Convolutional Neural Network-based Efficient Dense Point Cloud Generation using Unsigned Distance Fields

arXiv:2203.11537v3 Announce Type: replace
Abstract: Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics. So far, the existing methods are either computationally too expensive, suffer from limited resolution, or both. In addition, some methods are strictly limited to watertight surfaces -- another major obstacle for a number of applications. To address these issues, we propose a lightweight Convolutional Neural Network that learns and predicts the …

abstract arxiv cloud computer computer graphics computer vision convolutional neural network cs.cv fields graphics network neural network type vision