amosgropp/IGR
Implicit Geometric Regularization for Learning Shapes
This tool helps 3D graphics professionals and researchers create detailed, smooth 3D models from raw point cloud data, even if it lacks normal information. You input point clouds representing a 3D object, and it outputs a meshed surface, effectively reconstructing the object's shape. It also supports learning and generating variations within a collection of shapes, like human body scans.
444 stars. No commits in the last 6 months.
Use this if you need to reconstruct smooth, high-fidelity 3D surfaces from noisy or incomplete 3D scan data (point clouds) and require a deep learning approach for robust shape generation.
Not ideal if you need a quick, off-the-shelf solution for simple mesh generation without deep learning expertise, or if your primary goal is real-time processing of very large point clouds.
Stars
444
Forks
42
Language
Python
License
—
Category
Last pushed
Dec 09, 2021
Commits (30d)
0
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