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Feature learning for 3D object detection from point clouds is very challenging due to the irregularity of 3D point cloud data.
Multiple 3d object tracking for augmented reality
Youngmin Park, Vincent Lepetit, and W. Woo · 2008
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 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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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 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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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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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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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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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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Deep parametric continuous convolutional neural networks
Shenlong Wang, Simon Suo, Wei-Chiu Ma, Andrei Pokrovsky, and Raquel Urtasun · 2018
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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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On the relationship between self-attention and convolutional layers
Jean-Baptiste Cordonnier, Andreas Loukas, and Martin Jaggi · 2019
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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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3d-sis: 3d semantic instance segmentation of rgb-d scans
Ji Hou, Angela Dai, and Matthias Niessner · 2019
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Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
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Set transformer: A framework for attention-based permutation-invariant neural networks
Juho Lee, Yoonho Lee, Jungtaek Kim, Adam Kosiorek, Seungjin Choi, and Yee Whye Teh · 2019
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Multi-task multi-sensor fusion for 3d object detection
Ming Liang, Bin Yang, Yun Chen, Rui Hu, and Raquel Urtasun · 2019
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Deep hough voting for 3d object detection in point clouds
Charles R Qi, Or Litany, Kaiming He, and Leonidas J Guibas · 2019
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Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, I. Bello, Anselm Levskaya, and Jonathon Shlens · 2019
MMDetection3D: OpenMMLab next-generation platform for general 3d object detection
MMDetection3D Contributors · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale, 2020
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2020
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Transformers are rnns: Fast autoregressive transformers with linear attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, and Franccois Fleuret · 2020
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Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya · 2020
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Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
Shaoshuai Shi, Chaoxu Guo, L. Jiang, Zhe Wang, Jianping Shi, X. Wang, and Hongsheng Li · 2020
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Cited alongside, same era.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Cited alongside, same era.
Kpconv: Flexible and deformable convolution for point clouds
H. Thomas, Charles R. Qi, Jean-Emmanuel Deschaud, B. Marcotegui, F. Goulette, and L. Guibas · 2019
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Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2019
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Modeling point clouds with self-attention and gumbel subset sampling
Jiancheng Yang, Qiang Zhang, Bingbing Ni, Linguo Li, Jinxian Liu, Mengdie Zhou, and Qi Tian · 2019
Cited alongside, same era.
Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, and Gang Yu · 2019
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
H. Caesar, Varun Bankiti, A. Lang, Sourabh Vora, Venice Erin Liong, Q. Xu, A. Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Point-gnn: Graph neural network for 3d object detection in a point cloud
Weijing Shi and Raj Rajkumar · 2020
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Openpcdet: An open-source toolbox for 3d object detection from point clouds
OpenPCDet Development Team · 2020
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Pointpainting: Sequential fusion for 3d object detection
Sourabh Vora, Alex H. Lang, Bassam Helou, and Oscar Beijbom · 2020
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Li, Madian Khabsa, Han Fang, and Hao Ma · 2020
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Mlcvnet: Multi-level context votenet for 3d object detection
Qian Xie, Yu-Kun Lai, Jing Wu, Zhoutao Wang, Yiming Zhang, Kai Xu, and Jun Wang · 2020
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Grid-gcn for fast and scalable point cloud learning
Qiangeng Xu, Xudong Sun, Cho-Ying Wu, Panqu Wang, and U. Neumann · 2020
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Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling
Xu Yan, C. Zheng, Zhuguo Li, S. Wang, and Shuguang Cui · 2020
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Hvnet: Hybrid voxel network for lidar based 3d object detection
M. Ye, Shuangjie Xu, and Tongyi Cao · 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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Deformable detr: Deformable transformers for end-to-end object detection, 2020
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
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