Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space (Paper)

A paper that describes how to speed-up deep learning on 3D point clouds with (G-)CNNs by compressing its linear representation layers by a local partial symmetry analysis.

Data and Resources

Additional Info

Field Value
Publication(s)
Publication 1
Title of related publication
Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space
Year of related publication
2026
DOI of related publication (not DOI of data resources)
Funding DFG Project No. 233630050-TRR146
Subproject Project B7: Automated model building and representation learning for multiscale simulations
Cooperation partner(s) Johannes Gutenberg University Mainz
Responsible Person's Name (PI) Prof. Dr. Michael Wand
Responsible Person's Email for further data requests wandm@uni-mainz.de
Responsible Person's Affiliation Institute of Computer Science, Johannes Gutenberg University Mainz, Germany