RRepoGEO

REPOGEO REPORT · LITE

danieljf24/awesome-video-text-retrieval

Default branch master · commit 6cfaa3b8 · scanned 6/6/2026, 12:12:51 AM

GitHub: 645 stars · 69 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 danieljf24/awesome-video-text-retrieval, 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 'awesome list' nature in the README's opening sentence

    Why:

    CURRENT
    A curated list of deep learning resources for video-text retrieval.
    COPY-PASTE FIX
    This repository is an awesome curated list of deep learning resources for video-text retrieval, including papers, implementations, and datasets.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    awesome-list, deep-learning, video-text-retrieval, video-retrieval, natural-language-processing, computer-vision, multimodal-ai, research-papers, code-resources
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file with the MIT License text.

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 danieljf24/awesome-video-text-retrieval
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
CLIP
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. CLIP · recommended 2×
  2. VideoCLIP · recommended 2×
  3. Frozen CLIP · recommended 2×
  4. CLAP · recommended 1×
  5. InternVideo · recommended 1×
  • CATEGORY QUERY
    What deep learning models are effective for retrieving video content based on text descriptions?
    you: not recommended
    AI recommended (in order):
    1. CLIP
    2. CLAP
    3. VideoCLIP
    4. Frozen CLIP
    5. InternVideo
    6. ALPRO
    7. VATT
    8. UniVL
    9. HERO
    10. Moment-DETR
    11. 2D-TAN

    AI recommended 11 alternatives but never named danieljf24/awesome-video-text-retrieval. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I find research papers and code for video search using natural language queries?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. arXiv
    3. Papers With Code
    4. GitHub
    5. Hugging Face
    6. Kaggle
    7. CLIP
    8. VideoCLIP
    9. CLIP4Clip
    10. Frozen CLIP
    11. BLIP
    12. ViT
    13. Transformers (huggingface/transformers)
    14. PyTorch
    15. TensorFlow

    AI recommended 15 alternatives but never named danieljf24/awesome-video-text-retrieval. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 danieljf24/awesome-video-text-retrieval?
    pass
    AI did not name danieljf24/awesome-video-text-retrieval — 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 danieljf24/awesome-video-text-retrieval in production, what risks or prerequisites should they evaluate first?
    pass
    AI named danieljf24/awesome-video-text-retrieval 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 danieljf24/awesome-video-text-retrieval solve, and who is the primary audience?
    pass
    AI did not name danieljf24/awesome-video-text-retrieval — 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?

Embed your GEO score

Drop this badge into the README of danieljf24/awesome-video-text-retrieval. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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danieljf24/awesome-video-text-retrieval — 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