RRepoGEO

REPOGEO REPORT · LITE

EricGuo5513/momask-codes

Default branch main · commit 94a6636c · scanned 5/27/2026, 7:48:15 PM

GitHub: 1,282 stars · 108 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 EricGuo5513/momask-codes, 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
    Add a concise, keyword-rich introductory paragraph to the README

    Why:

    CURRENT
    The README starts with `# MoMask: Generative Masked Modeling of 3D Human Motions (CVPR 2024)` followed by links and news.
    COPY-PASTE FIX
    Insert a paragraph after the main title and links: "MoMask is the official implementation of 'Generative Masked Modeling of 3D Human Motions,' a CVPR 2024 paper. This framework introduces a novel approach for synthesizing realistic 3D human motion, including text-to-motion generation, motion inpainting, and motion editing, making it a powerful tool for researchers and developers in computer vision and graphics."
  • mediumreadme#2
    Emphasize MoMask's unique 'Generative Masked Modeling' approach and its benefits within the introduction

    Why:

    CURRENT
    The current README title is `# MoMask: Generative Masked Modeling of 3D Human Motions (CVPR 2024)`. The unique approach is stated but not elaborated on as a differentiator in the immediate context.
    COPY-PASTE FIX
    Modify the introductory paragraph (from Action 1) to explicitly highlight the unique aspect: "MoMask is the official implementation of 'Generative Masked Modeling of 3D Human Motions,' a CVPR 2024 paper. This framework introduces a novel approach for synthesizing realistic 3D human motion. **Leveraging generative masked modeling, MoMask achieves robust and flexible 3D human motion synthesis, enabling diverse applications from text-to-motion generation to complex motion editing and inpainting.** It is a powerful tool for researchers and developers in computer vision and graphics."
  • mediumreadme#3
    Add a 'Key Features' or 'Capabilities' section to the README

    Why:

    CURRENT
    The README excerpt does not contain a dedicated 'Features' or 'Capabilities' section.
    COPY-PASTE FIX
    Add a new section, e.g., `## Key Features` or `## Capabilities`, with bullet points summarizing what MoMask can do, such as:
    ```
    ## Key Features
    - **Generative Masked Modeling:** A novel approach for robust and flexible 3D human motion synthesis.
    - **Text-to-Motion Generation:** Create realistic 3D human motion sequences from natural language descriptions.
    - **Motion Inpainting & Editing:** Capabilities for filling missing motion data and modifying existing sequences.
    - **Research Implementation:** Official code for the CVPR 2024 paper, ideal for academic and development use.
    - **Accessible Demos:** Easily try MoMask with available HuggingFace and Colab demos.
    ```

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 EricGuo5513/momask-codes
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MDM
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. MDM · recommended 1×
  2. MLD · recommended 1×
  3. T2M-GPT · recommended 1×
  4. TEMOS · recommended 1×
  5. DeepMotion · recommended 1×
  • CATEGORY QUERY
    How to generate realistic 3D human motion sequences from natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. MDM
    2. MLD
    3. T2M-GPT
    4. TEMOS
    5. DeepMotion
    6. Euphoria
    7. AMASS
    8. BABEL

    AI recommended 8 alternatives but never named EricGuo5513/momask-codes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best generative models for synthesizing 3D character animations from text?
    you: not recommended
    AI recommended (in order):
    1. Motion Diffusion Model (MDM)
    2. T2M-GPT (Text-to-Motion GPT)
    3. FACT (Fast and Accurate Character Animation from Text)
    4. MotionCLIP
    5. ControlNet
    6. DreamFusion
    7. Magic3D
    8. Phenaki
    9. Make-A-Video

    AI recommended 9 alternatives but never named EricGuo5513/momask-codes. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 EricGuo5513/momask-codes?
    pass
    AI did not name EricGuo5513/momask-codes — 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 EricGuo5513/momask-codes in production, what risks or prerequisites should they evaluate first?
    pass
    AI named EricGuo5513/momask-codes 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 EricGuo5513/momask-codes solve, and who is the primary audience?
    pass
    AI did not name EricGuo5513/momask-codes — 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 EricGuo5513/momask-codes. 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/EricGuo5513/momask-codes.svg)](https://repogeo.com/en/r/EricGuo5513/momask-codes)
HTML
<a href="https://repogeo.com/en/r/EricGuo5513/momask-codes"><img src="https://repogeo.com/badge/EricGuo5513/momask-codes.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

EricGuo5513/momask-codes — 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