3D point cloudClass-imbalanced learningSemantic segmentationSemi-supervised learning2024 Elsevier LtdSemi-supervised learning (SSL), thanks to the significant reduction of data annotation costs, has been an act
Large-scale point cloud semantic segmentation: Recently, various models have been introduced in academia to address the challenge of large-scale point cloud semantic segmentation. Among them, Landrieu et al. introduced SPG [11], which leverages the concept of a superpoint graph to transform point ...
Semantic segmentation of large-scale point clouds in 3D computer vision is a challenging problem. Existing feature extraction modules often emphasize learn
If you use the semantic segmentation module (code in /learning), please cite: Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs, Loic Landrieu and Martin Simonovski, CVPR, 2018. If you use the learned partition module (code in /supervized_partition), please cite: Point Clo...
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs, Loic Landrieu and Martin Simonovski, CVPR, 2018. If you use the learned partition module (code in/supervized_partition), please cite: Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning, Loic Landrieu and Mo...
Learning Semantic Segmentation of Large-Scale Point Clouds With Random Sampling 用随机抽样法学习大规模点云的语义分割 摘要 我们研究了大规模三维点云的有效语义分割问题。由于依赖昂贵的采样技术或计算量大的前/后处理步骤,大多数现有的方法只能在小规模的点云上进行训练和操作。在本文中,我们介绍了RandLA-Net,...
论文《RandLaNet: Efficient Semantic Segmentation of Large-Scale Point Clouds》阅读笔记,程序员大本营,技术文章内容聚合第一站。
SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation weixin 炸炉师 来自专栏 · 机器之脑 8 人赞同了该文章 Year: 2021 Published in: CVPR TL;DR 本文主要探索了如何高效处理大规模点云分割的问题,主要是通过一种叫做 Spatial Contextual Features(SCF) 的模块学习点云在...
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds CVPR 论文笔记 2020,程序员大本营,技术文章内容聚合第一站。
A. Semantic-based Farthest Point Sampling B. Semantic-augmented Feature Extraction C. Semantic-refined Transformation Estimation D. Loss Functions 论文 代码 简介: 与以前仅在点空间中构建对应关系的方法不同,利用语义特征作为辅助来提高配准精度。 一、introduction: 作者认为,从本质上讲,大多数现有的方法仅利用...