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Deep learning models are the state-of-the-art methods for semantic point cloud segmentation, the success of which relies on the availability of large-scale annotated datasets.
Normalized cuts and image segmentation
Jianbo Shi and Jitendra M. Malik · 2000
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Incorporating diversity in active learning with support vector machines
Klaus Brinker · 2003
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Multi-class active learning for image classification
Ajay J. Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos · 2009
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Metabox+: A new region based active learning method for semantic segmentation using priority maps
Pascal Colling, Lutz Roese-Koerner, Hanno Gottschalk, and Matthias Rottmann · 2010
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Dimensionality based scale selection in 3d lidar point clouds
Jérôme Demantké, Clément Mallet, Nicolas David, and Bruno Vallet · 2011
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Slice-n-swipe: A free-hand gesture user interface for 3d point cloud annotation
F. Bacim, M. Nabiyouni, and D. A. Bowman · 2014
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Touching the cloud: Bimanual annotation of immersive point clouds
P. Lubos, R. Beimler, M. Lammers, and F. Steinicke · 2014
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Smartannotator: An interactive tool for annotating RGBD indoor images
Yu-Shiang Wong, Hung-Kuo Chu, and Niloy J. Mitra · 2014
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3d shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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3d semantic parsing of large-scale indoor spaces
Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
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A scalable active framework for region annotation in 3d shape collections
Li Yi, Vladimir G Kim, Duygu Ceylan, I Shen, Mengyan Yan, Hao Su, Cewu Lu, Qixing Huang, Alla Sheffer, Leonidas Guibas, et al · 2016
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Multi-label point cloud annotation by selection of sparse control points
R. Monica, J. Aleotti, M. Zillich, and M. Vincze · 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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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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Active learning for convolutional neural networks: A core-set approach
Ozan Sener and Silvio Savarese · 2017
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Adversarial active learning for deep networks: a margin based approach
Melanie Ducoffe and Frederic Precioso · 2018
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Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding
Kaichun Mo, Shilin Zhu, Angel X Chang, Li Yi, Subarna Tripathi, Leonidas J Guibas, and Hao Su · 2019
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Deep hough voting for 3d object detection in point clouds
Charles R Qi, Or Litany, Kaiming He, and Leonidas J Guibas · 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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Pointatme: Efficient 3d point cloud labeling in virtual reality
F. Wirth, J. Quehl, J. Ota, and C. Stiller · 2019
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3d point capsule networks
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Jiaxin Li, Ben M Chen, and Gim Hee Lee · 2018
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On learning and learned representation by capsule networks
Ancheng Lin, Jun Li, and Zhenyuan Ma · 2018
Cited alongside, same era.
Cereals-cost-effective region-based active learning for semantic segmentation
Radek Mackowiak, Philip Lenz, Omair Ghori, Ferran Diego, Oliver Lange, and Carsten Rother · 2018
Cited alongside, same era.
Partnet: A large-scale benchmark for fine-grained and hierarchical part-level 3d object understanding, 2018
Kaichun Mo, Shilin Zhu, Angel X. Chang, Li Yi, Subarna Tripathi, Leonidas J. Guibas, and Hao Su · 2018
Cited alongside, same era.
4d spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
Cited alongside, same era.
Unsupervised multi-task feature learning on point clouds
K. Hassani and M. Haley · 2019
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Yongheng Zhao, Tolga Birdal, Haowen Deng, and Federico Tombari · 2019
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Weakly supervised 3d object detection from point clouds
Zengyi Qin, Jinglu Wang, and Yan Lu · 2020
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A survey of deep active learning
Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, and Xin Wang · 2020
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Multi-path region mining for weakly supervised 3d semantic segmentation on point clouds
Jiacheng Wei, Guosheng Lin, Kim-Hui Yap, Tzu-Yi Hung, and Lihua Xie · 2020
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Pointcontrast: Unsupervised pre-training for 3d point cloud understanding
Saining Xie, Jiatao Gu, Demi Guo, Charles R Qi, Leonidas J Guibas, and Or Litany · 2020
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Weakly supervised semantic point cloud segmentation: Towards 10x fewer labels
Xun Xu and Gim Hee Lee · 2020
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