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We propose an unsupervised method for parsing large 3D scans of real-world scenes with easily-interpretable shapes.
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LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management
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Comparative testing of single-tree detection algorithms under different types of forest
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Minhyuk Sung, Vladimir G Kim, Roland Angst, and Leonidas Guibas · 2015
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Iro Armeni, Ozan Sener, Amir R Zamir, Helen Jiang, Ioannis Brilakis, Martin Fischer, and Silvio Savarese · 2016
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 2016
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Airborne LiDAR estimation of aboveground forest biomass in the absence of field inventory
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An improved method for power-line reconstruction from point cloud data
Bo Guo, Qingquan Li, Xianfeng Huang, and Chisheng Wang · 2016
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Manhattan-world urban reconstruction from point clouds
Minglei Li, Peter Wonka, and Liangliang Nan · 2016
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Dynamic FAUST: Registering human bodies in motion
Federica Bogo, Javier Romero, Gerard Pons-Moll, and Michael J Black · 2017
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Semantic segmentation of LiDAR points clouds: Rasterization beyond digital elevation models
Florent Guiotte, Minh-Tan Pham, Romain Dambreville, Thomas Corpetti, and Sébastien Lefèvre · 2020
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Object-centric learning with slot attention
Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf · 2020
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Deep Transformation-Invariant Clustering
Tom Monnier, Thibault Groueix, and Mathieu Aubry · 2020
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Learning unsupervised hierarchical part decomposition of 3D objects from a single RGB image
Despoina Paschalidou, Luc Van Gool, and Andreas Geiger · 2020
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Nikhila Ravi, Jeremy Reizenstein, David Novotny, Taylor Gordon, Wan-Yen Lo, Justin Johnson, and Georgia Gkioxari · 2020
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Arno Knapitsch, Jaesik Park, Qian-Yi Zhou, and Vladlen Koltun · 2017
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Grass: Generative recursive autoencoders for shape structures
Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, and Leonidas Guibas · 2017
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SceneNet RGB-D: Can 5M synthetic images beat generic imagenet pre-training on indoor segmentation?
John McCormac, Ankur Handa, Stefan Leutenegger, and Andrew J.Davison · 2017
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3d tree modeling from incomplete point clouds via optimization and l 1-mst
Jie Mei, Liqiang Zhang, Shihao Wu, Zhen Wang, and Liang Zhang · 2017
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Polyfit: Polygonal surface reconstruction from point clouds
Liangliang Nan and Peter Wonka · 2017
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Learning shape abstractions by assembling volumetric primitives
Shubham Tulsiani, Hao Su, Leonidas J Guibas, Alexei A Efros, and Jitendra Malik · 2017
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3D-PRNN: Generating shape primitives with recurrent neural networks
Chuhang Zou, Ersin Yumer, Jimei Yang, Duygu Ceylan, and Derek Hoiem · 2017
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DALES: A large-scale aerial LiDAR data set for semantic segmentation
Nina Varney, Vijayan K Asari, and Quinn Graehling · 2020
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Geometric primitives in LiDAR point clouds: A review
Shaobo Xia, Dong Chen, Ruisheng Wang, Jonathan Li, and Xinchang Zhang · 2020
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LASDU: A large-scale aerial LiDAR dataset for semantic labeling in dense urban areas
Zhen Ye, Yusheng Xu, Rong Huang, Xiaohua Tong, Xin Li, Xiangfeng Liu, Kuifeng Luan, Ludwig Hoegner, and Uwe Stilla · 2020
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Joint supervised and self-supervised learning for 3D real world challenges
Antonio Alliegro, Davide Boscaini, and Tatiana Tommasi · 2021
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SUM: A benchmark dataset of semantic urban meshes
Weixiao Gao, Liangliang Nan, Bas Boom, and Hugo Ledoux · 2021
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Cuboids revisited: Learning robust 3D shape fitting to single RGB images
Florian Kluger, Hanno Ackermann, Eric Brachmann, Michael Ying Yang, and Bodo Rosenhahn · 2021
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Representing shape collections with alignment-aware linear models
Romain Loiseau, Tom Monnier, Mathieu Aubry, and Loïc Landrieu · 2021
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LiDAR-HD: A 3D mapping of France’s soil and subsoil, 2021
IGN (French mapping agency) · 2021
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Unsupervised layered image decomposition into object prototypes
Tom Monnier, Elliot Vincent, Jean Ponce, and Mathieu Aubry · 2021
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Neural parts: Learning expressive 3D shape abstractions with invertible neural networks
Despoina Paschalidou, Angelos Katharopoulos, Andreas Geiger, and Sanja Fidler · 2021
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DALES objects: A large scale benchmark dataset for instance segmentation in aerial LiDAR
Nina M Singer and Vijayan K Asari · 2021
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Marionette: Self-supervised sprite learning
Dmitriy Smirnov, Michael Gharbi, Matthew Fisher, Vitor Guizilini, Alexei Efros, and Justin M Solomon · 2021
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SPConv: Spatially sparse convolution library
Spconv Contributors · 2022
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City3D: large-scale building reconstruction from airborne LiDAR point clouds
Jin Huang, Jantien Stoter, Ravi Peters, and Liangliang Nan · 2022
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Multi-layer modeling of dense vegetation from aerial lidar scans
Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet, and Nesrine Chehata · 2022
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KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2D and 3D
Yiyi Liao, Jun Xie, and Andreas Geiger · 2022
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Robust and accurate superquadric recovery: A probabilistic approach
Weixiao Liu, Yuwei Wu, Sipu Ruan, and Gregory S Chirikjian · 2022
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Monteboxfinder: Detecting and filtering primitives to fit a noisy point cloud
Michaël Ramamonjisoa, Sinisa Stekovic, and Vincent Lepetit · 2022
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Individual tree crown segmentation and crown width extraction from a heightmap derived from aerial laser scanning data using a deep learning framework
Chenxin Sun, Chengwei Huang, Huaiqing Zhang, Bangqian Chen, Feng An, Liwen Wang, and Ting Yun · 2022
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Primitive-based shape abstraction via nonparametric bayesian inference
Yuwei Wu, Weixiao Liu, Sipu Ruan, and Gregory S Chirikjian · 2022
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Unsupervised Discovery of Object Radiance Fields
Hong-Xing Yu, Leonidas J. Guibas, and Jiajun Wu · 2022
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