RRepoGEO

REPOGEO REPORT · LITE

willard-yuan/awesome-cbir-papers

Default branch master · commit 6aa5acfd · scanned 5/26/2026, 10:13:16 AM

GitHub: 1,762 stars · 290 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface willard-yuan/awesome-cbir-papers, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening sentence to clarify its nature as a curated collection

    Why:

    CURRENT
    The main goal is to collect classical and solid works of image retrieval in academia and industry.
    COPY-PASTE FIX
    This is a curated, categorized collection of classical and solid research papers on Content-Based Image Retrieval (CBIR) in academia and industry, designed to save researchers time by highlighting essential works.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of a suitable open-source license (e.g., MIT License).
  • mediumabout#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add `https://github.com/willard-yuan/awesome-cbir-papers` as the homepage URL in the repository's 'About' section.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface willard-yuan/awesome-cbir-papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Scholar
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Scholar · recommended 1×
  2. arXiv · recommended 1×
  3. IEEE Xplore Digital Library · recommended 1×
  4. ACM Digital Library · recommended 1×
  5. Microsoft Academic · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of research papers on image retrieval techniques?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv
    3. IEEE Xplore Digital Library
    4. ACM Digital Library
    5. Microsoft Academic
    6. Semantic Scholar
    7. OpenReview

    AI recommended 7 alternatives but never named willard-yuan/awesome-cbir-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the essential academic papers for understanding content-based visual search algorithms?
    you: not recommended
    AI recommended (in order):
    1. QBIC
    2. SIFT
    3. VLAD
    4. Bag-of-Visual-Words (BoVW)
    5. Convolutional Neural Networks (CNNs)
    6. Oxford Buildings
    7. Paris

    AI recommended 7 alternatives but never named willard-yuan/awesome-cbir-papers. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of willard-yuan/awesome-cbir-papers?
    pass
    AI did not name willard-yuan/awesome-cbir-papers — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts willard-yuan/awesome-cbir-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named willard-yuan/awesome-cbir-papers explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo willard-yuan/awesome-cbir-papers solve, and who is the primary audience?
    pass
    AI did not name willard-yuan/awesome-cbir-papers — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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