Fetching the paper…
Reading the bibliography…
High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving.
Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
Earlier work this paper cites.
Deep sliding shapes for amodal 3d object detection in rgb-d images
Shuran Song and Jianxiong Xiao · 2016
Earlier work this paper cites.
Multi-view 3d object detection network for autonomous driving
Xiaozhi Chen, Huimin Ma, Ji Wan, Bo Li, and Tian Xia · 2017
Earlier work this paper cites.
Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
Earlier work this paper cites.
3d bounding box estimation using deep learning and geometry
Arsalan Mousavian, Dragomir Anguelov, John Flynn, and Jana Kosecka · 2017
Earlier work this paper cites.
Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles R Qi, Hao Su, Kaichun Mo, and Leonidas J Guibas · 2017
Earlier work this paper cites.
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas · 2017
Earlier work this paper cites.
The 1cycle policy
Sylvain Gugger · 2018
Earlier work this paper cites.
Joint 3d proposal generation and object detection from view aggregation
Jason Ku, Melissa Mozifian, Jungwook Lee, Ali Harakeh, and Steven L Waslander · 2018
Earlier work this paper cites.
Cornernet: Detecting objects as paired keypoints
Hei Law and Jia Deng · 2018
Cited alongside, same era.
Pointcnn: Convolution on x-transformed points
Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen · 2018
Cited alongside, same era.
Frustum pointnets for 3d object detection from rgb-d data
Charles R Qi, Wei Liu, Chenxia Wu, Hao Su, and Leonidas J Guibas · 2018
Cited alongside, same era.
Complex-yolo: An euler-region-proposal for real-time 3d object detection on point clouds
Martin Simony, Stefan Milzy, Karl Amendey, and Horst-Michael Gross · 2018
Cited alongside, same era.
Second: Sparsely embedded convolutional detection
Yan Yan, Yuxing Mao, and Bo Li · 2018
Cited alongside, same era.
Pixor: Real-time 3d object detection from point clouds
Bin Yang, Wenjie Luo, and Raquel Urtasun · 2018
Cited alongside, same era.
Deep hough voting for 3d object detection in point clouds
Charles R Qi, Or Litany, Kaiming He, and Leonidas J Guibas · 2019
Later among the works it cites.
Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
Later among the works it cites.
Disentangling monocular 3d object detection
Andrea Simonelli, Samuel Rota Bulo, Lorenzo Porzi, Manuel López-Antequera, and Peter Kontschieder · 2019
Later among the works it cites.
Scalability in perception for autonomous driving: Waymo open dataset
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, et al · 2019
Later among the works it cites.
FCOS: Fully convolutional one-stage object detection
Zhi Tian, Chunhua Shen, Hao Chen, and Tong He · 2019
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
Cited alongside, same era.
nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2019
Cited alongside, same era.
Object as hotspots: An anchor-free 3d object detection approach via firing of hotspots
Qi Chen, Lin Sun, Zhixin Wang, Kui Jia, and Alan Yuille · 2019
Cited alongside, same era.
Pointpillars: Fast encoders for object detection from point clouds
Alex H Lang, Sourabh Vora, Holger Caesar, Lubing Zhou, Jiong Yang, and Oscar Beijbom · 2019
Cited alongside, same era.
Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
Cited alongside, same era.
Lasernet: An efficient probabilistic 3d object detector for autonomous driving
Gregory P. Meyer, Ankit Laddha, Eric Kee, Carlos Vallespi-Gonzalez, and Carl K. Wellington · 2019
Cited alongside, same era.
Frustum convnet: Sliding frustums to aggregate local point-wise features for amodal 3d object detection
Zhixin Wang and Kui Jia · 2019
Later among the works it cites.
Std: Sparse-to-dense 3d object detector for point cloud
Zetong Yang, Yanan Sun, Shu Liu, Xiaoyong Shen, and Jiaya Jia · 2019
Later among the works it cites.
Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
Later among the works it cites.
End-to-end multi-view fusion for 3d object detection in lidar point clouds
Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, and Vijay Vasudevan · 2019
Later among the works it cites.
Class-balanced grouping and sampling for point cloud 3d object detection
Benjin Zhu, Zhengkai Jiang, Xiangxin Zhou, Zeming Li, and Gang Yu · 2019
Later among the works it cites.
Improving 3d object detection through progressive population based augmentation
Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, et al · 2020
Closest in time.
Rtm3d: Real-time monocular 3d detection from object keypoints for autonomous driving
Peixuan Li, Huaici Zhao, Pengfei Liu, and Feidao Cao · 2020
Closest in time.
Training-time-friendly network for real-time object detection
Zili Liu, Tu Zheng, Guodong Xu, Zheng Yang, Haifeng Liu, and Deng Cai · 2020
Closest in time.