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The rapid progress in 3D scene understanding has come with growing demand for data; however, collecting and annotating 3D scenes (e.g.
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3D shape matching with 3D shape contexts
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Imagenet: A large-scale hierarchical image database
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Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2013
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A category-level 3d object dataset: Putting the kinect to work
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SUN3D: A database of big spaces reconstructed using sfm and object labels
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Rich feature hierarchies for accurate object detection and semantic segmentation
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Microsoft COCO: Common objects in context
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Sliding shapes for 3D object detection in depth images
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ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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U-Net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 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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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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Volumetric and multi-view cnns for object classification on 3D data
Charles Ruizhongtai Qi, Hao Su, Matthias Nießner, Angela Dai, Mengyuan Yan, and Leonidas Guibas · 2016
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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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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 R Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
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Segcloud: Semantic segmentation of 3D point clouds
Lyne Tchapmi, Christopher Choy, Iro Armeni, JunYoung Gwak, and Silvio Savarese · 2017
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Learning representations and generative models for 3D point clouds
Panos Achlioptas, Olga Diamanti, Ioannis Mitliagkas, and Leonidas Guibas · 2018
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Multiresolution tree networks for 3D point cloud processing
Matheus Gadelha, Rui Wang, and Subhransu Maji · 2018
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3D semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
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A papier-mâché approach to learning 3D surface generation
Thibault Groueix, Matthew Fisher, Vladimir G Kim, Bryan C Russell, and Mathieu Aubry · 2018
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SO-Net: Self-organizing network for point cloud analysis
Jiaxin Li, Ben M Chen, and Gim Hee Lee · 2018
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Tags2Parts: Discovering semantic regions from shape tags
Sanjeev Muralikrishnan, Vladimir G Kim, and Siddhartha Chaudhuri · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Frustum pointnets for 3D object detection from RGB-D data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
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Sgpn: Similarity group proposal network for 3d point cloud instance segmentation
PointConv: Deep convolutional networks on 3D point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
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Learning object bounding boxes for 3D instance segmentation on point clouds
Bo Yang, Jianan Wang, Ronald Clark, Qingyong Hu, Sen Wang, Andrew Markham, and Niki Trigoni · 2019
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GSPN: Generative shape proposal network for 3D instance segmentation in point cloud
Li Yi, Wang Zhao, He Wang, Minhyuk Sung, and Leonidas Guibas · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Unsupervised learning of visual features by contrasting cluster assignments
Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin · 2020
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Weiyue Wang, Ronald Yu, Qiangui Huang, and Ulrich Neumann · 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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Attentional shapecontextnet for point cloud recognition
Saining Xie, Sainan Liu, Zeyu Chen, and Zhuowen Tu · 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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Learning representations by maximizing mutual information across views
Philip Bachman, R Devon Hjelm, and William Buchwalter · 2019
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BAE-Net: Branched autoencoder for shape co-segmentation
Zhiqin Chen, Kangxue Yin, Matthew Fisher, Siddhartha Chaudhuri, and Hao Zhang · 2019
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4D spatio-temporal convnets: Minkowski convolutional neural networks
Christopher Choy, JunYoung Gwak, and Silvio Savarese · 2019
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Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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3D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation
Francis Engelmann, Martin Bokeloh, Alireza Fathi, Bastian Leibe, and Matthias Nießner · 2020
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Label-efficient learning on point clouds using approximate convex decompositions
Matheus Gadelha, Aruni RoyChowdhury, Gopal Sharma, Evangelos Kalogerakis, Liangliang Cao, Erik Learned-Miller, Rui Wang, and Subhransu Maji · 2020
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Bootstrap your own latent-a new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Generative sparse detection networks for 3D single-shot object detection
JunYoung Gwak, Christopher Choy, and Silvio Savarese · 2020
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OccuSeg: Occupancy-aware 3D instance segmentation
Lei Han, Tian Zheng, Lan Xu, and Lu Fang · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Data-efficient image recognition with contrastive predictive coding
Olivier J Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, SM Eslami, and Aaron van den Oord · 2020
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RevealNet: Seeing Behind Objects in RGB-D Scans
Ji Hou, Angela Dai, and Matthias Nießner · 2020
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End-to-End 3D Point Cloud Instance Segmentation Without Detection
Haiyong Jiang, Feilong Yan, Jianfei Cai, Jianmin Zheng, and Jun Xiao · 2020
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PointGroup: Dual-Set Point Grouping for 3D Instance Segmentation
Li Jiang, Hengshuang Zhao, Shaoshuai Shi, Shu Liu, Chi-Wing Fu, and Jiaya Jia · 2020
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Self-supervised learning of pretext-invariant representations
Ishan Misra and Laurens van der Maaten · 2020
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Imvotenet: Boosting 3D object detection in point clouds with image votes
Charles R Qi, Xinlei Chen, Or Litany, and Leonidas J Guibas · 2020
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Info3D: Representation learning on 3D objects using mutual information maximization and contrastive learning
Aditya Sanghi · 2020
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Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, and Dragomir Anguelov · 2020
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Contrastive multiview coding
Yonglong Tian, Dilip Krishnan, and Phillip Isola · 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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AdaCoSeg: Adaptive shape co-segmentation with group consistency loss
Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Li Yi, Leonidas J Guibas, and Hao Zhang · 2020
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