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State-of-the-art methods for large-scale driving-scene LiDAR segmentation often project the point clouds to 2D space and then process them via 2D convolution.
Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
3d u-net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
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3d graph neural networks for rgbd semantic segmentation
Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, and Raquel Urtasun · 2017
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Segcloud: Semantic segmentation of 3d point clouds
Lyne Tchapmi, Christopher Choy, Iro Armeni, JunYoung Gwak, and Silvio Savarese · 2017
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Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio · 2017
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Pyramid scene parsing network
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia · 2017
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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
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
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Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
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Tangent convolutions for dense prediction in 3d
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, and Qian-Yi Zhou · 2018
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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
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Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
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Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Jurgen Gall · 2019
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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 · 2019
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Acnet: Strengthening the kernel skeletons for powerful cnn via asymmetric convolution blocks
Xiaohan Ding, Yuchen Guo, Guiguang Ding, and Jungong Han · 2019
Cited alongside, same era.
Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019
Cited alongside, same era.
Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Cited alongside, same era.
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
Chenxi Liu, Liang-Chieh Chen, Florian Schroff, Hartwig Adam, Wei Hua, Alan L Yuille, and Li Fei-Fei · 2019
Cited alongside, same era.
Vv-net: Voxel vae net with group convolutions for point cloud segmentation
Hsien-Yu Meng, Lin Gao, Yu-Kun Lai, and Dinesh Manocha · 2019
Cited alongside, same era.
Rangenet++: Fast and accurate lidar semantic segmentation
3d-mpa: Multi-proposal aggregation for 3d semantic instance segmentation
Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe, and Matthias Nießner · 2020
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Tornado-net: multiview total variation semantic segmentation with diamond inception module
Martin Gerdzhev, Ryan Razani, Ehsan Taghavi, and Bingbing Liu · 2020
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Occuseg: Occupancy-aware 3d instance segmentation
Lei Han, Tian Zheng, Lan Xu, and Lu Fang · 2020
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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
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Pointgroup: Dual-set point grouping for 3d instance segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, and Jiaya Jia · 2020
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Andres Milioto, Ignacio Vizzo, Jens Behley, and Cyrill Stachniss · 2019
Cited alongside, same era.
Jsis3d: joint semantic-instance segmentation of 3d point clouds with multi-task pointwise networks and multi-value conditional random fields
Quang-Hieu Pham, Thanh Nguyen, Binh-Son Hua, Gemma Roig, and Sai-Kit Yeung · 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.
Graph attention convolution for point cloud semantic segmentation
Lei Wang, Yuchun Huang, Yaolin Hou, Shenman Zhang, and Jie Shan · 2019
Cited alongside, same era.
Shape robust text detection with progressive scale expansion network
Wenhai Wang, Enze Xie, Xiang Li, Wenbo Hou, Tong Lu, Gang Yu, and Shuai Shao · 2019
Cited alongside, same era.
Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 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.
Deyvid Kochanov, Fatemeh Karimi Nejadasl, and Olaf Booij · 2020
Closest in time.
Learning to segment 3d point clouds in 2d image space
Yecheng Lyu, Xinming Huang, and Ziming Zhang · 2020
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LiDAR Panoptic Segmentation for Autonomous Driving
A. Milioto, J. Behley, C. McCool, and C. Stachniss · 2020
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Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2020
Closest in time.
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
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Reconfigurable voxels: A new representation for lidar-based point clouds
Tai Wang, Xinge Zhu, and Dahua Lin · 2020
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Squeezesegv3: Spatially-adaptive convolution for efficient point-cloud segmentation
Chenfeng Xu, Bichen Wu, Zining Wang, Wei Zhan, Peter Vajda, Kurt Keutzer, and Masayoshi Tomizuka · 2020
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Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Xu Yan, Chaoda Zheng, Zhen Li, Sheng Wang, and Shuguang Cui · 2020
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Deep fusionnet for point cloud semantic segmentation
Feihu Zhang, Jin Fang, Benjamin Wah, and Philip Torr · 2020
Closest in time.
Fusion-aware point convolution for online semantic 3d scene segmentation
Jiazhao Zhang, Chenyang Zhu, Lintao Zheng, and Kai Xu · 2020
Closest in time.
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
Closest in time.
Ssn: Shape signature networks for multi-class object detection from point clouds
Xinge Zhu, Yuexin Ma, Tai Wang, Yan Xu, Jianping Shi, and Dahua Lin · 2020
Closest in time.