Fetching the paper…
Reading the bibliography…
Autonomous robotic systems and self driving cars rely on accurate perception of their surroundings as the safety of the passengers and pedestrians is the top priority.
Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite
A. Geiger, P. Lenz, and R. Urtasun · 2012
Earlier work this paper cites.
ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 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.
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.
Squeezenet: Alexnet-level accuracy with 50x fewer parameters and
Forrest N Iandola, Song Han, Matthew W Moskewicz, Khalid Ashraf, William J Dally, and Kurt Keutzer · 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.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
The lovász-softmax loss: a tractable surrogate for the optimization of the intersection-over-union measure in neural networks
Maxim Berman, Amal Rannen Triki, and Matthew B Blaschko · 2018
Earlier work this paper cites.
Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
Earlier work this paper cites.
Progressive neural architecture search
Chenxi Liu, Barret Zoph, Maxim Neumann, Jonathon Shlens, Wei Hua, Li-Jia Li, Li Fei-Fei, Alan Yuille, Jonathan Huang, and Kevin Murphy · 2018
Earlier work this paper cites.
Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
Earlier work this paper cites.
3d segmentation with exponential logarithmic loss for highly unbalanced object sizes
Ken CL Wong, Mehdi Moradi, Hui Tang, and Tanveer Syeda-Mahmood · 2018
Earlier work this paper cites.
Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud
Bichen Wu, Alvin Wan, Xiangyu Yue, and Kurt Keutzer · 2018
Cited alongside, same era.
An end-to-end deep learning architecture for graph classification
Muhan Zhang, Zhicheng Cui, Marion Neumann, and Yixin Chen · 2018
Cited alongside, same era.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
Cited alongside, same era.
Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jürgen Gall · 2019
Cited alongside, same era.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
Later among the works it cites.
Mvlidarnet: Real-time multi-class scene understanding for autonomous driving using multiple views
Ke Chen, Ryan Oldja, Nikolai Smolyanskiy, Stan Birchfield, Alexander Popov, David Wehr, Ibrahim Eden, and Joachim Pehserl · 2020
Later among the works it cites.
Salsanext: Fast semantic segmentation of lidar point clouds for autonomous driving
Tiago Cortinhal, George Tzelepis, and Eren Erdal Aksoy · 2020
Later among the works it cites.
Bayesian spatial kernel smoothing for scalable dense semantic mapping
Lu Gan, Ray Zhang, Jessy W Grizzle, Ryan M Eustice, and Maani Ghaffari · 2020
Later among the works it cites.
Randla-net: Efficient semantic segmentation of large-scale point clouds
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Jie Li, Yu Liu, Xia Yuan, Chunxia Zhao, Roland Siegwart, Ian Reid, and Cesar Cadena · 2019
Cited alongside, same era.
Relation-shape convolutional neural network for point cloud analysis
Yongcheng Liu, Bin Fan, Shiming Xiang, and Chunhong Pan · 2019
Cited alongside, same era.
Rangenet++: Fast and accurate lidar semantic segmentation
Andres Milioto, Ignacio Vizzo, Jens Behley, and Cyrill Stachniss · 2019
Cited alongside, same era.
Kpconv: Flexible and deformable convolution for point clouds
Hugues Thomas, Charles R Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J Guibas · 2019
Cited alongside, same era.
Voxsegnet: Volumetric cnns for semantic part segmentation of 3d shapes
Zongji Wang and Feng Lu · 2019
Cited alongside, same era.
Squeezesegv2: Improved model structure and unsupervised domain adaptation for road-object segmentation from a lidar point cloud
Bichen Wu, Xuanyu Zhou, Sicheng Zhao, Xiangyu Yue, and Kurt Keutzer · 2019
Cited alongside, same era.
Salsanet: Fast road and vehicle segmentation in lidar point clouds for autonomous driving
Eren Erdal Aksoy, Saimir Baci, and Selcuk Cavdar · 2020
Cited alongside, same era.
Kprnet: Improving projection-based lidar semantic segmentation
Deyvid Kochanov, Fatemeh Karimi Nejadasl, and Olaf Booij · 2020
Later among the works it cites.
Ggm-net: Graph geometric moments convolution neural network for point cloud shape classification
Dilong Li, Xin Shen, Yongtao Yu, Haiyan Guan, Hanyun Wang, and Deren Li · 2020
Later among the works it cites.
Latticenet: Fast point cloud segmentation using permutohedral lattices
Radu Alexandru Rosu, Peer Schütt, Jan Quenzel, and Sven Behnke · 2020
Later among the works it cites.
Searching efficient 3d architectures with sparse point-voxel convolution
Haotian* Tang, Zhijian* Liu, Shengyu Zhao, Yujun Lin, Ji Lin, Hanrui Wang, and Song Han · 2020
Later among the works it cites.
Squeezesegv3: Spatially-adaptive convolution for efficient point-cloud segmentation, 2020
Chenfeng Xu, Bichen Wu, Zining Wang, Wei Zhan, Peter Vajda, Kurt Keutzer, and Masayoshi Tomizuka · 2020
Later among the works it cites.
Deep fusionnet for point cloud semantic segmentation
Feihu Zhang, Jin Fang, Benjamin Wah, and Philip Torr · 2020
Later among the works it cites.
Polarnet: An improved grid representation for online lidar point clouds semantic segmentation
Yang Zhang, Zixiang Zhou, Philip David, Xiangyu Yue, Zerong Xi, Boqing Gong, and Hassan Foroosh · 2020
Later among the works it cites.
Cylinder3d: An effective 3d framework for driving-scene lidar semantic segmentation
Hui Zhou, Xinge Zhu, Xiao Song, Yuexin Ma, Zhe Wang, Hongsheng Li, and Dahua Lin · 2020
Later among the works it cites.