RRepoGEO

REPOGEO REPORT · LITE

VAST-AI-Research/TriplaneGaussian

Default branch main · commit e6a49391 · scanned 5/30/2026, 5:07:39 PM

GitHub: 922 stars · 68 forks

AI VISIBILITY SCORE
28 /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
2 / 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 VAST-AI-Research/TriplaneGaussian, 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:

    CURRENT
    (none)
    COPY-PASTE FIX
    ["3d-reconstruction", "gaussian-splatting", "single-view-3d", "generative-ai", "computer-vision", "deep-learning", "transformers", "3d-model-generation"]
  • highreadme#2
    Reposition the README's main heading (H1) to be more direct and benefit-oriented

    Why:

    CURRENT
    # Triplane Meets Gaussian Splatting:<br> Fast and Generalizable Single-View 3D Reconstruction with Transformers
    COPY-PASTE FIX
    # TriplaneGaussian: Fast, High-Quality 3D Model Generation from a Single Image
  • mediumabout#3
    Update the repository's 'About' description for clarity and benefit-orientation

    Why:

    CURRENT
    TriplaneGaussian: A new hybrid representation for single-view 3D reconstruction.
    COPY-PASTE FIX
    TriplaneGaussian: Fast, high-quality 3D model generation from a single image using a novel hybrid representation.

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 VAST-AI-Research/TriplaneGaussian
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Luma AI (Genie 1.0)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Luma AI (Genie 1.0) · recommended 1×
  2. NVlabs/instant-ngp · recommended 1×
  3. CSM (Consistent Single-Image 3D Mesh Reconstruction) · recommended 1×
  4. google-research/dreamfusion · recommended 1×
  5. Spline · recommended 1×
  • CATEGORY QUERY
    Need a tool for fast 3D model generation from a single input image.
    you: not recommended
    AI recommended (in order):
    1. Luma AI (Genie 1.0)
    2. Instant NGP (Neural Graphics Primitives) (NVlabs/instant-ngp)
    3. CSM (Consistent Single-Image 3D Mesh Reconstruction)
    4. DreamFusion (Google Research) (google-research/dreamfusion)
    5. Spline

    AI recommended 5 alternatives but never named VAST-AI-Research/TriplaneGaussian. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking methods for high-quality 3D reconstruction using hybrid explicit-implicit representations.
    you: not recommended
    AI recommended (in order):
    1. Neuralangelo
    2. Instant NGP
    3. NeuS
    4. DreamFusion
    5. Magic3D
    6. NeRF-W
    7. Plenoxels
    8. PlenOctrees
    9. 3D Gaussian Splatting

    AI recommended 9 alternatives but never named VAST-AI-Research/TriplaneGaussian. 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 VAST-AI-Research/TriplaneGaussian?
    pass
    AI named VAST-AI-Research/TriplaneGaussian explicitly

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

  • If a team adopts VAST-AI-Research/TriplaneGaussian in production, what risks or prerequisites should they evaluate first?
    pass
    AI named VAST-AI-Research/TriplaneGaussian 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 VAST-AI-Research/TriplaneGaussian solve, and who is the primary audience?
    pass
    AI did not name VAST-AI-Research/TriplaneGaussian — 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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VAST-AI-Research/TriplaneGaussian — 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