Fetching the paper…
Reading the bibliography…
Current 3D object detection methods are heavily influenced by 2D detectors.
Machine analysis of bubble chamber pictures
Paul VC Hough · 1959
Earlier work this paper cites.
Generalizing the hough transform to detect arbitrary shapes
Dana H Ballard · 1981
Earlier work this paper cites.
Combined object categorization and segmentation with an implicit shape model
Bastian Leibe, Ales Leonardis, and Bernt Schiele · 2004
Earlier work this paper cites.
Robust object detection with interleaved categorization and segmentation
Bastian Leibe, Aleš Leonardis, and Bernt Schiele · 2008
Earlier work this paper cites.
Object detection using a max-margin hough transform
Subhransu Maji and Jitendra Malik · 2009
Earlier work this paper cites.
Orientation invariant 3d object classification using hough transform based methods
Jan Knopp, Mukta Prasad, and Luc Van Gool · 2010
Earlier work this paper cites.
Depth-encoded hough voting for joint object detection and shape recovery
Min Sun, Gary Bradski, Bing-Xin Xu, and Silvio Savarese · 2010
Earlier work this paper cites.
The 3d hough transform for plane detection in point clouds: A review and a new accumulator design
Dorit Borrmann, Jan Elseberg, Kai Lingemann, and Andreas Nüchter · 2011
Earlier work this paper cites.
Hough forests for object detection, tracking, and action recognition
Juergen Gall, Angela Yao, Nima Razavi, Luc Van Gool, and Victor Lempitsky · 2011
Earlier work this paper cites.
Scene cut: Class-specific object detection and segmentation in 3d scenes
Jan Knopp, Mukta Prasad, and Luc Van Gool · 2011
Earlier work this paper cites.
A search-classify approach for cluttered indoor scene understanding
Liangliang Nan, Ke Xie, and Andrei Sharf · 2012
Earlier work this paper cites.
Implicit shape models for object detection in 3d point clouds
Alexander Velizhev, Roman Shapovalov, and Konrad Schindler · 2012
Earlier work this paper cites.
Class-specific hough forests for object detection
Juergen Gall and Victor Lempitsky · 2013
Earlier work this paper cites.
Accurate localization of 3d objects from rgb-d data using segmentation hypotheses
Byung-soo Kim, Shili Xu, and Silvio Savarese · 2013
Earlier work this paper cites.
Holistic scene understanding for 3d object detection with rgbd cameras
Dahua Lin, Sanja Fidler, and Raquel Urtasun · 2013
Earlier work this paper cites.
Sliding shapes for 3d object detection in depth images
Shuran Song and Jianxiong Xiao · 2014
Earlier work this paper cites.
Demisting the hough transform for 3d shape recognition and registration
Oliver J Woodford, Minh-Tri Pham, Atsuto Maki, Frank Perbet, and Björn Stenger · 2014
Earlier work this paper cites.
Database-assisted object retrieval for real-time 3d reconstruction
Yangyan Li, Angela Dai, Leonidas Guibas, and Matthias Nießner · 2015
Earlier work this paper cites.
Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
Earlier work this paper cites.
Sun rgb-d: A rgb-d scene understanding benchmark suite
Shuran Song, Samuel P Lichtenberg, and Jianxiong Xiao · 2015
Cited alongside, same era.
Deep learning of local rgb-d patches for 3d object detection and 6d pose estimation
Wadim Kehl, Fausto Milletari, Federico Tombari, Slobodan Ilic, and Nassir Navab · 2016
Cited alongside, same era.
Ssd: Single shot multibox detector
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C Berg · 2016
Cited alongside, same era.
Three-dimensional object detection and layout prediction using clouds of oriented gradients
Zhile Ren and Erik B Sudderth · 2016
Cited alongside, same era.
Deep sliding shapes for amodal 3d object detection in rgb-d images
Shuran Song and Jianxiong Xiao · 2016
Cited alongside, same era.
Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
Point convolutional neural networks by extension operators
Matan Atzmon, Haggai Maron, and Yaron Lipman · 2018
Later among the works it cites.
3d semantic segmentation with submanifold sparse convolutional networks
Benjamin Graham, Martin Engelcke, and Laurens van der Maaten · 2018
Later among the works it cites.
Pcpnet learning local shape properties from raw point clouds
Paul Guerrero, Yanir Kleiman, Maks Ovsjanikov, and Niloy J Mitra · 2018
Later among the works it cites.
3D-SIS: 3d semantic instance segmentation of rgb-d scans
Ji Hou, Angela Dai, and Matthias Nießner · 2018
Later among the works it cites.
Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
Cited alongside, same era.
A point set generation network for 3d object reconstruction from a single image
Haoqiang Fan, Hao Su, and Leonidas J Guibas · 2017
Cited alongside, same era.
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
Vehicle logo retrieval based on hough transform and deep learning
Li Huan, Qin Yujian, and Wang Li · 2017
Cited alongside, same era.
Escape from cells: Deep kd-networks for the recognition of 3d point cloud models
Roman Klokov and Victor Lempitsky · 2017
Cited alongside, same era.
2d-driven 3d object detection in rgb-d images
Jean Lahoud and Bernard Ghanem · 2017
Cited alongside, same era.
Pointgrid: A deep network for 3d shape understanding
Truc Le and Ye Duan · 2018
Later among the works it cites.
Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Later among the works it cites.
Semi-convolutional operators for instance segmentation
David Novotny, Samuel Albanie, Diane Larlus, and Andrea Vedaldi · 2018
Later among the works it cites.
Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
Later among the works it cites.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2018
Later among the works it cites.
Splatnet: Sparse lattice networks for point cloud processing
Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, and Jan Kautz · 2018
Later among the works it cites.
Tangent convolutions for dense prediction in 3d
Maxim Tatarchenko, Jaesik Park, Vladlen Koltun, and Qian-Yi Zhou · 2018
Later among the works it cites.
Dynamic graph cnn for learning on point clouds
Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E Sarma, Michael M Bronstein, and Justin M Solomon · 2018
Later among the works it cites.
Attentional shapecontextnet for point cloud recognition
Saining Xie, Sainan Liu, Zeyu Chen, and Zhuowen Tu · 2018
Later among the works it cites.
Spidercnn: Deep learning on point sets with parameterized convolutional filters
Yifan Xu, Tianqi Fan, Mingye Xu, Long Zeng, and Yu Qiao · 2018
Later among the works it cites.
Foldingnet: Point cloud auto-encoder via deep grid deformation
Yaoqing Yang, Chen Feng, Yiru Shen, and Dong Tian · 2018
Later among the works it cites.
Gspn: Generative shape proposal network for 3d instance segmentation in point cloud
Li Yi, Wang Zhao, He Wang, Minhyuk Sung, and Leonidas Guibas · 2018
Later among the works it cites.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
Later among the works it cites.