RRepoGEO

REPOGEO REPORT · LITE

amusi/ECCV2026-Papers-with-Code

Default branch master · commit b3864f2e · scanned 6/26/2026, 4:43:26 AM

GitHub: 2,275 stars · 272 forks

AI VISIBILITY SCORE
22 /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
1 / 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 amusi/ECCV2026-Papers-with-Code, 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
    Reposition the README H1 to reflect the repository's primary focus on ECCV 2026

    Why:

    CURRENT
    # ECCV 2024 论文和开源项目合集(Papers with Code)
    COPY-PASTE FIX
    # ECCV 2026 论文和开源项目合集(Papers with Code) - 包含往年ECCV精选
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root. For a collection of links and metadata, consider a permissive license like MIT or CC-BY-4.0 for the repository's content (excluding linked external works).
  • mediumtopics#3
    Add topics that explicitly describe the repository as a 'papers with code' collection

    Why:

    CURRENT
    computer-vision, deep-learning, eccv, eccv-2020, eccv2020, eccv2022, eccv2024, eccv2026, image-classification, image-segmentation, neural-network, object-detection
    COPY-PASTE FIX
    computer-vision, deep-learning, eccv, eccv-2020, eccv2020, eccv2022, eccv2024, eccv2026, image-classification, image-segmentation, neural-network, object-detection, papers-with-code, research-papers, conference-papers, computer-vision-papers

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 amusi/ECCV2026-Papers-with-Code
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 2×
  2. arXiv · recommended 2×
  3. GitHub · recommended 2×
  4. CVPR · recommended 1×
  5. ICCV · recommended 1×
  • CATEGORY QUERY
    Where can I find recent computer vision research papers with available code implementations?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. arXiv
    3. GitHub
    4. CVPR
    5. ICCV
    6. ECCV
    7. NeurIPS
    8. ICLR
    9. Hugging Face
    10. Kaggle
    11. Medium
    12. Towards Data Science

    AI recommended 12 alternatives but never named amusi/ECCV2026-Papers-with-Code. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to find the latest ECCV deep learning papers and their open-source projects?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. ECCV Official Website
    3. arXiv
    4. GitHub
    5. Twitter (X)
    6. The Batch (by DeepLearning.AI)
    7. SyncedReview
    8. Towards Data Science (on Medium)

    AI recommended 8 alternatives but never named amusi/ECCV2026-Papers-with-Code. 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 amusi/ECCV2026-Papers-with-Code?
    pass
    AI did not name amusi/ECCV2026-Papers-with-Code — 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 amusi/ECCV2026-Papers-with-Code in production, what risks or prerequisites should they evaluate first?
    pass
    AI named amusi/ECCV2026-Papers-with-Code 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 amusi/ECCV2026-Papers-with-Code solve, and who is the primary audience?
    pass
    AI did not name amusi/ECCV2026-Papers-with-Code — 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?

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