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Point cloud semantic segmentation often requires largescale annotated training data, but clearly, point-wise labels are too tedious to prepare.
Visualizing data using t-SNE
Laurens van der Maaten and Geoffrey Hinton · 2008
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Probabilistic graphical models: principles and techniques
Daphne Koller and Nir Friedman · 2009
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BoxSup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation
Jifeng Dai, Kaiming He, and Jian Sun · 2015
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Sparse 3D convolutional neural networks
Ben Graham · 2015
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Conditional random fields as recurrent neural networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, and Philip HS Torr · 2015
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What’s the point: Semantic segmentation with point supervision
Amy Bearman, Olga Russakovsky, Vittorio Ferrari, and Li Fei-Fei · 2016
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Temporal ensembling for semi-supervised learning
Samuli Laine and Timo Aila · 2016
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ScribbleSup: Scribble-supervised convolutional networks for semantic segmentation
Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, and Jian Sun · 2016
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Augmented feedback in semantic segmentation under image level supervision
Xiaojuan Qi, Zhengzhe Liu, Jianping Shi, Hengshuang Zhao, and Jiaya Jia · 2016
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Joint 2D-3D-semantic data for indoor scene understanding
Iro Armeni, Sasha Sax, Amir R. Zamir, and Silvio Savarese · 2017
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DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L. Yuille · 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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Weakly supervised segmentation-aided classification of urban scenes from 3D lidar point clouds
Stéphane Guinard and Loic Landrieu · 2017
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Exploiting saliency for object segmentation from image level labels
Seong Joon Oh, Rodrigo Benenson, Anna Khoreva, Zeynep Akata, Mario Fritz, and Bernt Schiele · 2017
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Extreme clicking for efficient object annotation
Dim P Papadopoulos, Jasper RR Uijlings, Frank Keller, and Vittorio Ferrari · 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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Octnet: Learning deep 3D representations at high resolutions
Gernot Riegler, Ali Osman Ulusoy, and Andreas Geiger · 2017
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Prototypical networks for few-shot learning
Jake Snell, Kevin Swersky, and Richard Zemel · 2017
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Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen and Harri Valpola · 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 pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation
Jiwoon Ahn and Suha Kwak · 2018
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3DMV: Joint 3D-multi-view prediction for 3D semantic scene segmentation
Angela Dai and Matthias Nießner · 2018
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Tri-net for semi-supervised deep learning
Wei Gao Dong-Dong Chen, Wei Wang and Zhi Hua Zhou · 2018
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3D semantic segmentation with submanifold sparse convolutional networks
PyTorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 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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Boundary perception guidance: A scribble-supervised semantic segmentation approach
Bin Wang, Guojun Qi, Sheng Tang, Tianzhu Zhang, Yunchao Wei, Linghui Li, and Yongdong Zhang · 2019
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PointConv: Deep convolutional networks on 3D point clouds
Wenxuan Wu, Zhongang Qi, and Li Fuxin · 2019
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StructPool: Structured graph pooling via conditional random fields
Hao Yuan and Shuiwang Ji · 2019
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Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
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Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
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Where are the blobs: Counting by localization with point supervision
Issam H Laradji, Negar Rostamzadeh, Pedro O Pinheiro, David Vazquez, and Mark Schmidt · 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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Deep extreme cut: From extreme points to object segmentation
Kevis-Kokitsi Maninis, Sergi Caelles, Jordi Pont-Tuset, and Luc Van Gool · 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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Deep co-training for semi-supervised image recognition
Siyuan Qiao, Wei Shen, Zhishuai Zhang, Bo Wang, and Alan Yuille · 2018
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ConvPoint: Continuous convolutions for point cloud processing
Alexandre Boulch · 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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Exploring data-efficient 3d scene understanding with contrastive scene contexts
Ji Hou, Benjamin Graham, Matthias Nießner, and Saining Xie · 2020
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JSENet: Joint semantic segmentation and edge detection network for 3D point clouds
Zeyu Hu, Mingmin Zhen, Xuyang Bai, Hongbo Fu, and Chiew-lan Tai · 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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Virtual multi-view fusion for 3D semantic segmentation
Abhijit Kundu, Xiaoqi Michael Yin, Alireza Fathi, David Alexander Ross, Brian Brewington, Tom Funkhouser, and Caroline Pantofaru · 2020
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FPConv: Learning local flattening for point convolution
Yiqun Lin, Zizheng Yan, Haibin Huang, Dong Du, Ligang Liu, Shuguang Cui, and Xiaoguang Han · 2020
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DualConvMesh-Net: Joint geodesic and euclidean convolutions on 3D meshes
Jonas Schult, Francis Engelmann, Theodora Kontogianni, and Bastian Leibe · 2020
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Weakly supervised semantic segmentation in 3D graph-structured point clouds of wild scenes
Haiyan Wang, Xuejian Rong, Liang Yang, Jinglun Feng, Jizhong Xiao, and Yingli Tian · 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 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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Weakly-supervised salient object detection via scribble annotations
Jing Zhang, Xin Yu, Aixuan Li, Peipei Song, Bowen Liu, and Yuchao Dai · 2020
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