RIU-Net: Embarrassingly simple semantic segmentation of 3D LiDAR point cloud

21 May 2019

Papers citing "RIU-Net: Embarrassingly simple semantic segmentation of 3D LiDAR point cloud"

5 / 5 papers shown

Title
RangeSeg: Range-Aware Real Time Segmentation of 3D LiDAR Point Clouds Tzu-Hsuan Chen T. Chang 3DPC 13 46 0 02 May 2022
Joint Pose and Shape Estimation of Vehicles from LiDAR Data Hunter Goforth Xiaoyan Hu Michael Happold Simon Lucey 3DPC 6 5 0 08 Sep 2020
ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation Hanwen Cao Yongyi Lu Cewu Lu Bo Pang Gongshen Liu Alan Yuille 3DPC 26 15 0 12 Aug 2020
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study Biao Gao Yancheng Pan Chengkun Li Sibo Geng Huijing Zhao 3DPC 19 25 0 08 Jun 2020
LU-Net: An Efficient Network for 3D LiDAR Point Cloud Semantic Segmentation Based on End-to-End-Learned 3D Features and U-Net P. Biasutti Vincent Lepetit Jean-François Aujol Mathieu Brédif Aurélie Bugeau 3DV SSeg 3DPC 14 38 0 30 Aug 2019