RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/NSVF

Default branch main · commit ecd08088 · scanned 6/6/2026, 2:57:58 PM

GitHub: 818 stars · 92 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 facebookresearch/NSVF, 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
    neural-rendering, nerf, voxel-fields, view-synthesis, computer-vision, graphics, 3d-reconstruction
  • mediumhomepage#2
    Add the official project page as the repository homepage

    Why:

    COPY-PASTE FIX
    https://[YOUR_PROJECT_PAGE_URL]
  • mediumreadme#3
    Reposition the core value proposition in the README's opening

    Why:

    CURRENT
    Photo-realistic free-viewpoint rendering of real-world scenes using classical computer graphics techniques is a challenging problem because it requires the difficult step of capturing detailed appearance and geometry models.
    COPY-PASTE FIX
    Neural Sparse Voxel Fields (NSVF) is a novel neural scene representation designed for fast and high-quality free-viewpoint rendering, addressing the limitations of existing approaches in photo-realistic scene reconstruction.

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 facebookresearch/NSVF
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mip-NeRF 360
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mip-NeRF 360 · recommended 2×
  2. K-Planes · recommended 2×
  3. 3D Gaussian Splatting · recommended 2×
  4. NeRF-W · recommended 2×
  5. NeRF · recommended 1×
  • CATEGORY QUERY
    How to achieve high-quality photo-realistic free-viewpoint rendering from 2D images?
    you: not recommended
    AI recommended (in order):
    1. NeRF
    2. Mip-NeRF 360
    3. Instant-NGP
    4. K-Planes
    5. Zip-NeRF
    6. 3D Gaussian Splatting
    7. Agisoft Metashape
    8. RealityCapture
    9. Meshroom
    10. NeRF-W
    11. Stereo Magnification
    12. Stanford Light Field Archive
    13. Lytro cameras

    AI recommended 13 alternatives but never named facebookresearch/NSVF. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are fast neural rendering techniques for efficient scene representation and view synthesis?
    you: not recommended
    AI recommended (in order):
    1. 3D Gaussian Splatting
    2. Instant NGP
    3. Plenoxels
    4. TensoRF
    5. K-Planes
    6. Mip-NeRF 360
    7. NeRF-W

    AI recommended 7 alternatives but never named facebookresearch/NSVF. 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 facebookresearch/NSVF?
    pass
    AI named facebookresearch/NSVF explicitly

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

  • If a team adopts facebookresearch/NSVF in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/NSVF 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 facebookresearch/NSVF solve, and who is the primary audience?
    pass
    AI did not name facebookresearch/NSVF — 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 facebookresearch/NSVF. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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facebookresearch/NSVF — 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