InterDigitalInc/GRASP-Net
Source code of "GRASP-Net: Geometric Residual Analysis and Synthesis for Point Cloud Compression"
This project helps professionals working with 3D scanning data, such as LiDAR scans or CAD models, to efficiently store and transmit their point clouds. It takes raw 3D point cloud data as input and produces a significantly smaller, compressed version that still accurately represents the original geometry. This is useful for engineers, researchers, and anyone else who needs to handle large volumes of 3D spatial data.
No commits in the last 6 months.
Use this if you regularly work with large 3D point cloud datasets and need to reduce their file size for storage or transmission without losing critical geometric detail.
Not ideal if your primary need is for compressing other types of 3D data like meshes or volumetric grids, or if your application requires perfectly lossless compression.
Stars
33
Forks
5
Language
Python
License
—
Category
Last pushed
Sep 20, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/InterDigitalInc/GRASP-Net"
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