RRepoGEO

REPOGEO REPORT · LITE

52CV/CVPR-2023-Papers

Default branch main · commit 28736e9d · scanned 6/1/2026, 2:57:39 AM

GitHub: 936 stars · 76 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-2023-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

2 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
    A curated collection of CVPR 2023 papers, categorized by research area, with links to official projects and code.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root, choosing a standard open-source license like MIT or Apache-2.0, to clearly define usage terms for the aggregated paper list and any associated content.

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-2023-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 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 2×
  2. Google Scholar · recommended 2×
  3. arXiv · recommended 1×
  4. CVF Open Access · recommended 1×
  5. Connected Papers · recommended 1×
  • CATEGORY QUERY
    Where can I find a categorized collection of recent computer vision conference papers?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. arXiv
    3. CVF Open Access
    4. Google Scholar
    5. Connected Papers
    6. AI Research (by Zeta Alpha)
    7. Conference Websites

    AI recommended 7 alternatives but never named 52CV/CVPR-2023-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to find top-tier research papers in object detection or 3D vision from recent years?
    you: not recommended
    AI recommended (in order):
    1. CVF Open Access (CVF-OAS)
    2. arXiv.org
    3. Papers With Code
    4. Google Scholar
    5. ACM Digital Library
    6. IEEE Xplore
    7. NeurIPS
    8. ICML
    9. IROS
    10. Stanford Vision and Learning Lab
    11. UC Berkeley AI Research
    12. CMU Robotics Institute
    13. FAIR
    14. Google Brain
    15. NVIDIA Research
    16. Microsoft Research

    AI recommended 16 alternatives but never named 52CV/CVPR-2023-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-2023-Papers?
    pass
    AI named 52CV/CVPR-2023-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-2023-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 52CV/CVPR-2023-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-2023-Papers solve, and who is the primary audience?
    pass
    AI did not name 52CV/CVPR-2023-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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52CV/CVPR-2023-Papers — 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