RRepoGEO

REPOGEO REPORT · LITE

YunjinPark/awesome_talking_face_generation

Default branch main · commit e5f656c7 · scanned 6/10/2026, 4:02:40 AM

GitHub: 840 stars · 70 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 YunjinPark/awesome_talking_face_generation, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 to clarify it's an awesome list of research

    Why:

    CURRENT
    # Awesome talking face generation
    COPY-PASTE FIX
    # Awesome Talking Face Generation: A Curated List of Papers & Codes
  • highabout#2
    Add a concise About description

    Why:

    COPY-PASTE FIX
    A comprehensive, curated list of research papers, code, and datasets for talking face generation, covering recent advancements and key methodologies.

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 YunjinPark/awesome_talking_face_generation
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepMotion
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepMotion · recommended 2×
  2. SadTalker · recommended 1×
  3. Wav2Lip · recommended 1×
  4. First Order Motion Model for Image Animation (FOMM) · recommended 1×
  5. MakeItTalk · recommended 1×
  • CATEGORY QUERY
    What are the best open-source tools for generating realistic talking head videos?
    you: not recommended
    AI recommended (in order):
    1. SadTalker
    2. Wav2Lip
    3. DeepMotion
    4. First Order Motion Model for Image Animation (FOMM)
    5. MakeItTalk

    AI recommended 5 alternatives but never named YunjinPark/awesome_talking_face_generation. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I synthesize expressive 3D talking avatars from speech with AI?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Audio2Face
    2. Meta AI's Codec Avatars
    3. VASA-1
    4. DeepMotion
    5. Synthesia
    6. Ready Player Me
    7. Unreal Engine MetaHumans
    8. Apple's Live Link Face
    9. Blender

    AI recommended 9 alternatives but never named YunjinPark/awesome_talking_face_generation. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 YunjinPark/awesome_talking_face_generation?
    pass
    AI did not name YunjinPark/awesome_talking_face_generation — 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 YunjinPark/awesome_talking_face_generation in production, what risks or prerequisites should they evaluate first?
    pass
    AI named YunjinPark/awesome_talking_face_generation 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 YunjinPark/awesome_talking_face_generation solve, and who is the primary audience?
    pass
    AI did not name YunjinPark/awesome_talking_face_generation — 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

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YunjinPark/awesome_talking_face_generation — 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