graphdeco-inria/hierarchical-3d-gaussians

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1461 stars · 140 forks observed · 2026-08-28

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

Official implementation of the SIGGRAPH 2024 paper 'A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasets'. It trains hierarchical 3D Gaussian splatting models that enable real-time rendering of very large captured scenes, organized in chunks.

Use cases

• render very large 3d captured scenes in real time
• train hierarchical 3d gaussian splatting models from photos
• novel view synthesis of large datasets
• reproduce the siggraph 2024 hierarchical 3dgs paper results
• convert and render large-scale gaussian splat scenes
• process thousands of images into a renderable 3d scene

When to choose

• you need real-time rendering of scenes too large for standard 3D Gaussian Splatting
• you want the authoritative reference implementation of the hierarchical 3DGS paper
• you are doing research on radiance fields or large-scale scene capture

When to avoid

• you need a production-ready, stable tool - the code is explicitly alpha
• you only need small-scene 3D Gaussian Splatting, where the original 3DGS repo is simpler
• you require a permissive license - the license is non-standard and restrictive

Facets

library · maturity experimental

graphics machine-learning image-processing simulation computer-vision graphics machine-learning deep-learning windows python 3d-gaussian-splatting novel-view-synthesis real-time-rendering radiance-fields research-code siggraph-2024 large-scale-scenes linux gpu

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