magicleap/Atlas

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1857 stars · 216 forks observed · 2026-08-28

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

Atlas is a PyTorch-based deep learning model from Magic Leap that performs end-to-end 3D scene reconstruction from posed RGB images, producing TSDF volumes and meshes. It includes training, evaluation, and inference code with Docker support and pretrained models.

Use cases

• reconstruct 3D scenes from posed images
• generate 3D meshes from RGB photos
• run TSDF fusion with a neural network
• evaluate 3D reconstruction on ScanNet
• research volumetric scene reconstruction
• build 3D models from camera poses

When to choose

• you have posed images and need dense 3D reconstruction
• you want a learned alternative to classical TSDF fusion
• you need a research baseline for end-to-end scene reconstruction

When to avoid

• you lack GPU hardware or posed camera data
• you need actively maintained production software
• you need reconstruction from unposed images without running COLMAP first

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing graphics simulation computer-vision deep-learning machine-learning graphics artificial-intelligence python 3d-reconstruction scene-reconstruction tsdf-fusion pytorch depth-estimation research-code posed-images linux docker gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="magicleap/Atlas")