RRepoGEO

REPOGEO REPORT · LITE

PRIS-CV/DemoFusion

Default branch main · commit 6aa190a8 · scanned 5/11/2026, 6:47:53 PM

GitHub: 2,044 stars · 216 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 PRIS-CV/DemoFusion, 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
    Clarify the GitHub 'About' description to emphasize generative AI

    Why:

    CURRENT
    Let us democratise high-resolution generation! (CVPR 2024)
    COPY-PASTE FIX
    Democratizing high-resolution image *generation* by extending existing Latent Diffusion Models (LDMs) for accessible, high-fidelity outputs on limited hardware. (CVPR 2024)
  • mediumtopics#2
    Add more specific topics to differentiate from pure upscaling

    Why:

    CURRENT
    aigc, genai, high-resolution, low-resource, stable-diffusion
    COPY-PASTE FIX
    aigc, genai, high-resolution, low-resource, stable-diffusion, diffusion-models, latent-diffusion, image-generation-framework
  • mediumreadme#3
    Strengthen the README's opening sentence to highlight the framework's approach

    Why:

    CURRENT
    Code release for "DemoFusion: Democratising High-Resolution Image Generation With No 💰"
    COPY-PASTE FIX
    DemoFusion is a novel framework that democratizes high-resolution image generation by seamlessly extending open-source Latent Diffusion Models (LDMs) with Progressive Upscaling, Skip Residual, and Dilated Sampling, making high-fidelity outputs accessible on limited hardware.

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 PRIS-CV/DemoFusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ESRGAN
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ESRGAN · recommended 2×
  2. SwinIR · recommended 2×
  3. Automatic1111 Stable Diffusion WebUI · recommended 1×
  4. ControlNet · recommended 1×
  5. LDSR · recommended 1×
  • CATEGORY QUERY
    How can I generate high-resolution images using existing diffusion models on limited hardware?
    you: not recommended
    AI recommended (in order):
    1. Automatic1111 Stable Diffusion WebUI
    2. ControlNet
    3. ESRGAN
    4. SwinIR
    5. LDSR
    6. SDXL Refiner
    7. ComfyUI
    8. InvokeAI
    9. Diffusers Library
    10. RunDiffusion
    11. ThinkDiffusion
    12. Vast.ai

    AI recommended 12 alternatives but never named PRIS-CV/DemoFusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for open-source frameworks to upscale generative AI images without significant capital investment.
    you: not recommended
    AI recommended (in order):
    1. Upscayl
    2. Real-ESRGAN
    3. SwinIR
    4. Waifu2x
    5. ESRGAN
    6. Image Super-Resolution (ISR)

    AI recommended 6 alternatives but never named PRIS-CV/DemoFusion. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 PRIS-CV/DemoFusion?
    pass
    AI named PRIS-CV/DemoFusion explicitly

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

  • If a team adopts PRIS-CV/DemoFusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PRIS-CV/DemoFusion 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 PRIS-CV/DemoFusion solve, and who is the primary audience?
    pass
    AI named PRIS-CV/DemoFusion explicitly

    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 PRIS-CV/DemoFusion. 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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PRIS-CV/DemoFusion — RepoGEO report