Industrial Anomaly Detection SOTA Paper Viewer
Based on information from the GitHub repository awesome-industrial-anomaly-detection.
SOTA Methods (with Code)
| Paper Title | Conference/Journal | Year | Topic |
|---|---|---|---|
| Anomaly Detection via Reverse Distillation from One-Class Embedding | CVPR | 2022 | Teacher-Student |
| Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection | CVPR | 2025 | Multi-Class Unif[1]ied |
| Revisiting Reverse Distillation for Anomaly Detection | CVPR | 2023 | Teacher-Student |
| SimpleNet: A Simple Network for Image Anomaly Detection and Localization | CVPR | 2023 | One-Class-Classification |
| Real-time unsupervised anomaly detection with localization via conditional normalizing flows | WACV | 2022 | Distribution Map |
| PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow | CVPR | 2023 | Distribution Map |
| Towards total recall in industrial anomaly detection | CVPR | 2022 | Memory-bank |
| PNI: Industrial Anomaly Detection using Position and Neighborhood Information | ICCV | 2023 | Memory-bank |
| Draem-a discriminatively trained reconstruction embedding for surface anomaly detection | ICCV | 2021 | Reconstruction-based |
| DSR: A dual subspace re-projection network for surface anomaly detection | ECCV | 2022 | Reconstruction-based |
| Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection | TIP | 2023 | Reconstruction-based |
| RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection | CVPR | 2024 | Reconstruction-based |
| Registration based few-shot anomaly detection | ECCV | 2022 | Few Shot |
| AnomalyGPT: Detecting Industrial Anomalies using Large Vision-Language Models | AAAI | 2024 | Few Shot |
| Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection | CVPR | 2022 | Few abnormal samples |
| Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection | CVPR | 2023 | Few abnormal samples |
| Deep one-class classification via interpolated gaussian descriptor | AAAI | 2022 | Noisy AD |
| SoftPatch: Unsupervised Anomaly Detection with Noisy Data | NeurIPS | 2022 | Noisy AD |
| Inter-Realization Channels: Unsupervised Anomaly Detection Beyond One-Class Classification | ICCV | 2023 | Noisy AD |
| Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt | AAAI | 2024 | Continual AD |
| A Unified Model for Multi-class Anomaly Detection | NeurIPS | 2022 | Multi-class unified |
| Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection | NeurIPS | 2023 | Multi-class unified |
| Multimodal Industrial Anomaly Detection via Hybrid Fusion | CVPR | 2023 | RGBD |
| Real3D-AD: A Dataset of Point Cloud Anomaly Detection | NeurIPS | 2023 | Point Cloud |
| AnoVL: Adapting Vision-Language Models for Unified Zero-shot Anomaly Localization | arxiv | 2023 | Zero Shot |
| Segment Any Anomaly without Training via Hybrid Prompt Regularization | arxiv | 2023 | Zero Shot |
| PSAD: Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection | AAAI | 2024 | Logical/Few Shot |
| UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection | arxiv | 2023 | Multi-class unified |