3dmatch-toolbox

Why we included this project

Aligning overlapping 3D scans is genuinely hard because depth data comes in noisy and incomplete, and this toolbox is the reference implementation of 3DMatch, a learned geometric descriptor built for that job. It turns partial point clouds and depth frames into per-voxel features, so you can find correspondences between fragments and use them for registration or keypoint matching before a full reconstruction. In addition to pretrained models ready to run on your own RGB-D data, it ships the training code to learn a fresh descriptor from existing reconstructions, which helps when your data differs from the published benchmarks. Robotics and scanning teams, or anyone doing instance-level object alignment, will find it a useful baseline for judging newer matching approaches. Expect a research codebase you run locally, not a hosted service.