RRepoGEO

REPOGEO REPORT · LITE

JosephPai/Awesome-Talking-Face

Default branch master · commit d383ea17 · scanned 5/26/2026, 7:22:19 AM

GitHub: 1,541 stars · 121 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 JosephPai/Awesome-Talking-Face, 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
    awesome-list, talking-face, face-generation, video-driven, face-reenactment, research-papers, computer-vision, deep-learning
  • highreadme#2
    Strengthen the README's opening sentence to clearly state its "awesome list" nature

    Why:

    CURRENT
    # Awesome Talking Face This is a repository for organizing papres, codes and other resources related to talking face/head.
    COPY-PASTE FIX
    # Awesome Talking Face A comprehensive, curated list of research papers, code, and resources dedicated to talking face generation and video-driven face reenactment.
  • mediumhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/JosephPai/Awesome-Talking-Face

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 JosephPai/Awesome-Talking-Face
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Awesome Talking Face Generation
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Awesome Talking Face Generation · recommended 1×
  2. Google Scholar · recommended 1×
  3. arXiv · recommended 1×
  4. Semantic Scholar · recommended 1×
  5. Papers With Code · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of research papers on talking face generation?
    you: not recommended
    AI recommended (in order):
    1. Awesome Talking Face Generation
    2. Google Scholar
    3. arXiv
    4. Semantic Scholar
    5. Papers With Code
    6. IEEE Xplore
    7. ACM Digital Library
    8. CVPR
    9. ICCV
    10. ECCV
    11. NeurIPS
    12. ICML

    AI recommended 12 alternatives but never named JosephPai/Awesome-Talking-Face. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best open-source libraries for real-time video-driven face reenactment?
    you: not recommended
    AI recommended (in order):
    1. DeepFaceLive
    2. FaceFusion
    3. First Order Motion Model for Image Animation (FOMM)
    4. SadTalker
    5. Wav2Lip
    6. OpenCV
    7. dlib
    8. MediaPipe

    AI recommended 8 alternatives but never named JosephPai/Awesome-Talking-Face. 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 JosephPai/Awesome-Talking-Face?
    pass
    AI did not name JosephPai/Awesome-Talking-Face — 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 JosephPai/Awesome-Talking-Face in production, what risks or prerequisites should they evaluate first?
    pass
    AI named JosephPai/Awesome-Talking-Face 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 JosephPai/Awesome-Talking-Face solve, and who is the primary audience?
    pass
    AI did not name JosephPai/Awesome-Talking-Face — 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?

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JosephPai/Awesome-Talking-Face — 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