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows [2021] [unofficial code]
Inter-realization channels: Unsupervised anomaly detection beyond one-class classification [ICCV 2023] [code]
Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection [IEEE TIP] [code]
Msflow: Multiscale flow based framework for unsupervised anomaly detection [IEEE Trans. Neural Netw. Learn. Syst. 2024] [code]
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly Detection [2024] [code]
Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings [CVPR 2020]
Glancing at the patch: Anomaly localization with global and local feature comparison [CVPR 2021]
Multiresolution knowledge distillation for anomaly detection [CVPR 2021]
Anomaly detection via reverse distillation from one-class embedding [CVPR 2022]
Unsupervised image anomaly detection and segmentation based on pretrained feature mapping [IEEE TII 2022]
Reconstructed student-teacher and discriminative networks for anomaly detection [IROS 2022]
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection [WACV 2023] [code]
Informative knowledge distillation for image anomaly segmentation [Knowledge-based Systems 2022] [code]
Remembering normality: Memory-guided knowledge distillation for unsupervised [ICCV 2023]
Destseg: Segmentation guided denoising student-teacher for anomaly detection [CVPR 2023] [code]
Enhanced Multi-Scale Features Mutual Mapping Fusion Based on Reverse Knowledge Distillation for Industrial Anomaly Detection and Localization [IEEE Trans. Big Data 2024]
AEKD: Unsupervised auto-encoder knowledge distillation for industrial anomaly detection [JMS 2024]
Masked feature regeneration based asymmetric student–teacher network for anomaly detection [Multimedia Tools and Applications 2024]
MCAD: Multi-classification anomaly detection with relational knowledge distillation [Neural Computing and Applications 2024]
Contextual affinity distillation for image anomaly detection [WACV 2024]
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies [WACV 2024]
Feature-Constrained and Attention-Conditioned Distillation Learning for Visual Anomaly Detection [ICASSP 2024]
Dual-modeling decouple distillation for unsupervised anomaly detection [ACM MM 2024]
Cutpaste: Self-supervised learning for anomaly detection and localization [CVPR 2021] [unofficial code]
Anomaly Detection under Distribution Shift [ICCV 2023] [code]
Simplenet: A simple network for image anomaly detection and localization [CVPR 2023] [code]
Slsg: Industrial image anomaly detection with improved feature embeddings and one-class classification [PR 2024]
Generalad: Anomaly detection across domains by attending to distorted features [ECCV 2024] [code]
Learning Transferable Representations for Image Anomaly Localization Using Dense Pretraining [WACV 2024] [code]
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization [ECCV 2024] [code]
Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection [IEEE TCSVT 2024] [code]
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows [2021] [unofficial code]
Same same but differnet: Semi-supervised defect detection with normalizing flows [WACV 2021] [code]
Pedenet: Image anomaly localization via patch embeddin and density estimation [Pattern Recognition Letters 2022]
Cflow-ad: Real-time unsupervised anomaly detection with localization via conditional normalizing flows [WACV 2022] [code]
Position Encoding Enhanced Feature Mapping for Image Anomaly Detection [CASE 2022] [code]
Focus your distribution: Coarse-to-fine non-contrastive learning for anomaly detection and localization [ICME 2022]
Anomaly detection of defect using energy of point pattern features within random finite set framework [Engineering Applications of Artificial Intelligence 2024] [code]
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection [WACV 2022] [code]
Msflow: Multiscale flow based framework for unsupervised anomaly detection [IEEE Trans. Neural Netw. Learn. Syst. 2024] [code]
Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization [IEEE TII 2023] [code]
Pyramidflow: High-resolution defect contrastive localization using pyramid normalizing flow [CVPR 2023] [code]
Attention modules improve image-level anomaly detection for industrial inspection: A differnet case study [WACV 2024]
Franomaly: flow-based rapid anomaly detection from images [Applied Intelligence 2024]
