Dilated Point Convolutions: On the Receptive Field Size of Point Convolutions on 3D Point Clouds

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Original

Yin Zhou and Oncel Tuzel · 1907

Earlier work this paper cites.

Visualizing and Understanding Convolutional Networks

Matthew D. Zeiler and Rob Fergus · 2014

Earlier work this paper cites.

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L. Yuille · 2015

Earlier work this paper cites.

VoxNet: A 3D Convolutional Neural Network for real-time object recognition

Daniel Maturana and Sebastian Scherer · 2015

Earlier work this paper cites.

Very Deep Convolutional Networks for Large-Scale Image Recognition

Karen Simonyan and Andrew Zisserman · 2015

Earlier work this paper cites.

Going Deeper with Convolutions

Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott E. Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015

Earlier work this paper cites.

3D ShapeNets: A Deep Representation for Volumetric Shapes

Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015

Earlier work this paper cites.

3D Semantic Parsing of Large-Scale Indoor Spaces

Iro Armeni, Ozan Sener, Amir R. Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016

Earlier work this paper cites.

Deep Residual Learning for Image Recognition

Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016

Earlier work this paper cites.

Understanding the effective receptive field in deep convolutional neural networks

Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel · 2016

Earlier work this paper cites.

Volumetric and Multi-View CNNs for Object Classification on 3D Data

Charles R. Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas J. Guibas · 2016

Earlier work this paper cites.

Multi-Scale Context Aggregation by Dilated Convolutions

Fisher Yu and Vladlen Koltun · 2016

Cited alongside, same era.

SnapNet: 3D point cloud semantic labeling with 2D deep segmentation networks

Alexandre Boulch, Joris Guerry, Bertrand Le Saux, and Nicolas Audebert · 2017

Cited alongside, same era.

ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenes

Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017

Cited alongside, same era.

Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models

Roman Klokov and Victor Lempitsky · 2017

Cited alongside, same era.

Systematic Evaluation of Convolution Neural Network Advances on the ImageNet

Dmytro Mishkin, Nikolay Sergievskiy, and Jiri Matas · 2017

Cited alongside, same era.

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

Pointwise Convolutional Neural Network

Binh-Son Hua, Minh-Khoi Tran, and Sai-Kit Yeung · 2018

Later among the works it cites.

Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs

Loïc Landrieu and Martin Simonovsky · 2018

Later among the works it cites.

SO-Net: Self-Organizing Network for Point Cloud Analysis

Jiaxin Li, Ben M Chen, and Gim Hee Lee · 2018

Later among the works it cites.

PointCNN: Convolution On X-Transformed Points

Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018

Later among the works it cites.

Deep Parametric Continuous Convolutional Neural Networks

S. Wang, S. Suo, W.C. Ma, A. Pokrovsky, and R. Urtasun · 2018

Later among the works it cites.

Dynamic Graph CNN for Learning on Point Clouds

Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, and Justin M. Solomon · 2018

Later among the works it cites.