RRepoGEO

REPOGEO REPORT · LITE

Harbinzzy/All-in-One-Image-Restoration-Survey

Default branch main · commit 6ff194c1 · scanned 6/16/2026, 3:38:24 PM

GitHub: 560 stars · 35 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Harbinzzy/All-in-One-Image-Restoration-Survey, 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 `awesome-list` to repository topics

    Why:

    CURRENT
    all-in-one-image-restoration, image-restoration, survey
    COPY-PASTE FIX
    all-in-one-image-restoration, image-restoration, survey, awesome-list
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the chosen license text (e.g., CC-BY-4.0 for content-heavy surveys or MIT for general repository structure).
  • mediumhomepage#3
    Set the repository homepage to the official paper link

    Why:

    COPY-PASTE FIX
    https://ieeexplore.ieee.org/document/11123156

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 Harbinzzy/All-in-One-Image-Restoration-Survey
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Restormer
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Restormer · recommended 1×
  2. MPRNet · recommended 1×
  3. Uformer · recommended 1×
  4. ESRGAN · recommended 1×
  5. SwinIR · recommended 1×
  • CATEGORY QUERY
    What are the current trends and evaluation methods in comprehensive image restoration?
    you: not recommended
    AI recommended (in order):
    1. Restormer
    2. MPRNet
    3. Uformer
    4. ESRGAN
    5. SwinIR
    6. HiFaceGAN
    7. DDPM
    8. SR3
    9. Palette
    10. Real-ESRGAN
    11. DCLS

    AI recommended 11 alternatives but never named Harbinzzy/All-in-One-Image-Restoration-Survey. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a survey of state-of-the-art all-in-one image restoration methods and benchmarks?
    you: not recommended
    AI recommended (in order):
    1. Papers with Code
    2. arXiv
    3. Google Scholar
    4. MMagic
    5. GitHub

    AI recommended 5 alternatives but never named Harbinzzy/All-in-One-Image-Restoration-Survey. 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 Harbinzzy/All-in-One-Image-Restoration-Survey?
    pass
    AI did not name Harbinzzy/All-in-One-Image-Restoration-Survey — 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 Harbinzzy/All-in-One-Image-Restoration-Survey in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Harbinzzy/All-in-One-Image-Restoration-Survey 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 Harbinzzy/All-in-One-Image-Restoration-Survey solve, and who is the primary audience?
    pass
    AI did not name Harbinzzy/All-in-One-Image-Restoration-Survey — 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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