Padim: a patch distribution modeling framework for anomaly detection and localization [ICPR 2021] [code]
Towards total recall in industrial anomaly detection [CVPR 2022] [code]
Multi-scale patch-based representation learning for image anomaly detection and segmentation [WACV 2022] [code]
Cfa: Coupled-hypersphere-based feature adaptation for target-oriented anomaly localization [IEEE Access 2022] [code]
Inter-realization channels: Unsupervised anomaly detection beyond one-class classification [ICCV 2023] [code]
Pni : Industrial anomaly detection using position [ICCV 2023] [code]
Diversity-measurable anomaly detection [CVPR 2023] [code]
FAPM: FAST ADAPTIVE PATCH MEMORY FOR REAL-TIME INDUSTRIAL ANOMALY DETECTION [ICASSP 2023] [code]
FAPM: FAST ADAPTIVE PATCH MEMORY FOR REAL-TIME INDUSTRIAL ANOMALY DETECTION [ICASSP 2023] [code]
Pushing the limits of fewshot anomaly detection in industry vision: Graphcore [ICLR 2023]
Unsupervised Image Anomaly Detection and Localization in Industry Based on Self-Updated Memory and Center Clustering [IEEE TIM 2023]
DMAD: Dual Memory Bank for Real-World Anomaly Detection [2024]
VQ-Flow: Taming Normalizing Flows for Multi-Class Anomaly Detection via Hierarchical Vector Quantization [2024] [code]
A Reconstruction-Based Feature Adaptation for Anomaly Detection with Self-Supervised Multi-Scale Aggregation [ICASSP 2024]
PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features [[2024]](PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features)
REB: Reducing biases in representation for industrial anomaly detection [Knowledge-Based Systems 2024] [code]
ReConPatch : Contrastive Patch Representation Learning for Industrial Anomaly Detection [WACV 2024]
Continuous Memory Representation for Anomaly Detection [ECCV 2024] [code]
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection [ECCVW 2024]
MemoryMamba: Memory-Augmented State Space Model for Defect Recognition [2024]
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection [NeurIPS 2024] [code]
Learning Transferable Visual Models From Natural Language Supervision [ICML 2021] [code]
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation [CVPR 2023] [Unofficial code]
Random Word Data Augmentation with CLIP for Zero-Shot Anomaly Detection [BMVC 2023] [code]
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection [2023] [code]
Anovl: Adapting vision-language models for unified zero-shot anomaly localization [2023] [code]
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection [ICLR 2024] [code]
Anomaly detection by adapting a pre-trained vision language mode [2024]
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection [CVPR 2024] [code]
Filo: Zero-shot anomaly detection by fine-grained description and high-quality localization [ACM MM 2024] [code]
ClipSAM: CLIP and SAM collaboration for zero-shot anomaly segmentation [Neurocomputing 2025]
Dual-image enhanced clip for zero-shot anomaly detection [2024]
AnoPLe: Few-Shot Anomaly Detection via Bi-directional Prompt Learning with Only Normal Samples [2024] [code]
IAD-CLIP: Vision-Language Models for Zero-Shot Industrial Anomaly Detection [ICAMechS 2024]
Industrial Image Anomaly Localization Based on Gaussian Clustering of Pretrained Feature [IEEE Trans. Ind. Electron 2021]
Anomaly Clustering: Grouping Images Into Coherent Clusters of Anomaly Types [WACV 2023]
JRCC-Net: A Segmentation Network With Joint Representation and Contrast Clustering for Surface Anomaly Detection [IEEE TIM 2023]
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection [ECCV 2024] [code]
Variational autoencoder for anomaly detection: A comparative study [2024] [code]
DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection [ICCV 2021] [code]
Reconstruction by inpainting for visual anomaly detection [PR 2021]
Unsupervised anomaly segmentation via deep feature reconstruction [Neurocomputing 2021] [code]
Divide-and-Assemble: Learning Block-wise Memory for Unsupervised Anomaly Detection [ICCV 2021]
Learning deep feature correspondence for unsupervised anomaly detection and segmentation [PR 2022] [code]
DSR - A dual subspace re-projection network for surface anomaly detection [ECCV 2022] [code]
Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization [ECCV 2022] [code]
