RRepoGEO

REPOGEO REPORT · LITE

ChaofWang/Awesome-Super-Resolution

Default branch master · commit dcb621b9 · scanned 6/14/2026, 1:37:32 PM

GitHub: 3,070 stars · 368 forks

AI VISIBILITY SCORE
69 /100
Needs work
Category recall
2 / 2
Avg rank #3.0 when recommended
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 ChaofWang/Awesome-Super-Resolution, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    super-resolution, image-processing, deep-learning, computer-vision, awesome-list, research-papers, datasets, machine-learning
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0).
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    Set the homepage URL in the repository settings to a relevant project page or a link back to the GitHub repo itself if no external site exists (e.g., https://github.com/ChaofWang/Awesome-Super-Resolution).

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
2 / 2
100% of queries surface ChaofWang/Awesome-Super-Resolution
Avg rank
#3.0
Lower is better. #1 = top recommendation.
Share of voice
8%
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. arXiv · recommended 1×
  3. Google Scholar · recommended 1×
  4. Awesome Super-Resolution · recommended 1×
  5. thibaud-jty/awesome-super-resolution · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of super-resolution research papers and datasets?
    you: #5
    AI recommended (in order):
    1. Papers With Code
    2. arXiv
    3. Google Scholar
    4. Awesome Super-Resolution
    5. ChaofWang/Awesome-Super-Resolution (ChaofWang/Awesome-Super-Resolution) ← you
    6. thibaud-jty/awesome-super-resolution (thibaud-jty/awesome-super-resolution)
    7. DIV2K
    8. Flickr2K
    9. Set5
    10. Set14
    11. BSD100
    12. Urban100
    13. Manga109
    14. REDS
    15. CVPR
    16. ICCV
    17. ECCV
    18. NeurIPS
    19. OpenReview
    Show full AI answer
  • CATEGORY QUERY
    I need to compare various deep learning approaches for image super-resolution; what resources are available?
    you: #1
    AI recommended (in order):
    1. Awesome-Super-Resolution ← you
    2. Papers With Code - Super-Resolution
    3. PyTorch-Image-Super-Resolution
    4. BasicSR
    5. Real-ESRGAN
    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 ChaofWang/Awesome-Super-Resolution?
    pass
    AI named ChaofWang/Awesome-Super-Resolution explicitly

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

  • If a team adopts ChaofWang/Awesome-Super-Resolution in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ChaofWang/Awesome-Super-Resolution 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 ChaofWang/Awesome-Super-Resolution solve, and who is the primary audience?
    pass
    AI did not name ChaofWang/Awesome-Super-Resolution — 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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ChaofWang/Awesome-Super-Resolution — 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