RRepoGEO

REPOGEO REPORT · LITE

youquanl/Segment-Any-Point-Cloud

Default branch main · commit d7f2618f · scanned 6/12/2026, 3:13:28 AM

GitHub: 639 stars · 31 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 youquanl/Segment-Any-Point-Cloud, 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
    3d-computer-vision, point-cloud-segmentation, foundation-models, vision-transformers, neurips2023, deep-learning, computer-vision, segment-anything
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root directory of the repository, specifying the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • highreadme#3
    Clarify the unique value proposition in the README's opening

    Why:

    CURRENT
    <p align="right">English | <a href="docs/README_CN.md">简体中文</a></p>

<p align="center">
  
  
  <h3 align="center"><strong>Segment Any Point Cloud Sequences by Distilling Vision Foundation Models</strong></h3>
    COPY-PASTE FIX
    # SEAL: Segment Any Point Cloud Sequences

This repository presents SEAL, a novel framework for segmenting arbitrary objects or regions within dynamic 3D point cloud sequences. Inspired by 2D vision foundation models like SAM, SEAL enables flexible, prompt-based segmentation in 3D by distilling knowledge from powerful vision models.

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 youquanl/Segment-Any-Point-Cloud
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Open3D
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Open3D · recommended 2×
  2. OpenPCDet · recommended 1×
  3. MinkowskiEngine · recommended 1×
  4. PointNet++ · recommended 1×
  5. Mask3D · recommended 1×
  • CATEGORY QUERY
    How can I accurately segment objects within dynamic 3D point cloud sequences?
    you: not recommended
    AI recommended (in order):
    1. OpenPCDet
    2. MinkowskiEngine
    3. PointNet++
    4. Mask3D
    5. Panoptic-DeepLab
    6. Open3D
    7. PointTrack

    AI recommended 7 alternatives but never named youquanl/Segment-Any-Point-Cloud. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help apply vision foundation models for robust point cloud segmentation?
    you: not recommended
    AI recommended (in order):
    1. PyTorch3D
    2. Open3D
    3. MMSegmentation3D
    4. TensorFlow
    5. Hugging Face Transformers
    6. Pointcept

    AI recommended 6 alternatives but never named youquanl/Segment-Any-Point-Cloud. 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 youquanl/Segment-Any-Point-Cloud?
    pass
    AI did not name youquanl/Segment-Any-Point-Cloud — 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 youquanl/Segment-Any-Point-Cloud in production, what risks or prerequisites should they evaluate first?
    pass
    AI named youquanl/Segment-Any-Point-Cloud 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 youquanl/Segment-Any-Point-Cloud solve, and who is the primary audience?
    pass
    AI named youquanl/Segment-Any-Point-Cloud explicitly

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

Embed your GEO score

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youquanl/Segment-Any-Point-Cloud — 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