Open AccessNeuralQAAD: An Efficient Differentiable Framework for Compressing High Resolution Consistent Point Clouds Datasets
Author(s) -
Nicolas Wagner,
Ulrich Schwanecke
Publication year - 2022
Publication title -
proceedings of the 17th international joint conference on computer vision, imaging and computer graphics theory and applications
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5220/0010772500003124
Subject(s) - differentiable function , computer science , point cloud , point (geometry) , resolution (logic) , high resolution , algorithm , artificial intelligence , remote sensing , geology , mathematics , geometry , mathematical analysis