andreasMazur/geoconv
A Python library for end-to-end learning on surfaces. It implements pre-processing functions that include geodesic algorithms, neural network layers that operate on surfaces, visualization tools and benchmarking functionalities.
This tool helps researchers and engineers build deep learning models that can analyze the shapes and characteristics of 3D objects, specifically those represented as mesh files. It takes a 3D mesh (like a .ply file) and a signal defined on its surface, then processes them to produce a structured output ready for neural network analysis or classification. It is used by anyone working with 3D object data who needs to apply deep learning for tasks like shape recognition, object classification, or analyzing physical properties on curved surfaces.
Available on PyPI.
Use this if you need to apply deep learning to 3D object surfaces and want to use intrinsic convolutions that respect the object's geometry, rather than treating it as flat data.
Not ideal if your data is primarily flat (Euclidean) or if you are working with unstructured point clouds without mesh connectivity.
Stars
37
Forks
3
Language
Python
License
GPL-3.0
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Dependencies
10
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