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection [CVPR 2022] [code]
FastRecon: Few-shot Industrial Anomaly Detection via Fast Feature Reconstruction [ICCV 2023] [code]
Template-guided hierarchical feature restoration for anomaly detection [ICCV 2023]
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection [IEEE TPAMI 2023] [code]
Neural network training strategy to enhance anomaly detection performance: A perspective on reconstruction loss amplification [ICASSP 2024]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Implicit Foreground-Guided Network for Anomaly Detection and Localization [ICASSP 2024] [code]
Mixed-Attention Auto Encoder for Multi-Class Industrial Anomaly Detection [ICASSP 2024]
Patch-Wise Augmentation for Anomaly Detection and Localization [ICASSP 2024]
Dual-Constraint Autoencoder and Adaptive Weighted Similarity Spatial Attention for Unsupervised Anomaly Detection [IEEE TII 2024]
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection [2023] [code]
GAN-based anomaly detection: A review [Neurocomputing 2022]
Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection [AAAI 2021]
Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection [IEEE TIP] [code]
Few-shot defect image generation via defect-aware feature manipulation [AAAI 2023] [code]
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization [ISIE 2021] [code]
ADTR: Anomaly Detection Transformer with Feature Reconstruction [ICONIP 2022]
AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder [IEEE Access 2022]
Masked Transformer for image Anomaly Localization [International Journal of Neural Systems 2022]
Inpainting Transformer for Anomaly Detection [ICIAP 2022]
Masked swin transformer unet for industrial anomaly detection [IEEE TII 2022]
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection [ICCV 2023] [code]
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization [IEEE TASE 2024] [code]
Prior Normality Prompt Transformer for Multiclass Industrial Image Anomaly Detection [IEEE TII 2024]
Exploring plain ViT features for multi-class unsupervised visual anomaly detection [Computer Vision and Image Understanding 2025] [code]
AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise [CVPR workshop 2022] [code]
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection [2023] [code]
Anomaly Detection with Conditioned Denoising Diffusion Models [2023] [code]
LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection [2023]
Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model [ICCV 2023] [code]
Removing Anomalies as Noises for Industrial Defect Localization [ICCV 2023]
A Diffusion-Based Framework for Multi-Class Anomaly Detection [AAAI 2024] [code]
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model [AAAI 2024] [code]
D3AD: Dynamic Denoising Diffusion Probabilistic Model for Anomaly Detection [2024]
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection [ECCV 2024] [code]
TransFusion – A Transparency-Based Diffusion Model for Anomaly Detection [ECCV 2024] [code]
AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model [2024]
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection [2025] [code]
GPT-4V-AD: Exploring Grounding Potential of VQA-Oriented GPT-4V for Zero-Shot Anomaly Detection [IJCAI 2024] [code]
AnomalyGPT: detecting industrial anomalies using large vision-language models [AAAI 2024] [code]
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning [2024] [code]
LogiCode: An LLM-Driven Framework for Logical Anomaly Detection [IEEE TASE 2024]
SEAD: Segment Element-Based Anomaly Detection [IEEE Access]
Segment Any Anomaly without Training via Hybrid Prompt Regularization [2023] [code]
Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt [AAAI 2024] [code]
A SAM-guided Two-stream Lightweight Model for Anomaly Detection [ACM TMCCA 2024] [code]
EasyNet: An Easy Network for 3D Industrial Anomaly Detection [ACM MM 2023] [code]
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning [ACM MM 2024] [code]
3D Industrial anomaly detection via dual reconstruction network [Applied Intelligence 2024]
R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detection [ECCV 2024] [homepage]
Complementary pseudo multimodal feature for point cloud anomaly detection [PR 2024] [code]
Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework [2024] [code]
