willard-yuan/awesome-cbir-papers resource

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1758 stars · 287 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated awesome-list of classical and deep learning papers on content-based image retrieval (CBIR), covering local features, global features, instance search, ANN search, and industry systems. It also links to tutorials, datasets, demos, and useful packages for image retrieval research.

Use cases

• find papers on content-based image retrieval
• research deep learning features for image search
• learn about SIFT and classical local feature retrieval methods
• find datasets for image retrieval benchmarks
• survey approximate nearest neighbor search methods
• study industrial image retrieval systems
• find tutorials on visual search and CBIR

When to choose

• you are researching or surveying image retrieval literature
• you need a starting point for CBIR, instance search, or ANN search papers
• you want curated links to datasets and tutorials for visual search

When to avoid

• you need runnable image retrieval software rather than papers
• you want an exhaustive, automatically updated bibliography
• you need non-image retrieval topics like text or video retrieval

Facets

learning-resource · maturity active

search-engine computer-vision machine-learning computer-vision image-processing artificial-intelligence awesome-lists cross-platform cbir image-retrieval visual-search paper-collection nearest-neighbor-search instance-retrieval local-features curated-list search

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