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LiDAR segmentation is crucial for autonomous driving perception.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Fully convolutional networks for semantic segmentation
Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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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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Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Super-convergence: Very fast training of neural networks using large learning rates
Leslie N. Smith and Nicholay Topin · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin · 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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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 · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 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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Semantickitti: A dataset for semantic scene understanding of lidar sequences
Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, and Juergen Gall · 2019
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4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Panoptic segmentation
Alexander Kirillov, Kaiming He, Ross Girshick, Carsten Rother, and Piotr Dollár · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Point-voxel cnn for efficient 3d deep learning
Zhijian Liu, Haotian Tang, Yujun Lin, and Song Han · 2019
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Rangenet++: Fast and accurate lidar semantic segmentation
Andres Milioto, Ignacio Vizzo, Jens Behley, and Cyrill Stachniss · 2019
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Seamless scene segmentation
Lorenzo Porzi, Samuel Rota Bulo, Aleksander Colovic, and Peter Kontschieder · 2019
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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
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Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2019
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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
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Salsanet: Fast road and vehicle segmentation in lidar point clouds for autonomous driving
Eren Erdal Aksoy, Saimir Baci, and Selcuk Cavdar · 2020
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3d-mininet: Learning a 2d representation from point clouds for fast and efficient 3d lidar semantic segmentation
Iñigo Alonso, Luis Riazuelo, Luis Montesano, and Ana C Murillo · 2020
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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 · 2020
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Pointmixup: Augmentation for point clouds
Yunlu Chen, Vincent Tao Hu, Efstratios Gavves, Thomas Mensink, Pascal Mettes, Pengwan Yang, and Cees GM Snoek · 2020
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Panoptic-deeplab: A simple, strong, and fast baseline for bottom-up panoptic segmentation
Bowen Cheng, Maxwell D. Collins, Yukun Zhu, Ting Liu, Thomas S. Huang, and Hartwig Adam · 2020
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Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds
Tiago Cortinhal, George Tzelepis, and Eren Erdal Aksoy · 2020
Cited alongside, same era.
Deep learning for 3d point clouds: A survey
Yulan Guo, Hanyun Wang, Qingyong Hu, Hao Liu, Li Liu, and Mohammed Bennamoun · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Kprnet: Improving projection-based lidar semantic segmentation
Deyvid Kochanov, Fatemeh Karimi Nejadasl, and Olaf Booij · 2020
Cited alongside, same era.
Deep learning for lidar point clouds in autonomous driving: A review
Ying Li, Lingfei Ma, Zilong Zhong, Fei Liu, Michael A Chapman, Dongpu Cao, and Jonathan Li · 2020
Cited alongside, same era.
K-net: Towards unified image segmentation
Wenwei Zhang, Jiangmiao Pang, Kai Chen, and Chen Change Loy · 2021
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Fidnet: Lidar point cloud semantic segmentation with fully interpolation decoding
Yiming Zhao, Lin Bai, and Xinming Huang · 2021
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Panoptic-polarnet: Proposal-free lidar point cloud panoptic segmentation
Zixiang Zhou, Yang Zhang, and Hassan Foroosh · 2021
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Cylindrical and asymmetrical 3d convolution networks for lidar segmentation
Xinge Zhu, Hui Zhou, Tai Wang, Fangzhou Hong, Yuexin Ma, Wei Li, Hongsheng Li, and Dahua Lin · 2021
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Perception-aware multi-sensor fusion for 3d lidar semantic segmentation
Zhuangwei Zhuang, Rong Li, Kui Jia, Qicheng Wang, Yuanqing Li, and Mingkui Tan · 2021
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Cenet: Toward concise and efficient lidar semantic segmentation for autonomous driving
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Venice Erin Liong, Thi Ngoc Tho Nguyen, Sergi Widjaja, Dhananjai Sharma, and Zhuang Jie Chong · 2020
Cited alongside, same era.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, and Benjamin Caine · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Scan-based semantic segmentation of lidar point clouds: An experimental study
Larissa T Triess, David Peter, Christoph B Rist, and J Marius Zöllner · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Deep fusionnet for point cloud semantic segmentation
Feihu Zhang, Jin Fang, Benjamin Wah, and Philip Torr · 2020
Cited alongside, same era.
Polarnet: An improved grid representation for online lidar point clouds semantic segmentation
Yang Zhang, Zixiang Zhou, Philip David, Xiangyu Yue, Zerong Xi, and Hassan Foroosh · 2020
Cited alongside, same era.
Huixian Cheng, Xianfeng Han, and Guoqiang Xiao · 2022
Later among the works it cites.