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection [NeurIPS 2024] [code]
Real3D-AD: A Dataset of Point Cloud Anomaly Detection [NeurIPS 2023] [code]
Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping [CVPR 2024] [code]
MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection [CVPR 2019] [data]
SPot-the-Difference Self-supervised Pre-training for Anomaly Detection and Segmentation [ECCV 2022] [data]
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization [ISIE 2021] [data]
Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions [ICUMT 2021] [data]
Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization [IJCV 2022] [data]
The mvtec 3d-ad dataset for unsupervised 3d anomaly detection and localization [VISAPP 2021] [data]
The Eyecandies Dataset for Unsupervised Multimodal Anomaly Detection and Localization [ACCV 2022] [data]
Real3D-AD: A Dataset of Point Cloud Anomaly Detection [NeurIPS 2023] [data]
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection [CVPR 2024] [data]
PUAD: Frustratingly Simple Method for Robust Anomaly Detection [ICIP 2024]
Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection [ECCV 2024] [code]
A Unified Model for Multi-class Anomaly Detection [NeurIPS 2022] [code]
A Survey on Industrial Anomaly Detection – from Methodology to Implementation
35
2 commits
updated Mar 4, 2025
A Diffusion-Based Framework for Multi-Class Anomaly Detection [AAAI 2024] [code]
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model [AAAI 2024] [code]
AnomalyGPT: detecting industrial anomalies using large vision-language models [AAAI 2024] [code]
Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt [AAAI 2024] [code]
Hyperbolic Anomaly Detection [CVPR 2024]
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection [CVPR 2024] [code]
Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble [CVPR 2024 Visual Anomaly Detection Workshop] [homepage]
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping [CVPR 2024] [code]
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection [CVPR 2024] [data]
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection [NeurIPS 2024] [code]
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection [NeurIPS 2024] [code]
Generalad: Anomaly detection across domains by attending to distorted features [ECCV 2024] [code]
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization [ECCV 2024] [code]
Continuous Memory Representation for Anomaly Detection [ECCV 2024] [code]
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection [ECCV 2024] [code]
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection [ECCV 2024] [code]
TransFusion – A Transparency-Based Diffusion Model for Anomaly Detection [ECCV 2024] [code]
R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detection [ECCV 2024] [homepage]
Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection [ECCV 2024] [code]
Dual-modeling decouple distillation for unsupervised anomaly detection [ACM MM 2024]
Filo: Zero-shot anomaly detection by fine-grained description and high-quality localization [ACM MM 2024] [code]
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning [ACM MM 2024] [code]
A Survey on Explainable Anomaly Detection [ACM TKDD 2023]
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect [2024]
Deep industrial image anomaly detection: A survey [Machine Intelligence Research 2024] [code]
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection [2024] [code]
Surface Defect Detection based on Improved YOLOv3-Tiny Algorithm [CCC 2022]
Metal surface defect detection based on improved YOLOv5 [Scientific Reports 2023]
Steel Surface Defect Detection Algorithm Based on YOLOv8 [Electronics 2024]
SSCL: Semi-supervised Contrastive Learning for Industrial Anomaly Detection [PRCV 2023]
GANomaly: Semi-supervised Anomaly Detection via Adversarial Training [ACCV 2018] [code]
Same same but differnet: Semi-supervised defect detection with normalizing flows [WACV 2021] [code]
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities [Engineering Applications of Artificial Intelligence 2023] [unofficial code]
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection [CVPR 2023] [code]
Hyperbolic Anomaly Detection [CVPR 2024]
Self-Supervised Autoencoders for Visual Anomaly Detection [Mathematics 2024]
