Fetching the paper…
Reading the bibliography…
Detecting objects such as cars and pedestrians in 3D plays an indispensable role in autonomous driving.
Sensor fusion for joint 3d object detection and semantic segmentation
Gregory P Meyer, Jake Charland, Darshan Hegde, Ankit Laddha, and Carlos Vallespi-Gonzalez · 1904
Earlier work this paper cites.
Nonlinear dimensionality reduction by locally linear embedding
Sam T Roweis and Lawrence K Saul · 2000
Earlier work this paper cites.
Learning from labeled and unlabeled data with label propagation
Zhu Xiaojin and Ghahramani Zoubin · 2002
Earlier work this paper cites.
Statistical inference and synthesis in the image domain for mobile robot environment modeling
Luz Abril Torres-Mendez and Gregory Dudek · 2004
Earlier work this paper cites.
Nonlinear dimensionality reduction by semidefinite programming and kernel matrix factorization
Kilian Q. Weinberger, Benjamin Packer, and Lawrence K. Saul · 2005
Earlier work this paper cites.
Highly parallel fast kd-tree construction for interactive ray tracing of dynamic scenes
Maxim Shevtsov, Alexei Soupikov, and Alexander Kapustin · 2007
Earlier work this paper cites.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Vision meets robotics: The kitti dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
Earlier work this paper cites.
Efficient joint segmentation, occlusion labeling, stereo and flow estimation
Koichiro Yamaguchi, David McAllester, and Raquel Urtasun · 2014
Earlier work this paper cites.
3d object proposals for accurate object class detection
Xiaozhi Chen, Kaustav Kundu, Yukun Zhu, Andrew G Berneshawi, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 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.
Data-driven 3d voxel patterns for object category recognition
Yu Xiang, Wongun Choi, Yuanqing Lin, and Silvio Savarese · 2015
Earlier work this paper cites.
Monocular 3d object detection for autonomous driving
Xiaozhi Chen, Kaustav Kundu, Ziyu Zhang, Huimin Ma, Sanja Fidler, and Raquel Urtasun · 2016
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Vehicle detection from 3d lidar using fully convolutional network
Bo Li, Tianlei Zhang, and Tian Xia · 2016
Earlier work this paper cites.
A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
Nikolaus Mayer, Eddy Ilg, Philip Hausser, Philipp Fischer, Daniel Cremers, Alexey Dosovitskiy, and Thomas Brox · 2016
Cited alongside, same era.
Deep manta: A coarse-to-fine many-task network for joint 2d and 3d vehicle analysis from monocular image
Florian Chabot, Mohamed Chaouch, Jaonary Rabarisoa, Céline Teulière, and Thierry Chateau · 2017
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
Cited alongside, same era.
Vote3deep: Fast object detection in 3d point clouds using efficient convolutional neural networks
Martin Engelcke, Dushyant Rao, Dominic Zeng Wang, Chi Hay Tong, and Ingmar Posner · 2017
Cited alongside, same era.
Unsupervised monocular depth estimation with left-right consistency
Clément Godard, Oisin Mac Aodha, and Gabriel J Brostow · 2017
Cited alongside, same era.
Deep ordinal regression network for monocular depth estimation
Huan Fu, Mingming Gong, Chaohui Wang, Kayhan Batmanghelich, and Dacheng Tao · 2018
Later among the works it cites.
Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven Waslander · 2018
Later among the works it cites.
Deep continuous fusion for multi-sensor 3d object detection
Ming Liang, Bin Yang, Shenlong Wang, and Raquel Urtasun · 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.
Dscnet: Replicating lidar point clouds with deep sensor cloning
Paden Tomasello, Sammy Sidhu, Anting Shen, Matthew W Moskewicz, Nobie Redmon, Gataryi Joshi, Romi Phadte, Paras Jain, and Forrest Iandola · 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…
Mask r-cnn
Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick · 2017
Cited alongside, same era.
3d fully convolutional network for vehicle detection in point cloud
Bo Li · 2017
Cited alongside, same era.
Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross B Girshick, Kaiming He, Bharath Hariharan, and Serge J Belongie · 2017
Cited alongside, same era.
3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Košecká · 2017
Cited alongside, same era.
Robust object proposals re-ranking for object detection in autonomous driving using convolutional neural networks
Cuong Cao Pham and Jae Wook Jeon · 2017
Cited alongside, same era.
Subcategory-aware convolutional neural networks for object proposals and detection
Yu Xiang, Wongun Choi, Yuanqing Lin, and Silvio Savarese · 2017
Cited alongside, same era.
Pyramid stereo matching network
Jia-Ren Chang and Yong-Sheng Chen · 2018
Cited alongside, same era.
Tsun-Hsuan Wang, Fu-En Wang, Juan-Ting Lin, Yi-Hsuan Tsai, Wei-Chen Chiu, and Min Sun · 2018
Later among the works it cites.
Multi-level fusion based 3d object detection from monocular images
Bin Xu and Zhenzhong Chen · 2018
Later among the works it cites.
Pointfusion: Deep sensor fusion for 3d bounding box estimation
Danfei Xu, Dragomir Anguelov, and Ashesh Jain · 2018
Later among the works it cites.
Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 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.
Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Closest in time.
Self-supervised sparse-to-dense: self-supervised depth completion from lidar and monocular camera
Fangchang Ma, Guilherme Venturelli Cavalheiro, and Sertac Karaman · 2019
Closest in time.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Closest in time.
Learning 2d to 3d lifting for object detection in 3d for autonomous vehicles
Siddharth Srivastava, Frederic Jurie, and Gaurav Sharma · 2019
Closest in time.
Dense depth posterior (ddp) from single image and sparse range
Yanchao Yang, Alex Wong, and Stefano Soatto · 2019
Closest in time.