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The success of deep learning heavily relies on large-scale data with comprehensive labels, which is more expensive and time-consuming to fetch in 3D compared to 2D images or natural languages.
Histograms of oriented gradients for human detection
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Model compression
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Diederik P. Kingma and Max Welling · 2014
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Angel X. Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Geoffrey E. Hinton, Oriol Vinyals, and Jeffrey Dean · 2015
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Yann LeCun, Yoshua Bengio, and Geoffrey E. Hinton · 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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Alexey Dosovitskiy, Philipp Fischer, Jost Tobias Springenberg, Martin A. Riedmiller, and Thomas Brox · 2016
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, and Kilian Q. Weinberger · 2016
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Mehdi Noroozi and Paolo Favaro · 2016
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Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
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Representation learning with contrastive predictive coding
Aäron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X. Yu, and Dahua Lin · 2018
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Spidercnn: Deep learning on point sets with parameterized convolutional filters
Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, and Yu Qiao · 2018
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Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Learning deep representations by mutual information estimation and maximization
R. Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, and Yoshua Bengio · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Pavlin G. Poličar, Martin Stražar, and Blaž Zupan · 2019
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Charles R. Qi, Or Litany, Kaiming He, and Leonidas J. Guibas · 2019
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Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
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Jonathan Sauder and Bjarne Sievers · 2019
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MVTN: multi-view transformation network for 3d shape recognition
Abdullah Hamdi, Silvio Giancola, and Bernard Ghanem · 2021
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Exploring data-efficient 3d scene understanding with contrastive scene contexts
Ji Hou, Benjamin Graham, Matthias Nießner, and Saining Xie · 2021
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Siyuan Huang, Yichen Xie, Song-Chun Zhu, and Yixin Zhu · 2021
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Dense-resolution network for point cloud classification and segmentation
Shi Qiu, Saeed Anwar, and Nick Barnes · 2021
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Hugues Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, Beatriz Marcotegui, François Goulette, and Leonidas J. Guibas · 2019
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Trieu H. Trinh, Minh-Thang Luong, and Quoc V. Le · 2019
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Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, and Justin M. Solomon · 2019
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