RRepoGEO

REPOGEO REPORT · LITE

junshutang/Make-It-3D

Default branch master · commit d5caefb4 · scanned 6/21/2026, 11:43:17 PM

GitHub: 1,885 stars · 137 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
35 /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
3 / 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 junshutang/Make-It-3D, 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 root of the repository with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • highhomepage#2
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    Add the project page URL (https://make-it-3d.github.io/) to the 'Homepage' field in the repository settings.
  • mediumreadme#3
    Strengthen the README's opening sentence to explicitly state the core problem solved

    Why:

    CURRENT
    # Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior (ICCV 2023)
    COPY-PASTE FIX
    # Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior (ICCV 2023)

Make-It-3D enables high-fidelity 3D model generation from just a single 2D image, leveraging diffusion models for superior realism and detail.

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 junshutang/Make-It-3D
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Luma AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Luma AI · recommended 2×
  2. Instant NGP · recommended 1×
  3. DreamFusion · recommended 1×
  4. Magic3D · recommended 1×
  5. Spline · recommended 1×
  • CATEGORY QUERY
    How can I generate detailed 3D models from just one input photograph?
    you: not recommended
    AI recommended (in order):
    1. Luma AI
    2. Instant NGP
    3. DreamFusion
    4. Magic3D
    5. Spline
    6. Kiri Engine
    7. Alpha3D
    8. Meshy

    AI recommended 8 alternatives but never named junshutang/Make-It-3D. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools use diffusion models to create realistic 3D objects from a single image?
    you: not recommended
    AI recommended (in order):
    1. Luma AI
    2. InstantMesh
    3. DreamGaussian
    4. Stable Diffusion
    5. Midjourney
    6. NeRFstudio
    7. Instant-NGP
    8. Wonder Dynamics
    9. Meshy.ai

    AI recommended 9 alternatives but never named junshutang/Make-It-3D. 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 junshutang/Make-It-3D?
    pass
    AI named junshutang/Make-It-3D explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts junshutang/Make-It-3D in production, what risks or prerequisites should they evaluate first?
    pass
    AI named junshutang/Make-It-3D 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 junshutang/Make-It-3D solve, and who is the primary audience?
    pass
    AI named junshutang/Make-It-3D explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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junshutang/Make-It-3D — 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