RRepoGEO

REPOGEO REPORT · LITE

52CV/CVPR-2022-Papers

Default branch main · commit f93925c8 · scanned 6/5/2026, 11:02:38 PM

GitHub: 630 stars · 58 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-2022-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
    A comprehensive, categorized collection of all accepted papers from the CVPR 2022 conference, organized by research area for easy browsing.
  • hightopics#2
    Add relevant topics for categorization

    Why:

    COPY-PASTE FIX
    computer-vision, cvpr, cvpr-2022, deep-learning, object-detection, image-segmentation, gan, transformer, 3d-vision, pose-estimation, medical-imaging, autonomous-vehicles, super-resolution, image-classification, vision-language, image-retrieval
  • highlicense#3
    Add a LICENSE file or state the license in README

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0) or add a clear statement to the README indicating the intended license for the repository's structure and metadata, such as 'All papers linked herein are subject to their original copyrights; this repository's structure and metadata are provided under the [Your Chosen License] license.'

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-2022-Papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Papers With Code · recommended 1×
  3. Connected Papers · recommended 1×
  4. Google Scholar · recommended 1×
  5. AI Research (by Google) · recommended 1×
  • CATEGORY QUERY
    How can I efficiently discover and browse the most recent computer vision research papers?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Papers With Code
    3. Connected Papers
    4. Google Scholar
    5. AI Research (by Google)
    6. CVF Open Access
    7. Semantic Scholar

    AI recommended 7 alternatives but never named 52CV/CVPR-2022-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the key papers from recent conferences on object detection and 3D vision?
    you: not recommended
    AI recommended (in order):
    1. DINO
    2. YOLOv7
    3. DiffusionDet
    4. SparseDETR
    5. OWL-ViT
    6. 3D Gaussian Splatting
    7. MVDream
    8. Zero-1-to-3
    9. Instruct-NeRF2NeRF
    10. Point-E
    11. Neuralangelo

    AI recommended 11 alternatives but never named 52CV/CVPR-2022-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-2022-Papers?
    pass
    AI named 52CV/CVPR-2022-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-2022-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 52CV/CVPR-2022-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-2022-Papers solve, and who is the primary audience?
    pass
    AI did not name 52CV/CVPR-2022-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

Drop this badge into the README of 52CV/CVPR-2022-Papers. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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52CV/CVPR-2022-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