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proxy2world

Proxy2World: Learning to Generate Worlds from Proxies Without Seeing Them.

This is 1 of 543 launches in AI agent infrastructure and tooling — see how it stacks up on momentum and crowding →

1328 other launches read as similar to this one →

Details

External ID
1391634428
Source
GITHUB
Company
—
Product
proxy2world
Website domain
github.io
Launched
Sept. 28, 2026
Cohort
—
Upvotes
9
Upvotes percentile
0.2155338635815859
Tags
—
Fetched at
Oct. 2, 2026, 1:02 a.m.
Updated at
Oct. 2, 2026, 1:02 a.m.

Enrichment

Theme
AI agent infrastructure and tooling
Vertical
Media & entertainment
Function
Content generation
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
world generation model using proxy data
Manually corrected
False

Could you build this?

No Proxy2World is cutting-edge AI research from Tencent IEG for generative 3D world synthesis using coarse geometric proxies and RGBD diffusion conditioning.

What it would actually take: The system requires training novel multi-modal diffusion architectures conditioned on RGBD video data and 3D camera trajectories. Building it involves complex computer vision pipelines: depth estimation, 3D scene representation (like 3D Gaussian Splatting or neural radiance fields), scale-aligned camera grounding, and heavy distributed model training on large video datasets. This demands dedicated research teams specializing in 3D computer vision, generative video models, and substantial high-performance GPU infrastructure.

Competitors

Other products that read as similar to this one — 1328 launches clear the similarity bar, closest 8 shown.

Attention rank: #904 of 1329 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 334 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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