Panoptic nuscenes: A large-scale benchmark for lidar panoptic segmentation and tracking
Whye Kit Fong, Rohit Mohan, Juana Valeria Hurtado, Lubing Zhou, Holger Caesar, Oscar Beijbom, and Abhinav Valada · 2022
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Maskrange: A mask-classification model for range-view based lidar segmentation
Yi Gu, Yuming Huang, Chengzhong Xu, and Hui Kong · 2022
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Unified 3d and 4d panoptic segmentation via dynamic shifting network
Fangzhou Hong, Lingdong Kong, Hui Zhou, Xinge Zhu, Hongsheng Li, and Ziwei Liu · 2022
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Point-to-voxel knowledge distillation for lidar semantic segmentation
Yuenan Hou, Xinge Zhu, Yuexin Ma, Chen Change Loy, and Yikang Li · 2022
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Self-distillation for robust lidar semantic segmentation in autonomous driving
Jiale Li, Hang Dai, and Yong Ding · 2022
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Panoptic-phnet: Towards real-time and high-precision lidar panoptic segmentation via clustering pseudo heatmap
Jinke Li, Xiao He, Yang Wen, Yuan Gao, Xiaoqiang Cheng, and Dan Zhang · 2022
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Gfnet: Geometric flow network for 3d point cloud semantic segmentation
Haibo Qiu, Baosheng Yu, and Dacheng Tao · 2022
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Benchmarking and analyzing point cloud classification under corruptions
Jiawei Ren, Liang Pan, and Ziwei Liu · 2022
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Efficientlps: Efficient lidar panoptic segmentation
Kshitij Sirohi, Rohit Mohan, Daniel Büscher, Wolfram Burgard, and Abhinav Valada · 2022
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Point cloud semantic segmentation using multi-scale sparse convolution neural network
Yunzheng Su, Lei Jiang, and Jie Cao · 2022
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Fully convolutional one-stage 3d object detection on lidar range images
Zhi Tian, Xiangxiang Chu, Xiaoming Wang, Xiaolin Wei, and Chunhua Shen · 2022
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Analyzing deep learning representations of point clouds for real-time in-vehicle lidar perception
Marc Uecker, Tobias Fleck, Marcel Pflugfelder, and J. Marius Zöllner · 2022
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Scribble-supervised lidar semantic segmentation
Ozan Unal, Dengxin Dai, and Luc Van Gool · 2022
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2dpass: 2d priors assisted semantic segmentation on lidar point clouds
Xu Yan, Jiantao Gao, Chaoda Zheng, Chao Zheng, Ruimao Zhang, Shuguang Cui, and Zhen Li · 2022
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LidarmultiNet: Towards a unified multi-task network for lidar perception
Dongqiangzi Ye, Zixiang Zhou, Weijia Chen, Yufei Xie, Yu Wang, Panqu Wang, and Hassan Foroosh · 2022
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Efficient point cloud segmentation with geometry-aware sparse networks
Maosheng Ye, Rui Wan, Shuangjie Xu, Tongyi Cao, and Qifeng Chen · 2022
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Pointcutmix: Regularization strategy for point cloud classification
Jinlai Zhang, Lyujie Chen, Bo Ouyang, Binbin Liu, Jihong Zhu, Yujin Chen, Yanmei Meng, and Danfeng Wu · 2022
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Svaseg: Sparse voxel-based attention for 3d lidar point cloud semantic segmentation
Lin Zhao, Siyuan Xu, Liman Liu, Delie Ming, and Wenbing Tao · 2022
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Rangevit: Towards vision transformers for 3d semantic segmentation in autonomous driving
Angelika Ando, Spyros Gidaris, Andrei Bursuc, Gilles Puy, Alexandre Boulch, and Renaud Marlet · 2023
Closest in time.
Clip2scene: Towards label-efficient 3d scene understanding by clip
Runnan Chen, Youquan Liu, Lingdong Kong, Xinge Zhu, Yuexin Ma, Yikang Li, Yuenan Hou, Yu Qiao, and Wenping Wang · 2023
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Conda: Unsupervised domain adaptation for lidar segmentation via regularized domain concatenation
Lingdong Kong, Niamul Quader, and Venice Erin Liong · 2023
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Lasermix for semi-supervised lidar semantic segmentation
Lingdong Kong, Jiawei Ren, Liang Pan, and Ziwei Liu · 2023
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Pcscnet: Fast 3d semantic segmentation of lidar point cloud for autonomous car using point convolution and sparse convolution network
Jaehyun Park, Chansoo Kim, Soyeong Kim, and Kichun Jo · 2023
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