yyfz/Pi3

Health v2 · maintenance only

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2122 stars · 167 forks observed · 2026-08-28

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

Pi3 (π³) is a feed-forward neural network for visual geometry reconstruction that eliminates the need for a fixed reference view, using a permutation-equivariant architecture to achieve state-of-the-art results. It reconstructs point clouds, camera poses, and depth from images or videos, with an upgraded Pi3X model supporting conditional injection and approximate metric scale.

Use cases

• reconstruct 3d point clouds from photos
• estimate camera poses from a video
• predict depth maps from images without a reference view
• recover visual geometry from in-the-wild videos
• run 3d reconstruction inference on gpu
• train a visual geometry model
• evaluate multi-view geometry reconstruction models

When to choose

• you need feed-forward 3d reconstruction from multiple images or video without fixed reference view
• you want state-of-the-art point cloud, camera pose, and depth prediction in one model
• you need conditional injection of camera pose, intrinsics, or depth (Pi3X)
• you want a research-grade model with training, evaluation, and demo code available

When to avoid

• you need real-time reconstruction on CPU or edge devices
• you need a lightweight classical SfM/SLAM pipeline like COLMAP
• you cannot run GPU inference
• you need production-supported software with long-term maintenance guarantees

Facets

library · maturity active

machine-learning deep-learning computer-vision image-processing graphics simulation computer-vision deep-learning machine-learning graphics artificial-intelligence python cross-platform 3d-reconstruction visual-geometry point-cloud camera-pose-estimation depth-estimation feed-forward-network permutation-equivariant structure-from-motion research-code iclr-2026 gpu linux

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