aim-uofa/AdelaiDepth

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1106 stars · 148 forks observed · 2026-08-28

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

AdelaiDepth is an open-source toolbox for monocular depth prediction and 3D scene reconstruction from single images, containing research projects like 3D Scene Shape (LeReS), DiverseDepth, and Virtual Normal. It provides pretrained models, training code, and datasets from academic computer vision research.

Use cases

• estimate depth from a single image
• reconstruct 3D scene shape from one photo
• generate point clouds from monocular images
• train a depth prediction model
• compare monocular depth estimation algorithms
• run depth estimation on gpu

When to choose

• you need state-of-the-art monocular depth estimation with pretrained models
• you want to reproduce or build on published depth estimation research
• you need 3D scene reconstruction from a single RGB image

When to avoid

• you need real-time depth estimation on edge devices
• you want a production-ready maintained product with active support
• you need stereo or multi-view depth estimation rather than monocular

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning graphics python monocular-depth-estimation 3d-reconstruction depth-prediction point-cloud research-code pytorch linux gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="aim-uofa/AdelaiDepth")