KPConv: Flexible and Deformable Convolution for Point Clouds

KPConv: Flexible and Deformable Convolution for Point Clouds

18 April 2019

Jean-Emmanuel Deschaud

Leonidas J. Guibas

Papers citing "KPConv: Flexible and Deformable Convolution for Point Clouds"

11 / 1,109 papers shown

Title
Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification Congcong Wen Lina Yang Ling Peng Xiang Li T. Chi 3DPC 26 99 0 19 Aug 2019
Deformable Filter Convolution for Point Cloud Reasoning Yuwen Xiong Mengye Ren Renjie Liao K. Wong R. Urtasun 3DPC 34 17 0 30 Jul 2019
A review on deep learning techniques for 3D sensed data classification David J. Griffiths Jan Boehm 3DPC 3DV 27 165 0 09 Jul 2019
Spatial Transformer for 3D Point Clouds Jiayun Wang Rudrasis Chakraborty Stella X. Yu 3DPC 22 14 0 26 Jun 2019
Learning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds Bo Yang Jianan Wang R. Clark Qingyong Hu Sen Wang Andrew Markham A. Trigoni 3DPC 41 324 0 04 Jun 2019
NPTC-net: Narrow-Band Parallel Transport Convolutional Neural Network on Point Clouds P. Jin Tianhao Lai Rongjie Lai Bin Dong 3DPC 9 3 0 29 May 2019
ConvPoint: Continuous Convolutions for Point Cloud Processing Alexandre Boulch 3DPC 28 239 0 04 Apr 2019
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters Yifan Xu Tianqi Fan Mingye Xu Long Zeng Yu Qiao 3DV 3DPC 152 769 0 30 Mar 2018
Inference, Learning and Attention Mechanisms that Exploit and Preserve Sparsity in Convolutional Networks Timo Hackel Mikhail (Misha) Usvyatsov S. Galliani Jan Dirk Wegner Konrad Schindler 21 14 0 31 Jan 2018
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 260 1,812 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 261 3,243 0 24 Nov 2016