PointCloudYC/ResPointNet2
ResPointNet++ for AutoCon journal paper.
This tool helps automate the identification of components within 3D point cloud scans of industrial sites. You input raw LiDAR data from industrial scenes, and it outputs a segmented point cloud where elements like pipes, pumps, tanks, and structural beams are automatically classified. This is designed for professionals in construction, industrial maintenance, or facilities management who work with as-built building information models (BIM).
No commits in the last 6 months.
Use this if you need to automatically and accurately identify and categorize industrial components from large 3D point cloud datasets to create or update BIM models.
Not ideal if you are working with non-industrial scenes or require segmentation of object types beyond plumbing and structural components.
Stars
43
Forks
3
Language
Python
License
MIT
Category
Last pushed
Oct 14, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/PointCloudYC/ResPointNet2"
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