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In this paper, we propose a weakly-supervised approach for 3D object detection, which makes it possible to train a strong 3D detector with position-level annotations (i.e.
Efficient graph-based image segmentation
Pedro F Felzenszwalb and Daniel P Huttenlocher · 2004
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A search-classify approach for cluttered indoor scene understanding
Liangliang Nan, Ke Xie, and Andrei Sharf · 2012
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Object discovery in 3d scenes via shape analysis
Andrej Karpathy, Stephen Miller, and Li Fei-Fei · 2013
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Sliding shapes for 3d object detection in depth images
Shuran Song and Jianxiong Xiao · 2014
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Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Unsupervised domain adaptation by backpropagation
Yaroslav Ganin and Victor Lempitsky · 2015
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Database-assisted object retrieval for real-time 3d reconstruction
Yangyan Li, Angela Dai, Leonidas Guibas, and Matthias Nießner · 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 shapenets: A deep representation for volumetric shapes
Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao · 2015
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Monocular 3d object detection for autonomous driving
Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2016
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You only look once: Unified, real-time object detection
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi · 2016
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Faster r-cnn: towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2016
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Deep sliding shapes for amodal 3d object detection in rgb-d images
Shuran Song and Jianxiong Xiao · 2016
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Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 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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2d-driven 3d object detection in rgb-d images
Jean Lahoud and Bernard Ghanem · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Asist: automatic semantically invariant scene transformation
Or Litany, Tal Remez, Daniel Freedman, Lior Shapira, Alex Bronstein, and Ran Gal · 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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Antti Tarvainen and Harri Valpola · 2017
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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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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Weakly supervised 3d object detection from lidar point cloud
Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Luc Van Gool, and Dengxin Dai · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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Weakly supervised 3d object detection from point clouds
Zengyi Qin, Jinglu Wang, and Yan Lu · 2020
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Deformation-aware 3d model embedding and retrieval
Mikaela Angelina Uy, Jingwei Huang, Minhyuk Sung, Tolga Birdal, and Leonidas Guibas · 2020
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Mlcvnet: Multi-level context votenet for 3d object detection
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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Scan2cad: Learning cad model alignment in rgb-d scans
Armen Avetisyan, Manuel Dahnert, Angela Dai, Manolis Savva, Angel X Chang, and Matthias Nießner · 2019
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End-to-end cad model retrieval and 9dof alignment in 3d scans
Armen Avetisyan, Angela Dai, and Matthias Nießner · 2019
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Joint embedding of 3d scan and cad objects
Manuel Dahnert, Angela Dai, Leonidas J Guibas, and Matthias Niessner · 2019
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3d-sis: 3d semantic instance segmentation of rgb-d scans
Ji Hou, Angela Dai, and Matthias Nießner · 2019
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Augmentation for small object detection
Mate Kisantal, Zbigniew Wojna, Jakub Murawski, Jacek Naruniec, and Kyunghyun Cho · 2019
Cited alongside, same era.
Flownet3d: Learning scene flow in 3d point clouds
Xingyu Liu, Charles R. Qi, and Leonidas J. Guibas · 2019
Cited alongside, same era.
Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Yiming Zhang, Kai Xu, and Jun Wang · 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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H3dnet: 3d object detection using hybrid geometric primitives
Zaiwei Zhang, Bo Sun, Haitao Yang, and Qixing Huang · 2020
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Sess: Self-ensembling semi-supervised 3d object detection
Na Zhao, Tat-Seng Chua, and Gim Hee Lee · 2020
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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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Group-free 3d object detection via transformers
Ze Liu, Zheng Zhang, Yue Cao, Han Hu, and Xin Tong · 2021
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Towards a weakly supervised framework for 3d point cloud object detection and annotation
Qinghao Meng, Wenguan Wang, Tianfei Zhou, Jianbing Shen, Yunde Jia, and Luc Van Gool · 2021
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Randomrooms: Unsupervised pre-training from synthetic shapes and randomized layouts for 3d object detection
Yongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, and Jie Zhou · 2021
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3d spatial recognition without spatially labeled 3d
Zhongzheng Ren, Ishan Misra, Alexander G Schwing, and Rohit Girdhar · 2021
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3dioumatch: Leveraging iou prediction for semi-supervised 3d object detection
He Wang, Yezhen Cong, Or Litany, Yue Gao, and Leonidas J Guibas · 2021
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Self-supervised pretraining of 3d features on any point-cloud
Zaiwei Zhang, Rohit Girdhar, Armand Joulin, and Ishan Misra · 2021
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