RRepoGEO

REPOGEO REPORT · LITE

52CV/CVPR-2021-Papers

Default branch main · commit 81563f57 · scanned 5/10/2026, 2:17:23 AM

GitHub: 2,542 stars · 312 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 52CV/CVPR-2021-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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    Aggregates and categorizes papers from the CVPR 2021 conference, providing links to PDFs, project pages, and code for computer vision researchers and students.
  • hightopics#2
    Add specific computer vision topics

    Why:

    COPY-PASTE FIX
    cvpr, cvpr2021, computer-vision, deep-learning, academic-papers, research-papers, paper-list, object-re-identification, gaze-estimation, image-to-image-translation, nlp, transfer-learning, crowd-counting, slam, ocr, image-generation, contrastive-learning, dataset
  • highlicense#3
    Add a LICENSE file or clarify licensing in README

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT or Apache-2.0 if appropriate for a paper list) or explicitly state the licensing terms for the repository's content (e.g., 'This repository's content is for academic reference and is licensed under [specific license if applicable to the curation/links themselves].') in the README.

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 52CV/CVPR-2021-Papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv · recommended 2×
  2. Google Scholar · recommended 2×
  3. Connected Papers · recommended 2×
  4. Papers With Code · recommended 1×
  5. CVF Open Access · recommended 1×
  • CATEGORY QUERY
    Where can I find a categorized list of recent computer vision conference papers?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. CVF Open Access
    3. arXiv
    4. Google Scholar
    5. Connected Papers
    6. Awesome Computer Vision (GitHub repositories)

    AI recommended 6 alternatives but never named 52CV/CVPR-2021-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to browse academic papers on specific computer vision topics like object re-identification?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv
    3. Connected Papers
    4. ResearchRabbit
    5. Semantic Scholar
    6. Microsoft Academic
    7. IEEE Xplore
    8. ACM Digital Library
    9. OpenReview

    AI recommended 9 alternatives but never named 52CV/CVPR-2021-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
    fail

    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 52CV/CVPR-2021-Papers?
    pass
    AI named 52CV/CVPR-2021-Papers explicitly

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

  • If a team adopts 52CV/CVPR-2021-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 52CV/CVPR-2021-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 52CV/CVPR-2021-Papers solve, and who is the primary audience?
    pass
    AI did not name 52CV/CVPR-2021-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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MARKDOWN (README)
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52CV/CVPR-2021-Papers — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite