Fetching the paper…
Reading the bibliography…
Constructing HD semantic maps is a central component of autonomous driving.
J. Illingworth and J. Kittler, “A survey of the hough transform,” Computer vision, graphics, and image processing , vol. 44, no. 1, pp. 87–116, 1988
1988
Earlier work this paper cites.
P. J. Besl and N. D. McKay, “Method for registration of 3-d shapes,” in Sensor fusion IV: control paradigms and data structures , vol. 1611. International Society for Optics and Photonics, 1992, pp. 586–606
1992
Earlier work this paper cites.
C. L. Lawson and R. J. Hanson, Solving least squares problems . SIAM, 1995
1995
Earlier work this paper cites.
P. Biber and W. Straßer, “The normal distributions transform: A new approach to laser scan matching,” in Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003)(Cat. No. 03CH37453) , vol. 3. IEEE, 2003, pp. 2743–2748
2003
Earlier work this paper cites.
K.-Y. Chiu and S.-F. Lin, “Lane detection using color-based segmentation,” in IEEE Proceedings. Intelligent Vehicles Symposium, 2005. IEEE, 2005, pp. 706–711
2005
Earlier work this paper cites.
A. Segal, D. Haehnel, and S. Thrun, “Generalized-icp.” in Robotics: science and systems , vol. 2, no. 4. Seattle, WA, 2009, p. 435
2009
Earlier work this paper cites.
H. Loose, U. Franke, and C. Stiller, “Kalman particle filter for lane recognition on rural roads,” in 2009 IEEE Intelligent Vehicles Symposium . IEEE, 2009, pp. 60–65
2009
Earlier work this paper cites.
A. Ess, T. Mueller, H. Grabner, and L. Van Gool, “Segmentation-based urban traffic scene understanding.” in BMVC , vol. 1. Citeseer, 2009, p. 2
2009
Earlier work this paper cites.
S. Zhou, Y. Jiang, J. Xi, J. Gong, G. Xiong, and H. Chen, “A novel lane detection based on geometrical model and gabor filter,” in 2010 IEEE Intelligent Vehicles Symposium . IEEE, 2010, pp. 59–64
2010
Earlier work this paper cites.
F. Dellaert, “Factor graphs and gtsam: A hands-on introduction,” Georgia Institute of Technology, Tech. Rep., 2012
2012
Earlier work this paper cites.
J. M. Alvarez, T. Gevers, Y. LeCun, and A. M. Lopez, “Road scene segmentation from a single image,” in ECCV , 2012
2012
Earlier work this paper cites.
F. Yu, J. Xiao, and T. Funkhouser, “Semantic alignment of lidar data at city scale,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 1722–1731
2015
Earlier work this paper cites.
F. Pomerleau, F. Colas, and R. Siegwart, “A review of point cloud registration algorithms for mobile robotics,” Foundations and Trends in Robotics , vol. 4, no. 1, pp. 1–104, 2015
2015
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. Belongie, L. Bourdev, R. Girshick, J. Hays, P. Perona, D. Ramanan, C. L. Zitnick, and P. Dollár, “Microsoft coco: Common objects in context,” 2015
2015
Earlier work this paper cites.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, A. C. Berg, and L. Fei-Fei, “Imagenet large scale visual recognition challenge,” 2015
2015
Earlier work this paper cites.
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele, “The cityscapes dataset for semantic urban scene understanding,” in CVPR , 2016
2016
Cited alongside, same era.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in CVPR , 2016
2016
Cited alongside, same era.
B. Zhou, H. Zhao, X. Puig, S. Fidler, A. Barriuso, and A. Torralba, “Scene parsing through ade20k dataset,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 633–641
2017
Cited alongside, same era.
G. Neuhold, T. Ollmann, S. Rota Bulo, and P. Kontschieder, “The mapillary vistas dataset for semantic understanding of street scenes,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 4990–4999
2017
Cited alongside, same era.
