REPOGEO REPORT · LITE

nv-tlabs/lyra

Default branch main · commit cc78b46b · scanned 5/23/2026, 2:58:12 AM

GitHub: 2,026 stars · 215 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /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

3 / 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 nv-tlabs/lyra, 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 project's core purpose immediately in README

Why:

CURRENT

<p align="center">
<h1 align="center">Project Lyra: Open Generative 3D World Models</h1>
<h3 align="center">NVIDIA Spatial Intelligence Lab</h3>
</p>

COPY-PASTE FIX

<p align="center">
<h1 align="center">Project Lyra: Open Generative 3D World Models</h1>
<h3 align="center">NVIDIA Spatial Intelligence Lab</h3>
</p>
Lyra provides official implementations of open generative 3D world models, enabling explorable 3D worlds with long-horizon, 3D-consistent generation from single images or videos.

mediumreadme#2

Expand README Overview to detail functional capabilities

Why:

CURRENT

**Project Lyra** is a series of open generative 3D world models developed at NVIDIA. This repository provides the official implementations of Lyra 1.0 and Lyra 2.0.

COPY-PASTE FIX

**Project Lyra** is a series of open generative 3D world models developed at NVIDIA. This repository provides the official implementations of Lyra 1.0 and Lyra 2.0, focusing on feed-forward 3D and 4D scene generation from a single image/video via video diffusion model self-distillation, and explorable generative 3D worlds with long-horizon, 3D-consistent generation.

mediumtopics#3

Add more specific topics for 3D generation and scene reconstruction

Why:

CURRENT

3d, diffusion, gaussians, video, world-model

COPY-PASTE FIX

3d, diffusion, gaussians, video, world-model, 3d-scene-generation, video-to-3d, generative-ai, neural-rendering, 3d-reconstruction

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 nv-tlabs/lyra

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

DreamFusion

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

DreamFusion · recommended 2×
Magic3D · recommended 2×
Nerfstudio · recommended 1×
COLMAP · recommended 1×
Meshroom · recommended 1×

CATEGORY QUERY
How to generate explorable 3D worlds from video input using AI models?
you: not recommended
AI recommended (in order):
1. Nerfstudio
2. COLMAP
3. Meshroom
4. AliceVision
5. RealityCapture
6. Instant-NGP (NVIDIA's Instant Neural Graphics Primitives)
7. DreamFusion
8. Magic3D
9. Zero123
10. Marigold
AI recommended 10 alternatives but never named nv-tlabs/lyra. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools exist for creating realistic 3D scenes from 2D media with diffusion?
you: not recommended
AI recommended (in order):
1. Luma AI
2. Instant NGP
3. DreamFusion
4. Magic3D
5. Stable Zero123
6. MVDream
AI recommended 6 alternatives but never named nv-tlabs/lyra. 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 nv-tlabs/lyra?
pass
AI named nv-tlabs/lyra explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts nv-tlabs/lyra in production, what risks or prerequisites should they evaluate first?
pass
AI named nv-tlabs/lyra 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 nv-tlabs/lyra solve, and who is the primary audience?
pass
AI named nv-tlabs/lyra explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/nv-tlabs/lyra"><img src="https://repogeo.com/badge/nv-tlabs/lyra.svg" alt="RepoGEO" /></a>

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nv-tlabs/lyra — 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