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Semantic segmentation of large-scale outdoor point clouds is essential for urban scene understanding in various applications, especially autonomous driving and urban high-definition (HD) mapping.
Contextual classification with functional max-margin markov networks
Daniel Munoz, J Andrew Bagnell, Nicolas Vandapel, and Martial Hebert · 2009
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Autonomous driving in urban environments: approaches, lessons and challenges
Mark Campbell, Magnus Egerstedt, Jonathan P How, and Richard M Murray · 2010
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Towards fully autonomous driving: Systems and algorithms
Jesse Levinson, Jake Askeland, Jan Becker, Jennifer Dolson, David Held, Soeren Kammel, J Zico Kolter, Dirk Langer, Oliver Pink, Vaughan Pratt, et al · 2011
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Fabio Remondino · 2011
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Unbiased look at dataset bias
Antonio Torralba and Alexei A Efros · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Stereopolis ii: A multi-purpose and multi-sensor 3d mobile mapping system for street visualisation and 3d metrology
Nicolas Paparoditis, Jean-Pierre Papelard, Bertrand Cannelle, Alexandre Devaux, Bahman Soheilian, Nicolas David, and Erwann Houzay · 2012
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3d object proposals for accurate object class detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G Berneshawi, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2015
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Voxnet: A 3d convolutional neural network for real-time object recognition
Daniel Maturana and Sebastian Scherer · 2015
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Vision-based offline-online perception paradigm for autonomous driving
German Ros, Sebastian Ramos, Manuel Granados, Amir Bakhtiary, David Vázquez, and Antonio M Lopez · 2015
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Multi-view convolutional neural networks for 3d shape recognition
Hang Su, Subhransu Maji, Evangelos Kalogerakis, and Erik Learned-Miller · 2015
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Terramobilita/iqmulus urban point cloud analysis benchmark
Bruno Vallet, Mathieu Brédif, Andrés Serna, Beatriz Marcotegui, and Nicolas Paparoditis · 2015
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Hierarchical extraction of urban objects from mobile laser scanning data
Bisheng Yang, Zhen Dong, Gang Zhao, and Wenxia Dai · 2015
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Review of automatic feature extraction from high-resolution optical sensor data for uav-based cadastral mapping
Sophie Crommelinck, Rohan Bennett, Markus Gerke, Francesco Nex, Michael Ying Yang, and George Vosselman · 2016
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Point cloud labeling using 3d convolutional neural network
Jing Huang and Suya You · 2016
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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
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Unstructured point cloud semantic labeling using deep segmentation networks
Alexandre Boulch, Bertrand Le Saux, and Nicolas Audebert · 2017
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Deep learning with geodesic moments for 3d shape classification
Lorenzo Luciano and A Ben Hamza · 2018
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Paris-lille-3d: A large and high-quality ground-truth urban point cloud dataset for automatic segmentation and classification
Xavier Roynard, Jean-Emmanuel Deschaud, and François Goulette · 2018
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Dels-3d: Deep localization and segmentation with a 3d semantic map
Peng Wang, Ruigang Yang, Binbin Cao, Wei Xu, and Yuanqing Lin · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 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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Gil Elbaz, Tamar Avraham, and Anath Fischer · 2017
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SEMANTIC3D.NET: A new large-scale point cloud classification benchmark
Timo Hackel, N. Savinov, L. Ladicky, Jan D. Wegner, K. Schindler, and M. Pollefeys · 2017
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A review of supervised object-based land-cover image classification
Lei Ma, Manchun Li, Xiaoxue Ma, Liang Cheng, Peijun Du, and Yongxue Liu · 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
Cited alongside, same era.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
Dynamic edge-conditioned filters in convolutional neural networks on graphs
Martin Simonovsky and Nikos Komodakis · 2017
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Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Cited alongside, same era.
Qingyong Hu, Bo Yang, Linhai Xie, Stefano Rosa, Yulan Guo, Zhihua Wang, Niki Trigoni, and Andrew Markham · 2019
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Tgnet: Geometric graph cnn on 3-d point cloud segmentation
Ying Li, Lingfei Ma, Zilong Zhong, Dongpu Cao, and Jonathan Li · 2019
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Multi-scale point-wise convolutional neural networks for 3d object segmentation from lidar point clouds in large-scale environments
Lingfei Ma, Ying Li, Jonathan Li, Weikai Tan, Yongtao Yu, and Michael A Chapman · 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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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
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Pointconv: Deep convolutional networks on 3d point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
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