RRepoGEO

REPOGEO REPORT · LITE

deepseek-ai/DreamCraft3D

Default branch main · commit 5829ef11 · scanned 5/29/2026, 6:18:16 PM

GitHub: 3,006 stars · 358 forks

AI VISIBILITY SCORE
27 /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
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 deepseek-ai/DreamCraft3D, 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 README opening to emphasize single-image 3D generation

    Why:

    CURRENT
    Official implementation of DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
    COPY-PASTE FIX
    DreamCraft3D is the official implementation of our ICLR 2024 method for hierarchical 3D content generation from a single 2D reference image, producing high-fidelity and coherent 3D objects.
  • mediumreadme#2
    Explicitly state the core 3D representation or unique technical approach

    Why:

    COPY-PASTE FIX
    Our method uniquely tackles consistency and fidelity issues by combining view-dependent score distillation sampling for geometry sculpting with Bootstrapped Score Distillation for texture boosting, using a personalized diffusion model.
  • lowtopics#3
    Add more specific topics for single-image 3D generation

    Why:

    CURRENT
    3d-creation, 3d-generation, aigc, diffusion-models, generative-model, image-to-3d
    COPY-PASTE FIX
    3d-creation, 3d-generation, aigc, diffusion-models, generative-model, image-to-3d, single-image-3d, 3d-reconstruction, neural-rendering

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 deepseek-ai/DreamCraft3D
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Luma AI
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. Luma AI · recommended 3×
  2. NVlabs/instant-ngp · recommended 2×
  3. Agisoft Metashape · recommended 2×
  4. RealityCapture · recommended 2×
  5. Stability-AI/Zero123 · recommended 1×
  • CATEGORY QUERY
    How to generate high-fidelity 3D models from single 2D images using AI?
    you: not recommended
    AI recommended (in order):
    1. Luma AI
    2. Instant NGP (NVlabs/instant-ngp)
    3. Zero123 (Stability-AI/Zero123)
    4. Zero123++ (Stability-AI/Zero123-XL)
    5. Mip-NeRF 360 (google-research/multinerf)
    6. K-Planes (sarafrid/K-Planes)
    7. DreamFusion (google-research/dreamfusion)
    8. Magic3D (google-research/magic3d)
    9. Agisoft Metashape
    10. RealityCapture
    11. Meshroom (alicevision/meshroom)

    AI recommended 11 alternatives but never named deepseek-ai/DreamCraft3D. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools provide consistent and coherent 3D object generation from image inputs?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA instant-ngp (NVlabs/instant-ngp)
    2. nerfstudio (nerfstudio-project/nerfstudio)
    3. Luma AI
    4. RealityCapture
    5. Agisoft Metashape
    6. Meshroom (alicevision/Meshroom)
    7. 3D Gaussian Splatting (graphdeco-inria/gaussian-splatting)
    8. Luma AI
    9. COLMAP (colmap/colmap)
    10. OpenMVG (openMVG/openMVG)
    11. Google DreamFusion / Magic3D
    12. NVIDIA Get3D
    13. OpenAI Point-E (openai/point-e)

    AI recommended 13 alternatives but never named deepseek-ai/DreamCraft3D. 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 deepseek-ai/DreamCraft3D?
    pass
    AI did not name deepseek-ai/DreamCraft3D — 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 deepseek-ai/DreamCraft3D in production, what risks or prerequisites should they evaluate first?
    pass
    AI named deepseek-ai/DreamCraft3D 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 deepseek-ai/DreamCraft3D solve, and who is the primary audience?
    pass
    AI did not name deepseek-ai/DreamCraft3D — 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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deepseek-ai/DreamCraft3D — 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