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We present the Dayton Annotated LiDAR Earth Scan (DALES) data set, a new large-scale aerial LiDAR data set with over a half-billion hand-labeled points spanning 10 square kilometers of area and eight object categories.
K-nearest neighbor classification
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Contextual classification with functional max-margin Markov networks
Daniel Munoz, J Andrew Bagnell, Nicolas Vandapel, and Martial Hebert · 2009
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Pushmeet Kohli Nathan Silberman, Derek Hoiem and Rob Fergus · 2012
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Representing 3D shape in sparse range images for urban object classification
Alistair James Quadros · 2013
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Paris-rue-Madame database: a 3D mobile laser scanner dataset for benchmarking urban detection, segmentation and classification methods
Andrés Serna, Beatriz Marcotegui, François Goulette, and Jean-Emmanuel Deschaud · 2014
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Abdul Nurunnabi, Geoff West, and David Belton · 2015
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Sun RGB-D: A RGB-D scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 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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Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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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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Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
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PointCNN: Convolution on X-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 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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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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Matterport3D: Learning from RGB-D data in indoor environments
Angel Chang, Angela Dai, Thomas Funkhouser, Maciej Halber, Matthias Niessner, Manolis Savva, Shuran Song, Andy Zeng, and Yinda Zhang · 2017
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ScanNet: Richly-annotated 3D reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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Semantic3D. net: A new large-scale point cloud classification benchmark
Timo Hackel, Nikolay Savinov, Lubor Ladicky, Jan D Wegner, Konrad Schindler, and Marc Pollefeys · 2017
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Alexandre Boulch · 2019
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Synthcity: A large scale synthetic point cloud
David Griffiths and Jan Boehm · 2019
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KPConv: Flexible and deformable convolution for point clouds
Thomas Hugues, Charles R Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J Guibas · 2019
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ShellNet: Efficient point cloud convolutional neural networks using concentric shells statistics
Zhiyuan Zhang, Binh-Son Hua, and Sai-Kit Yeung · 2019
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