Multilevel saliency-guided self-supervised learning for image anomaly detection [Signal, Image and Video Processing 2024]
TDAD: Self-supervised industrial anomaly detection with a two-stage diffusion model [Computers in Industry 2025]
SMD Anomaly Detection: A Self-Supervised Texture–Structure Anomaly Detection Framework [IEEE TIM 2022]
Self-supervised anomaly detection based on foreground enhancement and autoencoder reconstruction [Signal, Image and Video Processing 2024]
Self-supervised Visual Anomaly Detection with Image Patch Generation and Comparison Networks [ICIC 2024]
Self-supervised anomaly detection in computer vision and beyond: A survey and outlook [Neural Networks 2024]
Industrial Image Anomaly Detection via Self-Supervised Learning with Feature Enhancement Assistance [Applied Sciences 2024]
Self-Supervised Image Anomaly Detection and Localization with Synthetic Anomalies [IOTSMS 2023]
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation [ACCV 2020] [code]
Cutpaste: Self-supervised learning for anomaly detection and localization [CVPR 2021] [unofficial code]
SPot-the-Difference Self-supervised Pre-training for Anomaly Detection and Segmentation [ECCV 2022] [code]
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection [CVPR 2022] [code]
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection [IEEE TPAMI 2023] [code]
A Discrepancy Aware Framework for Robust Anomaly Detection [IEEE TII 2023] [code]
Revisiting Reverse Distillation for Anomaly Detection [CVPR 2023] [code]
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection [2023]
A Reconstruction-Based Feature Adaptation for Anomaly Detection with Self-Supervised Multi-Scale Aggregation [ICASSP 2024]
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network [CVPR 2024] [code]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Weakly supervised anomaly detection based on sparsity prior [Electronic Research Archive 2024]
Topology-preserving transfer learning for weakly-supervised anomaly detection and segmentation [PR Letters 2023]
Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection [CVPR 2022] [code]
Prototypical Residual Networks for Anomaly Detection and Localization [CVPR 2023] [unofficial code]
IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing [IEEE TCYB 2024] [code]
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection [CVPR 2024] [code]
BiaS: Incorporating Biased Knowledge to Boost Unsupervised Image Anomaly Localization [IEEE TSMC 2024]
Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble [CVPR 2024 Visual Anomaly Detection Workshop] [homepage]
Mixed supervision for surface-defect detection: From weakly to fully supervised learning [Computers in Industry 2021] [code]
Unsupervised industrial anomaly detection with diffusion models [J. Vis. Commun. Image R. 2023] [code]
Glancing at the patch: Anomaly localization with global and local feature comparison [CVPR 2021]
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows [2021] [unofficial code]
Inter-realization channels: Unsupervised anomaly detection beyond one-class classification [ICCV 2023] [code]
Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection [IEEE TIP] [code]
Msflow: Multiscale flow based framework for unsupervised anomaly detection [IEEE Trans. Neural Netw. Learn. Syst. 2024] [code]
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly Detection [2024] [code]
Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings [CVPR 2020]
Glancing at the patch: Anomaly localization with global and local feature comparison [CVPR 2021]
Multiresolution knowledge distillation for anomaly detection [CVPR 2021]
Anomaly detection via reverse distillation from one-class embedding [CVPR 2022]
Unsupervised image anomaly detection and segmentation based on pretrained feature mapping [IEEE TII 2022]
Reconstructed student-teacher and discriminative networks for anomaly detection [IROS 2022]
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection [WACV 2023] [code]
Informative knowledge distillation for image anomaly segmentation [Knowledge-based Systems 2022] [code]
Remembering normality: Memory-guided knowledge distillation for unsupervised [ICCV 2023]
Destseg: Segmentation guided denoising student-teacher for anomaly detection [CVPR 2023] [code]
