Project ◆ Hidden gem

TripoSR

VAST-AI-Research/TripoSR · Python · MIT

Fast feed-forward image-to-3D

TripoSR prioritizes speed: drop an image, get a mesh quickly for blocking out game assets.

57.6 / 100 · Score
★ 7.1k Stars
+64 30-day growth
20 min Time to first run
Not required API key

Score

Trend 61
Activity 9
Quality 65
Community 41
Relevance 100

Setup at a glance

DeployCli
GPU6 GB
API keyNot required
UI languages
Doc languagesen
Install
pip install triposr

Deep dive

TripoSR is a fast single-image-to-3D reconstruction model from VAST AI Research (with Stability AI collaboration): one photo in, a textured 3D model out in under a second on a capable GPU.

It builds on the LRM (Large Reconstruction Model) line of research — feed-forward 3D reconstruction without per-object optimization — which is what makes it fast enough for interactive use.

The repo is a compact, pip-installable inference stack with clear requirements (Python 3.8+, CUDA, PyTorch), so it drops into existing 3D tooling; the approach is documented in an arXiv paper.

Use cases

Rapid prop drafts
Concept-to-mesh
Pipeline smoke tests

Good for / Not ideal for

Good for

Designers iterating quickly

Not ideal for

Final hero assets needing perfect topology

Trend · 30d

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