M. Bai, G. Mattyus, N. Homayounfar, S. Wang, K. Lakshmikanth, Shrinidhi, and R. Urtasun, “Deep multi-sensor lane detection,” in IROS , 2018
2018
Later among the works it cites.
2018
Later among the works it cites.
N. Garnett, R. Cohen, T. Pe’er, R. Lahav, and D. Levi, “3d-lanenet: end-to-end 3d multiple lane detection,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2019, pp. 2921–2930
2019
Later among the works it cites.
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom, “Pointpillars: Fast encoders for object detection from point clouds,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2019
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…
C. R. Qi, H. Su, K. Mo, and L. J. Guibas, “Pointnet: Deep learning on point sets for 3d classification and segmentation,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , July 2017
2017
Cited alongside, same era.
E. Shelhamer, J. Long, and T. Darrell, “Fully convolutional networks for semantic segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 39, no. 4, pp. 640–651, 2017
2017
Cited alongside, same era.
B. De Brabandere, D. Neven, and L. Van Gool, “Semantic instance segmentation for autonomous driving,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , July 2017
2017
Cited alongside, same era.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” 2017
2017
Cited alongside, same era.
S. Yang, X. Zhu, X. Nian, L. Feng, X. Qu, and T. Ma, “A robust pose graph approach for city scale lidar mapping,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 1175–1182
2018
Cited alongside, same era.
J. Jiao, “Machine learning assisted high-definition map creation,” in 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC) , vol. 1. IEEE, 2018, pp. 367–373
2018
Cited alongside, same era.
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Y. Zhou, P. Sun, Y. Zhang, D. Anguelov, J. Gao, T. Ouyang, J. Guo, J. Ngiam, and V. Vasudevan, “End-to-end multi-view fusion for 3d object detection in LiDAR point clouds,” in The Conference on Robot Learning (CoRL) , 2019
2019
Later among the works it cites.
A. H. Lang, S. Vora, H. Caesar, L. Zhou, J. Yang, and O. Beijbom, “Pointpillars: Fast encoders for object detection from point clouds,” 2019
2019
Later among the works it cites.
L. Deng, M. Yang, H. Li, T. Li, B. Hu, and C. Wang, “Restricted deformable convolution-based road scene semantic segmentation using surround view cameras,” IEEE Transactions on Intelligent Transportation Systems , vol. 21, no. 10, p. 4350–4362, Oct 2020. [Online]. Available: http://dx.doi.org/10.1109/TITS.2019.2939832
2019
Later among the works it cites.
Y. Guo, G. Chen, P. Zhao, W. Zhang, J. Miao, J. Wang, and T. E. Choe, “Genlanenet: A generalized and scalable approach for 3d lane detection,” 2020
2020
Later among the works it cites.
B. Pan, J. Sun, H. Y. T. Leung, A. Andonian, and B. Zhou, “Cross-view semantic segmentation for sensing surroundings,” IEEE Robotics and Automation Letters , vol. 5, no. 3, p. 4867–4873, Jul 2020. [Online]. Available: http://dx.doi.org/10.1109/LRA.2020.3004325
2020
Later among the works it cites.
T. Roddick and R. Cipolla, “Predicting semantic map representations from images using pyramid occupancy networks,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 11 138–11 147
2020
Later among the works it cites.
J. Philion and S. Fidler, “Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,” 2020
2020
Later among the works it cites.
H. Caesar, V. Bankiti, A. H. Lang, S. Vora, V. E. Liong, Q. Xu, A. Krishnan, Y. Pan, G. Baldan, and O. Beijbom, “nuscenes: A multimodal dataset for autonomous driving,” 2020
2020
Later among the works it cites.
M. Tan and Q. V. Le, “Efficientnet: Rethinking model scaling for convolutional neural networks,” 2020
2020
Later among the works it cites.
L. Mi, H. Zhao, C. Nash, X. Jin, J. Gao, C. Sun, C. Schmid, N. Shavit, Y. Chai, and D. Anguelov, “Hdmapgen: A hierarchical graph generative model of high definition maps,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , June 2021, pp. 4227–4236
2021
Closest in time.