RRepoGEO

REPOGEO REPORT · LITE

SkalskiP/top-cvpr-2024-papers

Default branch master · commit 66dffdc3 · scanned 6/13/2026, 5:52:46 AM

GitHub: 737 stars · 57 forks

AI VISIBILITY SCORE
15 /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
0 / 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 SkalskiP/top-cvpr-2024-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 README to emphasize 'curated list with code and demos'

    Why:

    COPY-PASTE FIX
    Add this line immediately after the main H1 title in the README: "This repository is a curated collection of the most exciting and influential CVPR 2024 papers, including links to code and demos."
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/SkalskiP/top-cvpr-2024-papers
  • mediumtopics#3
    Add a more specific topic for 'curated collection'

    Why:

    CURRENT
    computer-vision, cvpr, cvpr2024, image-segmentation, object-detection, paper, transformers, vision-and-language
    COPY-PASTE FIX
    computer-vision, cvpr, cvpr2024, image-segmentation, object-detection, paper, transformers, vision-and-language, research-paper-collection

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 SkalskiP/top-cvpr-2024-papers
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. Hugging Face · recommended 1×
  3. arXiv · recommended 1×
  4. GitHub Trending · recommended 1×
  5. Awesome Computer Vision GitHub Repositories · recommended 1×
  • CATEGORY QUERY
    Looking for a curated list of cutting-edge computer vision research papers with code and demos.
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. Hugging Face
    3. arXiv
    4. GitHub Trending
    5. Awesome Computer Vision GitHub Repositories
    6. Google AI Blog
    7. Meta AI Blog
    8. Microsoft Research Blog
    9. Two Minute Papers

    AI recommended 9 alternatives but never named SkalskiP/top-cvpr-2024-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the most significant recent advancements in object detection and image segmentation research?
    you: not recommended
    AI recommended (in order):
    1. DETR
    2. Mask2Former
    3. DiffuSeg
    4. DALL-E 2
    5. Stable Diffusion
    6. SAM
    7. DINOv2
    8. YOLOv7
    9. YOLOv8
    10. RT-DETR
    11. CLIP
    12. GLIP
    13. NeRF
    14. Instant NGP

    AI recommended 14 alternatives but never named SkalskiP/top-cvpr-2024-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 SkalskiP/top-cvpr-2024-papers?
    pass
    AI did not name SkalskiP/top-cvpr-2024-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 SkalskiP/top-cvpr-2024-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name SkalskiP/top-cvpr-2024-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?

  • In one sentence, what problem does the repo SkalskiP/top-cvpr-2024-papers solve, and who is the primary audience?
    pass
    AI did not name SkalskiP/top-cvpr-2024-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?

Embed your GEO score

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