lizhihao6/Sparc3D

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1353 stars · 72 forks observed · 2026-08-28

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

Sparc3D is the official implementation of a research framework for high-resolution 3D shape modeling, combining a sparse deformable marching cubes representation (Sparcubes) with a sparse-convolution VAE (Sparconv-VAE). It enables near-lossless 1024³ 3D reconstruction and integrates with latent diffusion models for image-to-3D generation.

Use cases

• generate 3D models from a single image
• reconstruct high-resolution meshes from raw geometry
• build a VAE for 3D shape latent diffusion
• convert meshes to sparse volumetric representations
• research on sparse convolutional networks for 3D
• preserve fine details in 3D asset generation

When to choose

• you need state-of-the-art high-fidelity 3D reconstruction or image-to-3D generation
• you are researching sparse convolution VAEs or latent diffusion for 3D shapes
• you need to handle open surfaces, disconnected components, or intricate geometry

When to avoid

• you need a production-ready tool with a stable API and license
• you want simple, low-poly 3D modeling without GPU resources
• code release is still pending approval, so you need something immediately runnable

Facets

library · maturity experimental

machine-learning deep-learning image-processing graphics simulation artificial-intelligence deep-learning computer-vision graphics machine-learning python cross-platform 3d-generation 3d-reconstruction sparse-convolution variational-autoencoder latent-diffusion mesh-processing research-code image-to-3d gpu linux

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