Grid-GCN for Fast and Scalable Point Cloud Learning

Grid-GCN for Fast and Scalable Point Cloud Learning

6 December 2019

Cho-Ying Wu

Ulrich Neumann

Papers citing "Grid-GCN for Fast and Scalable Point Cloud Learning"

7 / 57 papers shown

Title
Learning Part Boundaries from 3D Point Clouds Marios Loizou Melinos Averkiou E. Kalogerakis 3DPC 29 33 0 15 Jul 2020
Local Grid Rendering Networks for 3D Object Detection in Point Clouds Jianan Li Jiashi Feng 3DPC 11 1 0 04 Jul 2020
Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels Yi Zhou Chenglei Wu Zimo Li Chen Cao Yuting Ye Jason M. Saragih Hao Li Yaser Sheikh 15 75 0 08 Jun 2020
Scene Completeness-Aware Lidar Depth Completion for Driving Scenario Cho-Ying Wu Ulrich Neumann 3DV 63 9 0 15 Mar 2020
DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing Yongcheng Liu Bin Fan Gaofeng Meng Jiwen Lu Shiming Xiang Chunhong Pan 3DPC 128 271 0 09 Sep 2019
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 169 769 0 30 Mar 2018
Joint 2D-3D-Semantic Data for Indoor Scene Understanding Iro Armeni S. Sax Amir Zamir Silvio Savarese 3DV 3DPC 127 878 0 03 Feb 2017