3DTopia/OpenLRM

Health v2 · maintenance only

Adoption not part of the score

1244 stars · 80 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenLRM is an open-source PyTorch implementation of Large Reconstruction Models (LRM) that reconstruct 3D objects (meshes and rendered videos) from single images using transformer-based models. It includes pretrained weights trained on Objaverse and MVImgNet, training code, and a Hugging Face demo.

Use cases

• reconstruct a 3D model from a single image
• generate 3D assets for games or AIGC pipelines
• train a large reconstruction model on custom multi-view data
• run image-to-3D inference with pretrained LRM weights
• render turntable videos of reconstructed 3D objects
• experiment with feed-forward 3D reconstruction research

When to choose

• you need an open-source, research-grade implementation of LRM with pretrained weights
• you want to fine-tune or train large reconstruction models on your own datasets
• you need single-image to 3D reconstruction with mesh export

When to avoid

• you need production-ready, photorealistic 3D generation with commercial licensing (weights are CC BY-NC)
• you lack a GPU or cannot install xFormers memory-efficient attention
• you need real-time 3D reconstruction rather than offline feed-forward inference

Facets

library · maturity active

machine-learning deep-learning image-processing graphics computer-vision artificial-intelligence graphics deep-learning python 3d-reconstruction large-reconstruction-model lrm 3d-generation aigc objaverse tripod-gaussian image-to-3d gpu linux

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