mabaorui/NeuralPull-Pytorch
Implementation of ICML'2021:Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
This project helps convert messy 3D point cloud data into clean, usable 3D surface models. It takes raw scans of objects or environments as input and outputs a smooth, reconstructed mesh that accurately represents the original shape. This tool is ideal for 3D artists, designers, engineers, or researchers working with scanned physical objects.
No commits in the last 6 months.
Use this if you need to create a solid, watertight 3D model from unorganized 3D scan data (point clouds).
Not ideal if you're looking for a tool to generate 3D models from scratch using traditional modeling techniques or descriptive parameters.
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Language
Python
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Last pushed
Feb 04, 2024
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