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LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment.
Building an efficient hash table on the gpu
Dan A Alcantara, Vasily Volkov, Shubhabrata Sengupta, Michael Mitzenmacher, John D Owens, and Nina Amenta · 2012
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Diederik P Kingma and Jimmy Ba · 2014
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The pascal visual object classes challenge: A retrospective
Mark Everingham, SM Ali Eslami, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2015
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Hyeonwoo Noh, Seunghoon Hong, and Bohyung Han · 2015
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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
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Enet: A deep neural network architecture for real-time semantic segmentation
Adam Paszke, Abhishek Chaurasia, Sangpil Kim, and Eugenio Culurciello · 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 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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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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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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3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens Van Der Maaten · 2018
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Yolov3: An incremental improvement
Joseph Redmon and Ali Farhadi · 2018
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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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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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Suma++: Efficient lidar-based semantic slam
Xieyuanli Chen, Andres Milioto, Emanuele Palazzolo, Philippe Giguere, Jens Behley, and Cyrill Stachniss · 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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RangeNet ++: Fast and Accurate LiDAR Semantic Segmentation
Andres Milioto, Ignacio Vizzo, Jens Behley, and Cyrill Stachniss · 2019
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Pointconv: Deep convolutional networks on 3d point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 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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Pointweb: Enhancing local neighborhood features for point cloud processing
Hengshuang Zhao, Li Jiang, Chi-Wing Fu, and Jiaya Jia · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, et al · 2019
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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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Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds
Tiago Cortinhal, George Tzelepis, and Eren Erdal Aksoy · 2020
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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
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Cenet: Toward concise and efficient lidar semantic segmentation for autonomous driving
Hui-Xian Cheng, Xian-Feng Han, and Guo-Qiang Xiao · 2022
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Fast point transformer
Chunghyun Park, Yoonwoo Jeong, Minsu Cho, and Jaesik Park · 2022
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Stratified transformer for 3d point cloud segmentation
Xin Lai, Jianhui Liu, Li Jiang, Liwei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, and Jiaya Jia · 2022
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Translo: A window-based masked point transformer framework for large-scale lidar odometry
Jiuming Liu, Guangming Wang, Chaokang Jiang, Zhe Liu, and Hesheng Wang · 2023
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End-to-end 2d-3d registration between image and lidar point cloud for vehicle localization
Guangming Wang, Yu Zheng, Yanfeng Guo, Zhe Liu, Yixiang Zhu, Wolfram Burgard, and Hesheng Wang · 2023
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Deyvid Kochanov, Fatemeh Karimi Nejadasl, and Olaf Booij · 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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Multi projection fusion for real-time semantic segmentation of 3d lidar point clouds
Yara Ali Alnaggar, Mohamed Afifi, Karim Amer, and Mohamed ElHelw · 2021
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Lite-hdseg: Lidar semantic segmentation using lite harmonic dense convolutions
Ryan Razani, Ran Cheng, Ehsan Taghavi, and Liu Bingbing · 2021
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2-s3net: Attentive feature fusion with adaptive feature selection for sparse semantic segmentation network
Ran Cheng, Ryan Razani, Ehsan Taghavi, Enxu Li, and Bingbing Liu · 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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Drinet: A dual-representation iterative learning network for point cloud segmentation
Maosheng Ye, Shuangjie Xu, Tongyi Cao, and Qifeng Chen · 2021
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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
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Spherical transformer for lidar-based 3d recognition
Xin Lai, Yukang Chen, Fanbin Lu, Jianhui Liu, and Jiaya Jia · 2023
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Pointconvformer: Revenge of the point-based convolution
Wenxuan Wu, Li Fuxin, and Qi Shan · 2023
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Exploring dual representations in large-scale point clouds: A simple weakly supervised semantic segmentation framework
Jiaming Liu, Yue Wu, Maoguo Gong, Qiguang Miao, Wenping Ma, and Cai Xu · 2023
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Regformer: an efficient projection-aware transformer network for large-scale point cloud registration
Jiuming Liu, Guangming Wang, Zhe Liu, Chaokang Jiang, Marc Pollefeys, and Hesheng Wang · 2023
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Jiuming Liu, Dong Zhuo, Zhiheng Feng, Siting Zhu, Chensheng Peng, Zhe Liu, and Hesheng Wang · 2024
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Semgauss-slam: Dense semantic gaussian splatting slam
Siting Zhu, Renjie Qin, Guangming Wang, Jiuming Liu, and Hesheng Wang · 2024
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Sni-slam: Semantic neural implicit slam
Siting Zhu, Guangming Wang, Hermann Blum, Jiuming Liu, Liang Song, Marc Pollefeys, and Hesheng Wang · 2024
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Sgs-slam: Semantic gaussian splatting for neural dense slam
Mingrui Li, Shuhong Liu, Heng Zhou, Guohao Zhu, Na Cheng, Tianchen Deng, and Hongyu Wang · 2024
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Emie-map: Large-scale road surface reconstruction based on explicit mesh and implicit encoding
Wenhua Wu, Qi Wang, Guangming Wang, Junping Wang, Tiankun Zhao, Yang Liu, Dongchao Gao, Zhe Liu, and Hesheng Wang · 2024
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Sfpnet: Sparse focal point network for semantic segmentation on general lidar point clouds
Yanbo Wang, Wentao Zhao, Chuan Cao, Tianchen Deng, Jingchuan Wang, and Weidong Chen · 2024
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Vision mamba: Efficient visual representation learning with bidirectional state space model
Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, and Xinggang Wang · 2024
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Joint semantic segmentation using representations of lidar point clouds and camera images
Yue Wu, Jiaming Liu, Maoguo Gong, Qiguang Miao, Wenping Ma, and Cai Xu · 2024
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Difflow3d: Toward robust uncertainty-aware scene flow estimation with iterative diffusion-based refinement
Jiuming Liu, Guangming Wang, Weicai Ye, Chaokang Jiang, Jinru Han, Zhe Liu, Guofeng Zhang, Dalong Du, and Hesheng Wang · 2024
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