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Vv-net: Voxel vae net with group convolutions for point cloud segmentation
We present a novel algorithm for point cloud segmentation. Our approach transforms
unstructured point clouds into regular voxel grids, and further uses a kernel-based …
unstructured point clouds into regular voxel grids, and further uses a kernel-based …
IterativePFN: True iterative point cloud filtering
The quality of point clouds is often limited by noise introduced during their capture process.
Consequently, a fundamental 3D vision task is the removal of noise, known as point cloud …
Consequently, a fundamental 3D vision task is the removal of noise, known as point cloud …
Deep feature-preserving normal estimation for point cloud filtering
Point cloud filtering, the main bottleneck of which is removing noise (outliers) while
preserving geometric features, is a fundamental problem in 3D field. The two-step schemes …
preserving geometric features, is a fundamental problem in 3D field. The two-step schemes …
Multi-patch collaborative point cloud denoising via low-rank recovery with graph constraint
Point cloud is the primary source from 3D scanners and depth cameras. It usually contains
more raw geometric features, as well as higher levels of noise than the reconstructed mesh …
more raw geometric features, as well as higher levels of noise than the reconstructed mesh …
Contrastive learning for joint normal estimation and point cloud filtering
Point cloud filtering and normal estimation are two fundamental research problems in the 3D
field. Existing methods usually perform normal estimation and filtering separately and often …
field. Existing methods usually perform normal estimation and filtering separately and often …
3d shape synthesis via content–style revealing priors
To increase the diversity of created shapes conveniently, we describe a fully automatic
synthesis framework based on the content–style analysis of an input set of 3D shapes. To …
synthesis framework based on the content–style analysis of an input set of 3D shapes. To …
Intrinsic shape matching via tensor-based optimization
This paper presents a simple yet efficient framework for finding a set of sparse
correspondences between two non-rigid shapes using a tensor-based optimization …
correspondences between two non-rigid shapes using a tensor-based optimization …
Geometric prior and deep learning co-supported normal estimation for point cloud
Point normals are fundamental geometric attributes of point clouds. To tackle traditional and
learning-based technology problems, a normal estimation method is proposed based on …
learning-based technology problems, a normal estimation method is proposed based on …
基于几何先验和深度学**的点云法矢估算
郜金艳， 郭延文， 王连生， 汪俊， 魏明** - 计算机辅助设计与图形学学报, 2022 - jcad.cn
法矢是三维点云曲面最基本的几何属性. 为解决传统几何估算子与基于学**技术中的问题,
提出基于几何先验和深度学**的点云法矢估算方法. 首先, 使用一个多尺度曲面块选择方法保持 …
提出基于几何先验和深度学**的点云法矢估算方法. 首先, 使用一个多尺度曲面块选择方法保持 …
[PDF][PDF] Fourier Ptychographic Microscopy Enhanced with Implicit Neural Fields and Ray-Distance Surface Modeling
M Ashrafuzzaman - 2024 - researchgate.net
Abstract Fourier Ptychographic Microscopy (FPM) is a powerful imaging technique that
combines widefield microscopy with computational algorithms to achieve high-resolution …
combines widefield microscopy with computational algorithms to achieve high-resolution …