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2020-3D Semantic Segmentation for Large-Scale Scene

幺幺零 2023-03-06 阅读 96
pointcloud拟合github激活函数Python后端开发


3D Semantic Segmentation for Large-Scale Scene Understanding

Kiran Akadas and Shankar Gangisetty
KLE Technological University, Hubballi, India
akadask@gmail.com, shankar@kletech.ac.in

年份：2020

期刊/会议：ACCV

代码：https://github.com/KiranAkadas/GRanDNet

1、创新

  • 基于RandLA-net，随机采样，速度快、效率高
  • 使用了空洞卷积
  • GeLU作为激活函数，对拟合方程更有帮助
  • 提出了可选的CRF优化方法

2、具体实现

2020-3D Semantic Segmentation for Large-Scale Scene_激活函数

3、实验结果

SHREC 2020

2020-3D Semantic Segmentation for Large-Scale Scene_pointcloud_02

2020-3D Semantic Segmentation for Large-Scale Scene_github_03

2020-3D Semantic Segmentation for Large-Scale Scene_激活函数_04

S3DIS

2020-3D Semantic Segmentation for Large-Scale Scene_github_05

2020-3D Semantic Segmentation for Large-Scale Scene_github_06

SemanticKITTI

2020-3D Semantic Segmentation for Large-Scale Scene_github_07

2020-3D Semantic Segmentation for Large-Scale Scene_github_08


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