RRepoGEO

REPOGEO REPORT · LITE

yuval-alaluf/hyperstyle

Default branch main · commit a723c731 · scanned 5/15/2026, 2:52:53 AM

GitHub: 1,030 stars · 117 forks

AI VISIBILITY SCORE
33 /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
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 yuval-alaluf/hyperstyle, 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's opening paragraph to highlight practical benefits

    Why:

    CURRENT
    The current README's initial body text begins by describing the technical problem of StyleGAN inversion's trade-off.
    COPY-PASTE FIX
    HyperStyle is a novel StyleGAN inversion method that enables **real-time, high-quality editing of real images** while **preserving semantic control**. It introduces a hypernetwork approach to overcome the inherent trade-off between reconstruction and editability, making advanced image manipulation practical and efficient. This repository provides the official implementation for our CVPR 2022 paper.
  • mediumtopics#2
    Add more specific application-oriented topics

    Why:

    CURRENT
    cvpr2022, generative-adversarial-network, hypernetworks, stylegan, stylegan-encoder
    COPY-PASTE FIX
    cvpr2022, generative-adversarial-network, hypernetworks, stylegan, stylegan-encoder, image-editing, real-image-editing, stylegan-inversion, latent-space-editing, semantic-image-editing
  • lowabout#3
    Rephrase the 'About' description to highlight the problem solved

    Why:

    CURRENT
    Official Implementation for "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing" (CVPR 2022) https://arxiv.org/abs/2111.15666
    COPY-PASTE FIX
    Official implementation of HyperStyle: a novel StyleGAN inversion method using hypernetworks for efficient, high-quality real image editing with semantic control. (CVPR 2022)

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 yuval-alaluf/hyperstyle
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
StyleGAN2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. StyleGAN2 · recommended 2×
  2. StyleGAN3 · recommended 2×
  3. StyleCLIP · recommended 2×
  4. Stable Diffusion · recommended 2×
  5. DALL-E 2 · recommended 2×
  • CATEGORY QUERY
    How to edit real images using generative models without losing semantic control?
    you: not recommended
    AI recommended (in order):
    1. StyleGAN-XL
    2. StyleGAN-NADA
    3. StyleGAN-T
    4. StyleGAN2
    5. StyleGAN3
    6. StyleCLIP
    7. e4e
    8. InstructPix2Pix
    9. Hugging Face Diffusers library
    10. ControlNet
    11. Stable Diffusion
    12. Automatic1111's Stable Diffusion WebUI
    13. ComfyUI
    14. DreamBooth
    15. LoRA
    16. Kohya_ss GUI
    17. SDEdit
    18. Img2Img
    19. GLIDE
    20. DALL-E 2
    21. Midjourney
    22. Google Imagen

    AI recommended 22 alternatives but never named yuval-alaluf/hyperstyle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Efficiently invert real-world images into a latent space for quick semantic manipulation?
    you: not recommended
    AI recommended (in order):
    1. StyleGAN3
    2. StyleGAN2
    3. pSp (pixel2style2pixel)
    4. e4e (encoder4editing)
    5. StyleCLIP
    6. GANSpace
    7. InterFaceGAN
    8. Diffusion Models
    9. Stable Diffusion
    10. DALL-E 2
    11. Diffusers
    12. VQGAN
    13. CLIP
    14. BigGAN
    15. BigGAN-Encoder
    16. LPIPS (Learned Perceptual Image Patch Similarity)
    17. Autoencoders
    18. VAEs
    19. Adversarial Autoencoders

    AI recommended 19 alternatives but never named yuval-alaluf/hyperstyle. 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 yuval-alaluf/hyperstyle?
    pass
    AI named yuval-alaluf/hyperstyle explicitly

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

  • If a team adopts yuval-alaluf/hyperstyle in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yuval-alaluf/hyperstyle 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 yuval-alaluf/hyperstyle solve, and who is the primary audience?
    pass
    AI did not name yuval-alaluf/hyperstyle — 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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yuval-alaluf/hyperstyle — 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