NVlabs/neuralangelo

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

4615 stars · 404 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Official PyTorch implementation of Neuralangelo, a CVPR 2023 method for high-fidelity neural surface reconstruction from multi-view images. It builds on NVIDIA's Imaginaire library and trains neural signed distance functions with multi-GPU support.

Use cases

• reconstruct 3d surfaces from video frames
• high-fidelity neural surface reconstruction from images
• generate 3d meshes from multi-view photos
• research neural implicit surface modeling
• reproduce cvpr 2023 neuralangelo paper results

When to choose

• you need state-of-the-art neural surface reconstruction with fine geometric detail
• you have known camera poses and want to train a neural SDF on multi-view data
• you want the official reference implementation for research reproduction

When to avoid

• you need a quick photogrammetry pipeline without GPU training
• you lack CUDA GPUs or multi-GPU infrastructure
• you want a turnkey 3D scanning app rather than a research codebase

Facets

library · maturity active

machine-learning computer-vision graphics simulation computer-vision graphics deep-learning python neural-rendering 3d-reconstruction neural-surface-reconstruction sdf nerf cvpr-2023 research-code multi-gpu-training gpu docker linux

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For agents

markdown · JSON · MCP: product_card(name="NVlabs/neuralangelo")