産業用異常検知 SOTA論文ビューア
GitHubリポジトリ awesome-industrial-anomaly-detection の情報を基にしています。
SOTA Method
論文名 | 会議/ジャーナル | 年 | トピック |
---|---|---|---|
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 |
MVTec AD AUROC スコア比較 (Image-Level)
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