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High-Definition (HD) maps can provide precise geometric and semantic information of static traffic environments for autonomous driving.
V. Mnih and G. E. Hinton, “Learning to detect roads in high-resolution aerial images,” in European Conference on Computer Vision . Springer, 2010, pp. 210–223
2010
Earlier work this paper cites.
J. D. Wegner, J. A. Montoya-Zegarra, and K. Schindler, “A higher-order crf model for road network extraction,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2013, pp. 1698–1705
2013
Earlier work this paper cites.
G. Máttyus, W. Luo, and R. Urtasun, “Deeproadmapper: Extracting road topology from aerial images,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 3438–3446
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in neural information processing systems , 2017, pp. 5998–6008
2017
Earlier work this paper cites.
T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 2117–2125
2017
Earlier work this paper cites.
N. Homayounfar, W.-C. Ma, S. Kowshika Lakshmikanth, and R. Urtasun, “Hierarchical recurrent attention networks for structured online maps,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 3417–3426
2018
Earlier work this paper cites.
F. Bastani, S. He, S. Abbar, M. Alizadeh, H. Balakrishnan, S. Chawla, S. Madden, and D. DeWitt, “Roadtracer: Automatic extraction of road networks from aerial images,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 4720–4728
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
P. Sun, X. Zhao, Z. Xu, R. Wang, and H. Min, “A 3d lidar data-based dedicated road boundary detection algorithm for autonomous vehicles,” IEEE Access , vol. 7, pp. 29 623–29 638, 2019
2019
Earlier work this paper cites.
N. Homayounfar, W.-C. Ma, J. Liang, X. Wu, J. Fan, and R. Urtasun, “Dagmapper: Learning to map by discovering lane topology,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 2911–2920
2019
Cited alongside, same era.
J. Liang, N. Homayounfar, W.-C. Ma, S. Wang, and R. Urtasun, “Convolutional recurrent network for road boundary extraction,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 9512–9521
2019
Cited alongside, same era.
A. Batra, S. Singh, G. Pang, S. Basu, C. Jawahar, and M. Paluri, “Improved road connectivity by joint learning of orientation and segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 10 385–10 393
2019
Cited alongside, same era.
N. Xue, S. Bai, F. Wang, G.-S. Xia, T. Wu, and L. Zhang, “Learning attraction field representation for robust line segment detection,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2019, pp. 1595–1603
S. He, F. Bastani, S. Jagwani, M. Alizadeh, H. Balakrishnan, S. Chawla, M. M. Elshrif, S. Madden, and M. A. Sadeghi, “Sat2graph: road graph extraction through graph-tensor encoding,” in Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIV 16 . Springer, 2020, pp. 51–67
2020
Later among the works it cites.
A. V. Etten, “City-scale road extraction from satellite imagery v2: Road speeds and travel times,” in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , 2020, pp. 1786–1795
2020
Later among the works it cites.
Z. Xu, Y. Sun, and M. Liu, “Topo-boundary: A benchmark dataset on topological road-boundary detection using aerial images for autonomous driving,” IEEE Robotics and Automation Letters , vol. 6, no. 4, pp. 7248–7255, 2021
2021
Closest in time.
Y. B. Can, A. Liniger, D. P. Paudel, and L. Van Gool, “Structured bird’s-eye-view traffic scene understanding from onboard images,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 15 661–15 670
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2019
Cited alongside, same era.
S. Yun, M. Jeong, R. Kim, J. Kang, and H. J. Kim, “Graph transformer networks,” Advances in Neural Information Processing Systems , vol. 32, pp. 11 983–11 993, 2019
2019
Cited alongside, same era.
K. Sun, B. Xiao, D. Liu, and J. Wang, “Deep high-resolution representation learning for human pose estimation,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2019, pp. 5693–5703
2019
Cited alongside, same era.
X. Lu, Y. Ai, and B. Tian, “Real-time mine road boundary detection and tracking for autonomous truck,” Sensors , vol. 20, no. 4, p. 1121, 2020
2020
Cited alongside, same era.
Y.-Q. Tan, S.-H. Gao, X.-Y. Li, M.-M. Cheng, and B. Ren, “Vecroad: Point-based iterative graph exploration for road graphs extraction,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 8910–8918
2020
Cited alongside, same era.
“csboundary project webpage,” https://sites.google.com/view/csboundary
Cited in the paper.
2021
Closest in time.
Z. Xu, Y. Sun, and M. Liu, “icurb: Imitation learning-based detection of road curbs using aerial images for autonomous driving,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 1097–1104, 2021
2021
Closest in time.
Z. Xu, Y. Sun, L. Wang, and M. Liu, “Cp-loss: Connectivity-preserving loss for road curb detection in autonomous driving with aerial images,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2021, pp. 1117–1123
2021
Closest in time.
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 , 2021, pp. 4227–4236
2021
Closest in time.
N. Girard, D. Smirnov, J. Solomon, and Y. Tarabalka, “Polygonal building extraction by frame field learning,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 5891–5900
2021
Closest in time.