RRepoGEO

REPOGEO REPORT · LITE

PruneTruong/DenseMatching

Default branch main · commit b054fe9f · scanned 6/2/2026, 11:38:04 PM

GitHub: 753 stars · 88 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 PruneTruong/DenseMatching, 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
  • highreadme#1
    Reposition the README's H1 and opening paragraph to emphasize its unified library approach

    Why:

    CURRENT
    # Dense Matching

A general dense matching library based on PyTorch.
    COPY-PASTE FIX
    # Dense Matching: A Unified PyTorch Library for State-of-the-Art Algorithms

This library provides a comprehensive, unified PyTorch framework for implementing, training, and evaluating state-of-the-art dense feature matching algorithms across geometric, optical flow, and semantic matching tasks.
  • mediumabout#2
    Update the repository's 'About' description to be more specific and highlight its unified nature

    Why:

    CURRENT
    Dense matching library based on PyTorch
    COPY-PASTE FIX
    A unified PyTorch library for implementing, training, and evaluating state-of-the-art dense feature matching algorithms.

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 PruneTruong/DenseMatching
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SuperGlue
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. SuperGlue · recommended 1×
  2. LoFTR · recommended 1×
  3. DINO · recommended 1×
  4. PatchMatch · recommended 1×
  5. kornia · recommended 1×
  • CATEGORY QUERY
    What are the best PyTorch libraries for dense feature matching in computer vision tasks?
    you: not recommended
    AI recommended (in order):
    1. SuperGlue
    2. LoFTR
    3. DINO
    4. PatchMatch
    5. kornia

    AI recommended 5 alternatives but never named PruneTruong/DenseMatching. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python library to implement and evaluate geometric matching networks with PyTorch.
    you: not recommended
    AI recommended (in order):
    1. PyTorch Geometric (PyG)
    2. DeepGraphLibrary (DGL)
    3. Open3D
    4. Kaolin
    5. torch-scatter / torch-sparse

    AI recommended 5 alternatives but never named PruneTruong/DenseMatching. 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 PruneTruong/DenseMatching?
    pass
    AI did not name PruneTruong/DenseMatching — 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 PruneTruong/DenseMatching in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PruneTruong/DenseMatching 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 PruneTruong/DenseMatching solve, and who is the primary audience?
    pass
    AI named PruneTruong/DenseMatching explicitly

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

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PruneTruong/DenseMatching — 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