[1] [1] Ma C, Mao L, Zhang Y, et al. Lane detection using Heuristic Search Methods based on color clustering[C]//2010 International Conference on Communications, Circuits and Systems (ICCCAS), 2010: 368-372.

[2] [2] Huang Y, Li Y, Hu X, et al. Lane Detection Based on Inverse Perspective Transformation and Kalman Filter[J]. KSII Transactions on Internet and Information Systems (TIIS), 2018, 12(2): 643-661.

[3] [3] Youjin T, Wei C, Xingguang L, et al. A Robust Lane Detection Method Based on Vanishing Point Estimation[J]. Procedia Computer Science, 2018, 131: 354-360.

[4] [4] Ko Y, Lee Y, Azam S, et al. Key Points Estimation and Point Instance Segmentation Approach for Lane Detection[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(7): 8949-8958.

[5] [5] Tabelini L, Berriel R, Paixo T M, et al. Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection[C]//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021: 294-302.

[6] [6] Pan X, Shi J, Luo P, et al. Spatial as deep: Spatial CNN for traffic scene understanding[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2018: 7276-7283.

[7] [7] Qin Z, Wang H, Li X. Ultra Fast Structure-Aware Deep Lane Detection[C]//Computer Vision-ECCV 2020: 16th European Conference, 2020: 276-291.

[8] [8] Zheng T, Fang H, Zhang Y, et al. RESA: Recurrent Feature-Shift Aggregator for Lane Detection[C]//Proceedings of the AAAI Conference on Artificial Intelligence, 2021: 3547-3554.

[9] [9] Yoo S, Lee H S, Myeong H, et al. End-to-End Lane Marker Detection via Row - wise Classification[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020: 4335-4343.

[10] [10] Liu R, Yuan Z, Liu T, et al. End-to-end Lane Shape Prediction with Transformers[C]//2021 IEEE Winter Conference on Applications of Computer Vision (WACV), 2021: 3693-3701.

[11] [11] Newell A, Yang K, Deng J. Stacked Hourglass Networks for Human Pose Estimation[C]//Computer Vision-ECCV 2016: 14th European Conference, 2016: 483-499.

[12] [12] He K, Zhang X, Ren S, et al. Deep Residual Learning for Image Recognition[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016: 770-778.

[13] [13] Wang Q, Wu B, Zhu P, et al. ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks[C]//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020: 11531-11539.