RRepoGEO

REPOGEO REPORT · LITE

pprp/awesome-attention-mechanism-in-cv

Default branch main · commit 59997fe4 · scanned 6/30/2026, 6:38:09 PM

GitHub: 1,273 stars · 172 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 pprp/awesome-attention-mechanism-in-cv, 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 README H1 to explicitly state "Awesome List"

    Why:

    CURRENT
    # Awesome-Attention-Mechanism-in-cv [](https://awesome.re)
    COPY-PASTE FIX
    # Awesome List of Attention Mechanisms in Computer Vision [](https://awesome.re)
  • mediumtopics#2
    Add 'awesome-list' and 'resources' topics to reinforce repo type

    Why:

    CURRENT
    attention-mechanisms, attention-model, computer-vision, implementation, plugandplay, pytorch-attention, vision-transformer
    COPY-PASTE FIX
    attention-mechanisms, attention-model, computer-vision, implementation, plugandplay, pytorch-attention, vision-transformer, awesome-list, resources
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/pprp/awesome-attention-mechanism-in-cv

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 pprp/awesome-attention-mechanism-in-cv
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 1×
  2. GitHub · recommended 1×
  3. Awesome-Vision-Transformer · recommended 1×
  4. PyTorch Hub · recommended 1×
  5. TensorFlow Hub · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of attention mechanism implementations for computer vision tasks?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. GitHub
    3. Awesome-Vision-Transformer
    4. PyTorch Hub
    5. TensorFlow Hub
    6. Kaggle
    7. arXiv

    AI recommended 7 alternatives but never named pprp/awesome-attention-mechanism-in-cv. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some plug-and-play attention modules to integrate into existing vision models?
    you: not recommended
    AI recommended (in order):
    1. SENet
    2. CBAM
    3. ECA-Net
    4. GC Block
    5. Coordinate Attention
    6. NLNet

    AI recommended 6 alternatives but never named pprp/awesome-attention-mechanism-in-cv. 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 pprp/awesome-attention-mechanism-in-cv?
    pass
    AI did not name pprp/awesome-attention-mechanism-in-cv — 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 pprp/awesome-attention-mechanism-in-cv in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pprp/awesome-attention-mechanism-in-cv 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 pprp/awesome-attention-mechanism-in-cv solve, and who is the primary audience?
    pass
    AI did not name pprp/awesome-attention-mechanism-in-cv — 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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pprp/awesome-attention-mechanism-in-cv — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite