REPOGEO REPORT · LITE

lixinustc/Awesome-diffusion-model-for-image-processing

Default branch main · commit 10215fcc · scanned 6/3/2026, 4:07:35 PM

GitHub: 947 stars · 68 forks

AI VISIBILITY SCORE

15 /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

0 / 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 lixinustc/Awesome-diffusion-model-for-image-processing, 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

highreadme#1

Reposition the README's opening to explicitly state it's an 'Awesome List' or 'Curated Survey'

Why:

CURRENT

Purpose: We aim to provide a summary of diffusion model-based image processing, including restoration, enhancement, coding, and quality assessment. More papers will be summarized.

COPY-PASTE FIX

This repository serves as an **Awesome List** and **curated survey** of diffusion model-based image processing papers, covering restoration, enhancement, coding, and quality assessment. It aims to provide a comprehensive summary of the latest research in this rapidly evolving field.

mediumtopics#2
Add specific topics that clearly indicate it's a list or survey of papers
Why:
CURRENT
```
["diffusion-models", "image-processing"]
```
COPY-PASTE FIX
```
["diffusion-models", "image-processing", "awesome-list", "literature-review"]
```
lowhomepage#3
Add a homepage link to the associated arXiv paper
Why:
COPY-PASTE FIX
```
https://arxiv.org/pdf/2308.09388v1.pdf
```

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 lixinustc/Awesome-diffusion-model-for-image-processing

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Hugging Face Diffusers Library

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Hugging Face Diffusers Library · recommended 1×
Stable Diffusion · recommended 1×
DDPM · recommended 1×
ControlNet · recommended 1×
latent diffusion models (LDMs) · recommended 1×

CATEGORY QUERY
How can I apply diffusion models for various image restoration and enhancement tasks?
you: not recommended
AI recommended (in order):
1. Hugging Face Diffusers Library
2. Stable Diffusion
3. DDPM
4. ControlNet
5. latent diffusion models (LDMs)
6. SwinIR
7. Real-ESRGAN
8. InstructPix2Pix
9. DALL-E 2
10. Midjourney
AI recommended 10 alternatives but never named lixinustc/Awesome-diffusion-model-for-image-processing. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Where can I find a comprehensive summary of diffusion models applied to image processing?
you: not recommended
AI recommended (in order):
1. Hugging Face Diffusers Library (huggingface/diffusers)
AI recommended 1 alternative but never named lixinustc/Awesome-diffusion-model-for-image-processing. 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 lixinustc/Awesome-diffusion-model-for-image-processing?
pass
AI did not name lixinustc/Awesome-diffusion-model-for-image-processing — 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 lixinustc/Awesome-diffusion-model-for-image-processing in production, what risks or prerequisites should they evaluate first?
pass
AI did not name lixinustc/Awesome-diffusion-model-for-image-processing — 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?
In one sentence, what problem does the repo lixinustc/Awesome-diffusion-model-for-image-processing solve, and who is the primary audience?
pass
AI did not name lixinustc/Awesome-diffusion-model-for-image-processing — 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 lixinustc/Awesome-diffusion-model-for-image-processing. 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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Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite