RRepoGEO

REPOGEO REPORT · LITE

hovsg/HOV-SG

Default branch main · commit d6e65a53 · scanned 7/1/2026, 4:53:13 PM

GitHub: 502 stars · 36 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 hovsg/HOV-SG, 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 the full project name and domain in the README's opening

    Why:

    CURRENT
    # HOV-SG
    COPY-PASTE FIX
    # HOV-SG: Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation
  • mediumreadme#2
    Add a concise problem/solution statement to the README introduction

    Why:

    CURRENT
    This repository is the official implementation of the paper:

> **Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation**
    COPY-PASTE FIX
    This repository provides the official implementation of HOV-SG, a novel framework designed to enable robots to navigate complex 3D environments using natural language commands by constructing hierarchical, open-vocabulary 3D scene graphs. It offers a comprehensive solution for language-grounded robot navigation in complex 3D environments.

This work is based on the paper:

> **Hierarchical Open-Vocabulary 3D Scene Graphs for Language-Grounded Robot Navigation**
  • lowtopics#3
    Add 'robotics' to the repository topics

    Why:

    CURRENT
    3d-scene-graph, natural-language-understanding, open-vocabulary, robot-navigation, robot-planning
    COPY-PASTE FIX
    3d-scene-graph, natural-language-understanding, open-vocabulary, robot-navigation, robot-planning, robotics

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 hovsg/HOV-SG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ROS
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ROS · recommended 2×
  2. MoveIt! · recommended 1×
  3. PCL - Point Cloud Library · recommended 1×
  4. OpenCV · recommended 1×
  5. OpenAI CLIP · recommended 1×
  • CATEGORY QUERY
    How can robots navigate complex 3D environments using natural language commands and scene graphs?
    you: not recommended
    AI recommended (in order):
    1. ROS
    2. MoveIt!
    3. PCL - Point Cloud Library
    4. OpenCV
    5. OpenAI CLIP
    6. DALL-E 2
    7. GPT-4V
    8. PyTorch Geometric (PyG)
    9. Deep Graph Library (DGL)
    10. Stanford Scene Graph Parser
    11. Visual Genome
    12. Habitat-ROS
    13. AI2-THOR
    14. Gazebo
    15. Webots

    AI recommended 15 alternatives but never named hovsg/HOV-SG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a framework for open-vocabulary 3D scene graph generation to enable advanced robot planning.
    you: not recommended
    AI recommended (in order):
    1. OpenSceneGraph
    2. ROS
    3. tf
    4. moveit_ros_planning
    5. PyTorch3D
    6. OmniGraph
    7. PyTorch Geometric
    8. Deep Graph Library
    9. Open3D
    10. MinkowskiEngine
    11. SceneGraphFusion

    AI recommended 11 alternatives but never named hovsg/HOV-SG. 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 hovsg/HOV-SG?
    pass
    AI named hovsg/HOV-SG explicitly

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

  • If a team adopts hovsg/HOV-SG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hovsg/HOV-SG 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 hovsg/HOV-SG solve, and who is the primary audience?
    pass
    AI named hovsg/HOV-SG 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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MARKDOWN (README)
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hovsg/HOV-SG — 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