RRepoGEO

REPOGEO REPORT · LITE

SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods

Default branch main · commit 7a673aae · scanned 6/2/2026, 12:38:10 PM

GitHub: 712 stars · 44 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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods, 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
    diffusion-models, image-editing, computer-vision, deep-learning, awesome-list, survey, research-papers, ai-powered-image-manipulation
  • mediumreadme#2
    Clarify the repository's role as a curated list in the README's opening

    Why:

    CURRENT
    The repository is based on our survey Diffusion Model-Based Image Editing: A Survey (TPAMI 2025).
    COPY-PASTE FIX
    This repository serves as a comprehensive, curated collection of methods for diffusion model-based image editing, accompanying our survey "Diffusion Model-Based Image Editing: A Survey" (TPAMI 2025).
  • lowabout#3
    Refine the repository description for clarity

    Why:

    CURRENT
    Diffusion Model-Based Image Editing: A Survey (TPAMI 2025)
    COPY-PASTE FIX
    A curated collection of methods for Diffusion Model-Based Image Editing, accompanying our TPAMI 2025 survey.

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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods
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. Google Scholar · recommended 1×
  4. CVPR · recommended 1×
  5. ICCV · recommended 1×
  • CATEGORY QUERY
    How can I find state-of-the-art methods for AI-powered image manipulation?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Papers With Code
    3. Google Scholar
    4. CVPR
    5. ICCV
    6. ECCV
    7. NeurIPS
    8. ICLR
    9. GitHub
    10. The Batch by DeepLearning.AI
    11. Towards Data Science
    12. Synced Review
    13. Stability AI
    14. Hugging Face
    15. NVIDIA
    16. Google AI
    17. Meta AI

    AI recommended 17 alternatives but never named SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive overview of diffusion models for image editing tasks?
    you: not recommended
    AI recommended (in order):
    1. Awesome Diffusion Models GitHub Repository
    2. Hugging Face Diffusers Library
    3. Papers with Code

    AI recommended 3 alternatives but never named SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods. 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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods?
    pass
    AI did not name SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods — 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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods 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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods solve, and who is the primary audience?
    pass
    AI did not name SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods — 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 SiatMMLab/Awesome-Diffusion-Model-Based-Image-Editing-Methods. 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite