REPOGEO REPORT · LITE

chaofengc/Awesome-Image-Quality-Assessment

Default branch main · commit 3ce45f20 · scanned 5/26/2026, 4:28:14 AM

GitHub: 1,514 stars · 86 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 chaofengc/Awesome-Image-Quality-Assessment, 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

Explicitly state the 'awesome list' nature in the README's opening sentence

Why:

CURRENT

A comprehensive collection of IQA papers, datasets and codes.

COPY-PASTE FIX

This repository is an *awesome list* providing a comprehensive collection of IQA papers, datasets, and codes.

highhomepage#2
Add a homepage URL to the repository settings
Why:
COPY-PASTE FIX
```
https://github.com/chaofengc/Awesome-Image-Quality-Assessment
```

mediumtopics#3

Expand topics to include broader research and computer vision terms

Why:

CURRENT

awesome, awesome-list, blind-image-quality-assessment, image-quality-assessment, iqa, iqa-dataset

COPY-PASTE FIX

awesome, awesome-list, blind-image-quality-assessment, image-quality-assessment, iqa, iqa-dataset, computer-vision, research-papers

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 chaofengc/Awesome-Image-Quality-Assessment

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

IEEE Xplore Digital Library

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

IEEE Xplore Digital Library · recommended 1×
ACM Digital Library · recommended 1×
Google Scholar · recommended 1×
arXiv · recommended 1×
LIVE Image Quality Assessment Database · recommended 1×

CATEGORY QUERY
Where can I find a comprehensive collection of research papers on image quality assessment?
you: not recommended
AI recommended (in order):
1. IEEE Xplore Digital Library
2. ACM Digital Library
3. Google Scholar
4. arXiv
5. LIVE Image Quality Assessment Database
6. CSIQ database
7. ResearchGate
8. Academia.edu
9. SpringerLink
10. ScienceDirect
AI recommended 10 alternatives but never named chaofengc/Awesome-Image-Quality-Assessment. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the best resources for blind image quality assessment datasets and PyTorch implementations?
you: not recommended
AI recommended (in order):
1. LIVE In the Wild Image Quality Challenge Database (LIVE-itW)
2. KonIQ-10k
3. CSIQ (Categorical Subjective Image Quality)
4. TID2013 (Tampere Image Database 2013)
5. LIVE (Laboratory for Image and Video Engineering) Image Quality Assessment Database
6. IQA-PyTorch (meowuu/IQA-PyTorch)
7. PyTorch-IQA (idearib/PyTorch-IQA)
8. TorchIQA (pytorch-iqa/TorchIQA)
9. BRISQUE
AI recommended 9 alternatives but never named chaofengc/Awesome-Image-Quality-Assessment. 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 chaofengc/Awesome-Image-Quality-Assessment?
pass
AI did not name chaofengc/Awesome-Image-Quality-Assessment — 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 chaofengc/Awesome-Image-Quality-Assessment in production, what risks or prerequisites should they evaluate first?
pass
AI named chaofengc/Awesome-Image-Quality-Assessment 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 chaofengc/Awesome-Image-Quality-Assessment solve, and who is the primary audience?
pass
AI did not name chaofengc/Awesome-Image-Quality-Assessment — 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 chaofengc/Awesome-Image-Quality-Assessment. 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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HTML

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chaofengc/Awesome-Image-Quality-Assessment — 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