M-3LAB/awesome-industrial-anomaly-detection resource

Health v2 · maintenance only

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3747 stars · 340 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated awesome-list of papers, datasets, benchmarks, and SOTA methods for industrial image anomaly and defect detection. It accompanies a published survey and is continuously updated with recent research from major conferences.

Use cases

• find papers on industrial anomaly detection
• find datasets for defect detection in manufacturing images
• survey state-of-the-art anomaly segmentation methods
• research benchmarks for visual quality inspection
• keep up with anomaly detection papers from CVPR, ECCV, NeurIPS
• compare anomaly synthesis methods for training data

When to choose

• you need a curated starting point for industrial anomaly detection research
• you want links to datasets like MVTec AD and recent SOTA code
• you are writing a literature review on defect detection

When to avoid

• you need runnable software rather than a paper list
• you need non-image anomaly detection such as time-series or logs
• you need a maintained library with an API

Facets

learning-resource · maturity active

computer-vision machine-learning data-science computer-vision image-processing artificial-intelligence deep-learning cross-platform awesome-list anomaly-detection defect-detection industrial-inspection paper-list datasets survey manufacturing

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