Chen-Suyi/PointRegGPT
[ECCV 2024] PointRegGPT: Boosting 3D Point Cloud Registration using Generative Point-Cloud Pairs for Training, Pytorch implementation.
This project helps improve the accuracy of aligning 3D scans of indoor environments. It takes existing single depth maps of a scene and generates realistic, varied pairs of 3D point clouds that accurately simulate different viewing angles. Engineers, roboticists, or researchers working with 3D scanning and reconstruction will find this useful for training and evaluating their 3D point cloud registration algorithms.
Use this if you need to train or evaluate 3D point cloud registration algorithms for indoor scenes and require more realistic and diverse training data than readily available real-world or simple synthetic datasets.
Not ideal if your primary goal is to perform 3D point cloud registration directly, as this tool is focused on improving the training data for other registration algorithms, not on registration itself.
Stars
61
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 24, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Chen-Suyi/PointRegGPT"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
daavoo/pyntcloud
pyntcloud is a Python library for working with 3D point clouds.
yangyanli/PointCNN
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
torch-points3d/torch-points3d
Pytorch framework for doing deep learning on point clouds.
yogeshhk/MidcurveNN
Computation of Midcurve of Thin Polygons using Neural Networks
charlesq34/pointnet2
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space