RRepoGEO

REPOGEO REPORT · LITE

pengsongyou/openscene

Default branch main · commit 0f369bc7 · scanned 6/11/2026, 4:39:51 AM

GitHub: 828 stars · 68 forks

AI VISIBILITY SCORE
73 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
2 pass · 0 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 pengsongyou/openscene, 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
    Clarify README's opening sentence to highlight zero-shot segmentation

    Why:

    CURRENT
    OpenScene is a zero-shot approach to perform a series of novel 3D scene understanding tasks using open-vocabulary queries.
    COPY-PASTE FIX
    OpenScene is a zero-shot approach for open-vocabulary 3D scene understanding, specifically enabling semantic segmentation of point clouds with arbitrary labels.
  • mediumabout#2
    Update repository description to be more specific about capabilities

    Why:

    CURRENT
    [CVPR'23] OpenScene: 3D Scene Understanding with Open Vocabularies
    COPY-PASTE FIX
    [CVPR'23] OpenScene: Zero-shot, open-vocabulary 3D scene understanding, including point cloud segmentation.
  • lowtopics#3
    Add 'zero-shot' and 'open-vocabulary' to repository topics

    Why:

    CURRENT
    3d-scene-understanding, clip, cvpr2023, llm, matterport3d, nuscenes, point-cloud-segmentation, point-clouds, scannet, semantic-segmentation
    COPY-PASTE FIX
    3d-scene-understanding, clip, cvpr2023, llm, matterport3d, nuscenes, open-vocabulary, point-cloud-segmentation, point-clouds, scannet, semantic-segmentation, zero-shot

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
1 / 2
50% of queries surface pengsongyou/openscene
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
PointCLIP
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PointCLIP · recommended 2×
  2. MaskCLIP · recommended 2×
  3. CLIP · recommended 1×
  4. CLIP-NeRF · recommended 1×
  5. LERF · recommended 1×
  • CATEGORY QUERY
    How to perform 3D scene understanding using open-vocabulary queries for novel objects?
    you: #1
    AI recommended (in order):
    1. OpenScene ← you
    2. CLIP
    3. PointCLIP
    4. CLIP-NeRF
    5. LERF
    6. OV-3D
    7. Grounding DINO
    8. OWL-ViT
    9. MaskCLIP
    10. Segment Anything Model (SAM)
    11. L-Seg
    12. 3D-VAC
    Show full AI answer
  • CATEGORY QUERY
    Looking for a zero-shot approach to segment 3D point clouds with arbitrary semantic labels.
    you: not recommended
    AI recommended (in order):
    1. OpenSeg
    2. PointCLIP
    3. CLIP2Scene
    4. LSEG
    5. MaskCLIP
    6. GroupCLIP
    7. Point-BERT

    AI recommended 7 alternatives but never named pengsongyou/openscene. 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 pengsongyou/openscene?
    pass
    AI named pengsongyou/openscene explicitly

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

  • If a team adopts pengsongyou/openscene in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pengsongyou/openscene 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 pengsongyou/openscene solve, and who is the primary audience?
    pass
    AI named pengsongyou/openscene explicitly

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

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pengsongyou/openscene — 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