Enhanced Multi-Scale Features Mutual Mapping Fusion Based on Reverse Knowledge Distillation for Industrial Anomaly Detection and Localization [IEEE Trans. Big Data 2024]
AEKD: Unsupervised auto-encoder knowledge distillation for industrial anomaly detection [JMS 2024]
Masked feature regeneration based asymmetric student–teacher network for anomaly detection [Multimedia Tools and Applications 2024]
MCAD: Multi-classification anomaly detection with relational knowledge distillation [Neural Computing and Applications 2024]
Contextual affinity distillation for image anomaly detection [WACV 2024]
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies [WACV 2024]
Feature-Constrained and Attention-Conditioned Distillation Learning for Visual Anomaly Detection [ICASSP 2024]
Dual-modeling decouple distillation for unsupervised anomaly detection [ACM MM 2024]
Cutpaste: Self-supervised learning for anomaly detection and localization [CVPR 2021] [unofficial code]
Anomaly Detection under Distribution Shift [ICCV 2023] [code]
Simplenet: A simple network for image anomaly detection and localization [CVPR 2023] [code]
Slsg: Industrial image anomaly detection with improved feature embeddings and one-class classification [PR 2024]
Generalad: Anomaly detection across domains by attending to distorted features [ECCV 2024] [code]
Learning Transferable Representations for Image Anomaly Localization Using Dense Pretraining [WACV 2024] [code]
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization [ECCV 2024] [code]
Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection [IEEE TCSVT 2024] [code]
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows [2021] [unofficial code]
Same same but differnet: Semi-supervised defect detection with normalizing flows [WACV 2021] [code]
Pedenet: Image anomaly localization via patch embeddin and density estimation [Pattern Recognition Letters 2022]
Cflow-ad: Real-time unsupervised anomaly detection with localization via conditional normalizing flows [WACV 2022] [code]
Position Encoding Enhanced Feature Mapping for Image Anomaly Detection [CASE 2022] [code]
Focus your distribution: Coarse-to-fine non-contrastive learning for anomaly detection and localization [ICME 2022]
Anomaly detection of defect using energy of point pattern features within random finite set framework [Engineering Applications of Artificial Intelligence 2024] [code]
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection [WACV 2022] [code]
Msflow: Multiscale flow based framework for unsupervised anomaly detection [IEEE Trans. Neural Netw. Learn. Syst. 2024] [code]
Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization [IEEE TII 2023] [code]
Pyramidflow: High-resolution defect contrastive localization using pyramid normalizing flow [CVPR 2023] [code]
Attention modules improve image-level anomaly detection for industrial inspection: A differnet case study [WACV 2024]
Franomaly: flow-based rapid anomaly detection from images [Applied Intelligence 2024]
Padim: a patch distribution modeling framework for anomaly detection and localization [ICPR 2021] [code]
Towards total recall in industrial anomaly detection [CVPR 2022] [code]
Multi-scale patch-based representation learning for image anomaly detection and segmentation [WACV 2022] [code]
Cfa: Coupled-hypersphere-based feature adaptation for target-oriented anomaly localization [IEEE Access 2022] [code]
Inter-realization channels: Unsupervised anomaly detection beyond one-class classification [ICCV 2023] [code]
Pni : Industrial anomaly detection using position [ICCV 2023] [code]
Diversity-measurable anomaly detection [CVPR 2023] [code]
FAPM: FAST ADAPTIVE PATCH MEMORY FOR REAL-TIME INDUSTRIAL ANOMALY DETECTION [ICASSP 2023] [code]
FAPM: FAST ADAPTIVE PATCH MEMORY FOR REAL-TIME INDUSTRIAL ANOMALY DETECTION [ICASSP 2023] [code]
Pushing the limits of fewshot anomaly detection in industry vision: Graphcore [ICLR 2023]
Unsupervised Image Anomaly Detection and Localization in Industry Based on Self-Updated Memory and Center Clustering [IEEE TIM 2023]
DMAD: Dual Memory Bank for Real-World Anomaly Detection [2024]
VQ-Flow: Taming Normalizing Flows for Multi-Class Anomaly Detection via Hierarchical Vector Quantization [2024] [code]
A Reconstruction-Based Feature Adaptation for Anomaly Detection with Self-Supervised Multi-Scale Aggregation [ICASSP 2024]
PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features [[2024]](PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features)
REB: Reducing biases in representation for industrial anomaly detection [Knowledge-Based Systems 2024] [code]
ReConPatch : Contrastive Patch Representation Learning for Industrial Anomaly Detection [WACV 2024]
Continuous Memory Representation for Anomaly Detection [ECCV 2024] [code]
AnomalousPatchCore: Exploring the Use of Anomalous Samples in Industrial Anomaly Detection [ECCVW 2024]
MemoryMamba: Memory-Augmented State Space Model for Defect Recognition [2024]
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection [NeurIPS 2024] [code]
Learning Transferable Visual Models From Natural Language Supervision [ICML 2021] [code]
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation [CVPR 2023] [Unofficial code]
Random Word Data Augmentation with CLIP for Zero-Shot Anomaly Detection [BMVC 2023] [code]
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection [2023] [code]
Anovl: Adapting vision-language models for unified zero-shot anomaly localization [2023] [code]
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection [ICLR 2024] [code]
Anomaly detection by adapting a pre-trained vision language mode [2024]
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection [CVPR 2024] [code]
Filo: Zero-shot anomaly detection by fine-grained description and high-quality localization [ACM MM 2024] [code]
ClipSAM: CLIP and SAM collaboration for zero-shot anomaly segmentation [Neurocomputing 2025]
Dual-image enhanced clip for zero-shot anomaly detection [2024]
AnoPLe: Few-Shot Anomaly Detection via Bi-directional Prompt Learning with Only Normal Samples [2024] [code]
IAD-CLIP: Vision-Language Models for Zero-Shot Industrial Anomaly Detection [ICAMechS 2024]
Industrial Image Anomaly Localization Based on Gaussian Clustering of Pretrained Feature [IEEE Trans. Ind. Electron 2021]
Anomaly Clustering: Grouping Images Into Coherent Clusters of Anomaly Types [WACV 2023]
JRCC-Net: A Segmentation Network With Joint Representation and Contrast Clustering for Surface Anomaly Detection [IEEE TIM 2023]
Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection [ECCV 2024] [code]
Variational autoencoder for anomaly detection: A comparative study [2024] [code]
DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection [ICCV 2021] [code]
Reconstruction by inpainting for visual anomaly detection [PR 2021]
Unsupervised anomaly segmentation via deep feature reconstruction [Neurocomputing 2021] [code]
Divide-and-Assemble: Learning Block-wise Memory for Unsupervised Anomaly Detection [ICCV 2021]
Learning deep feature correspondence for unsupervised anomaly detection and segmentation [PR 2022] [code]
DSR - A dual subspace re-projection network for surface anomaly detection [ECCV 2022] [code]
Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization [ECCV 2022] [code]
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection [CVPR 2022] [code]
FastRecon: Few-shot Industrial Anomaly Detection via Fast Feature Reconstruction [ICCV 2023] [code]
Template-guided hierarchical feature restoration for anomaly detection [ICCV 2023]
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection [IEEE TPAMI 2023] [code]
Neural network training strategy to enhance anomaly detection performance: A perspective on reconstruction loss amplification [ICASSP 2024]
RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection [CVPR 2024] [code]
Implicit Foreground-Guided Network for Anomaly Detection and Localization [ICASSP 2024] [code]
Mixed-Attention Auto Encoder for Multi-Class Industrial Anomaly Detection [ICASSP 2024]
Patch-Wise Augmentation for Anomaly Detection and Localization [ICASSP 2024]
Dual-Constraint Autoencoder and Adaptive Weighted Similarity Spatial Attention for Unsupervised Anomaly Detection [IEEE TII 2024]
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection [2023] [code]
GAN-based anomaly detection: A review [Neurocomputing 2022]
Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection [AAAI 2021]
Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection [IEEE TIP] [code]
Few-shot defect image generation via defect-aware feature manipulation [AAAI 2023] [code]
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization [ISIE 2021] [code]
