RRepoGEO

REPOGEO REPORT · LITE

NVlabs/FoundationPose

Default branch main · commit a1b694b8 · scanned 5/12/2026, 12:13:18 AM

GitHub: 3,178 stars · 472 forks

AI VISIBILITY SCORE
35 /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
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 NVlabs/FoundationPose, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Add a 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    Insert a "## Key Features" section near the top of the README, for example:

## Key Features
- **Unified Foundation Model:** Seamlessly performs 6D object pose estimation and tracking.
- **Novel Object Support:** Instantly applicable to new objects without fine-tuning.
- **Zero-Shot Capability:** Works with CAD models or a few reference images, no per-object training required.
- **Strong Generalizability:** Achieved through large-scale synthetic training and advanced architectures.
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a section to the README, e.g., "## License
This project is licensed under [specify license(s) here, e.g., a custom NVIDIA license or a combination of licenses]. Please refer to the LICENSE file for full details."

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 NVlabs/FoundationPose
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CosyPose
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. CosyPose · recommended 2×
  2. OpenCV · recommended 1×
  3. COLMAP · recommended 1×
  4. Google MediaPipe Objectron · recommended 1×
  5. MegaPose · recommended 1×
  • CATEGORY QUERY
    How to perform 6D pose estimation and tracking for novel objects without extensive training?
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. COLMAP
    3. Google MediaPipe Objectron
    4. CosyPose
    5. MegaPose
    6. ArUco Markers
    7. AprilTags

    AI recommended 7 alternatives but never named NVlabs/FoundationPose. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a unified foundation model for 6D object pose and tracking using CAD models.
    you: not recommended
    AI recommended (in order):
    1. GDR-Net
    2. CosyPose
    3. BundleFusion
    4. Open3D
    5. Mask R-CNN
    6. DeepIM
    7. PoseCNN
    8. Neural Radiance Fields (NeRF)
    9. NeRF-Pose
    10. BARF

    AI recommended 10 alternatives but never named NVlabs/FoundationPose. 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 NVlabs/FoundationPose?
    pass
    AI named NVlabs/FoundationPose explicitly

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

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

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

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MARKDOWN (README)
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NVlabs/FoundationPose — 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