RRepoGEO

REPOGEO REPORT · LITE

ChenHsing/Awesome-Video-Diffusion-Models

Default branch main · commit 5975e31b · scanned 5/26/2026, 11:12:50 PM

GitHub: 2,293 stars · 113 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 ChenHsing/Awesome-Video-Diffusion-Models, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the Creative Commons Attribution 4.0 International License (CC-BY-4.0), suitable for a curated list/survey.
  • highhomepage#2
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    Set the repository homepage URL in the repository settings to `https://arxiv.org/abs/2310.10647` to link directly to the published survey paper.
  • mediumreadme#3
    Refine the README's main title to emphasize its 'awesome list' nature

    Why:

    CURRENT
    # A Survey on Video Diffusion Models
    COPY-PASTE FIX
    # Awesome Video Diffusion Models: A Comprehensive Survey and Curated List of Resources

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 ChenHsing/Awesome-Video-Diffusion-Models
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Video Diffusion (SVD)
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Video Diffusion (SVD) · recommended 2×
  2. Papers With Code · recommended 1×
  3. Hugging Face Models · recommended 1×
  4. AnimateDiff · recommended 1×
  5. GitHub Repositories · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive overview of current video generation diffusion models?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. Hugging Face Models
    3. Stable Video Diffusion (SVD)
    4. AnimateDiff
    5. GitHub Repositories
    6. arXiv
    7. Phenaki
    8. Imagen Video
    9. Make-A-Video
    10. Google AI Blog
    11. Meta AI Blog
    12. OpenAI Blog

    AI recommended 12 alternatives but never named ChenHsing/Awesome-Video-Diffusion-Models. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading text-to-video diffusion models available for research or development?
    you: not recommended
    AI recommended (in order):
    1. Stable Video Diffusion (SVD)
    2. Pika Labs (Pika 1.0)
    3. RunwayML Gen-2
    4. Google Lumiere
    5. Meta Make-A-Video
    6. Phenaki (Google)

    AI recommended 6 alternatives but never named ChenHsing/Awesome-Video-Diffusion-Models. 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 ChenHsing/Awesome-Video-Diffusion-Models?
    pass
    AI did not name ChenHsing/Awesome-Video-Diffusion-Models — 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 ChenHsing/Awesome-Video-Diffusion-Models in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ChenHsing/Awesome-Video-Diffusion-Models 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 ChenHsing/Awesome-Video-Diffusion-Models solve, and who is the primary audience?
    pass
    AI did not name ChenHsing/Awesome-Video-Diffusion-Models — 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 ChenHsing/Awesome-Video-Diffusion-Models. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/ChenHsing/Awesome-Video-Diffusion-Models.svg)](https://repogeo.com/en/r/ChenHsing/Awesome-Video-Diffusion-Models)
HTML
<a href="https://repogeo.com/en/r/ChenHsing/Awesome-Video-Diffusion-Models"><img src="https://repogeo.com/badge/ChenHsing/Awesome-Video-Diffusion-Models.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

ChenHsing/Awesome-Video-Diffusion-Models — 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