ADTR: Anomaly Detection Transformer with Feature Reconstruction [ICONIP 2022]
AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder [IEEE Access 2022]
Masked Transformer for image Anomaly Localization [International Journal of Neural Systems 2022]
Inpainting Transformer for Anomaly Detection [ICIAP 2022]
Masked swin transformer unet for industrial anomaly detection [IEEE TII 2022]
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection [ICCV 2023] [code]
AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly Detection and Localization [IEEE TASE 2024] [code]
Prior Normality Prompt Transformer for Multiclass Industrial Image Anomaly Detection [IEEE TII 2024]
Exploring plain ViT features for multi-class unsupervised visual anomaly detection [Computer Vision and Image Understanding 2025] [code]
AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise [CVPR workshop 2022] [code]
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection [2023] [code]
Anomaly Detection with Conditioned Denoising Diffusion Models [2023] [code]
LafitE: Latent Diffusion Model with Feature Editing for Unsupervised Multi-class Anomaly Detection [2023]
Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model [ICCV 2023] [code]
Removing Anomalies as Noises for Industrial Defect Localization [ICCV 2023]
A Diffusion-Based Framework for Multi-Class Anomaly Detection [AAAI 2024] [code]
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model [AAAI 2024] [code]
D3AD: Dynamic Denoising Diffusion Probabilistic Model for Anomaly Detection [2024]
GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection [ECCV 2024] [code]
TransFusion – A Transparency-Based Diffusion Model for Anomaly Detection [ECCV 2024] [code]
AnomalySD: Few-Shot Multi-Class Anomaly Detection with Stable Diffusion Model [2024]
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly Detection [2025] [code]
GPT-4V-AD: Exploring Grounding Potential of VQA-Oriented GPT-4V for Zero-Shot Anomaly Detection [IJCAI 2024] [code]
AnomalyGPT: detecting industrial anomalies using large vision-language models [AAAI 2024] [code]
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning [2024] [code]
LogiCode: An LLM-Driven Framework for Logical Anomaly Detection [IEEE TASE 2024]
SEAD: Segment Element-Based Anomaly Detection [IEEE Access]
Segment Any Anomaly without Training via Hybrid Prompt Regularization [2023] [code]
Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt [AAAI 2024] [code]
A SAM-guided Two-stream Lightweight Model for Anomaly Detection [ACM TMCCA 2024] [code]
EasyNet: An Easy Network for 3D Industrial Anomaly Detection [ACM MM 2023] [code]
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning [ACM MM 2024] [code]
3D Industrial anomaly detection via dual reconstruction network [Applied Intelligence 2024]
R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detection [ECCV 2024] [homepage]
Complementary pseudo multimodal feature for point cloud anomaly detection [PR 2024] [code]
Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework [2024] [code]
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection [NeurIPS 2024] [code]
Real3D-AD: A Dataset of Point Cloud Anomaly Detection [NeurIPS 2023] [code]
Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping [CVPR 2024] [code]
MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection [CVPR 2019] [data]
SPot-the-Difference Self-supervised Pre-training for Anomaly Detection and Segmentation [ECCV 2022] [data]
VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization [ISIE 2021] [data]
Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions [ICUMT 2021] [data]
Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization [IJCV 2022] [data]
The mvtec 3d-ad dataset for unsupervised 3d anomaly detection and localization [VISAPP 2021] [data]
The Eyecandies Dataset for Unsupervised Multimodal Anomaly Detection and Localization [ACCV 2022] [data]
Real3D-AD: A Dataset of Point Cloud Anomaly Detection [NeurIPS 2023] [data]
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection [CVPR 2024] [data]
PUAD: Frustratingly Simple Method for Robust Anomaly Detection [ICIP 2024]
Self-supervised Feature Adaptation for 3D Industrial Anomaly Detection [ECCV 2024] [code]
A Unified Model for Multi-class Anomaly Detection [NeurIPS 2022] [code]
