[1] KIM J, LEE M. Robust lane detection based on convolutional neural network and random sample consensus[C]//International Conference on Neural Information Processing. Cham: Springer, 2014: 454-461.
[2] HUVAL B, WANG T, TANDON S, et al. An empirical evaluation of deep learning on highway driving[J]. arXiv:1504.01716, 2015.
[3] 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.
[4] NEVEN D, DE BRABANDERE B, GEORGOULIS S, et al. Towards end-to-end lane detection: an instance segmentation approach[C]//2018 IEEE Intelligent Vehicles Symposium (IV), 2018: 286-291.
[5] GHAFOORIAN M, NUGTEREN C, BAKA N, et al. El-GAN: embedding loss driven generative adversarial networks for lane detection[C]//Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018.
[6] GOODFELLOW I, POUGET-ABADIE J, MIRZA M, et al. Generative adversarial networks[J]. Communications of the ACM, 2020, 63(11): 139-144.
[7] 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, 35(4): 3547-3554.
[8] WANG Q, HAN T, QIN Z, et al. Multitask attention network for lane detection and fitting[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 33(3): 1066-1078.
[9] CARION N, MASSA F, SYNNAEVE G, et al. End-to-end object detection with transformers[C]//European Conference on Computer Vision. Cham: Springer, 2020: 213-229.
[10] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need[C]//Advances in Neural Information Processing Systems, 2017, 30: 21-25.
[11] DAI Z, LIU H, LE Q V, et al. Coatnet: marrying convolution and attention for all data sizes[C]//Advances in Neural Information Processing Systems, 2021, 34: 3965-3977.
[12] QIN Z, WANG H, LI X. Ultra fast structure-aware deep lane detection[C]//European Conference on Computer Vision. Cham: Springer, 2020: 276-291.
[13] PHILION J. FastDraw: addressing the long tail of lane detection by adapting a sequential prediction network[C]//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019: 11582-11591.
[14] TABELINI L, BERRIEL R, PAIXAO T M, et al. PolyLaneNet: lane estimation via deep polynomial regression[C]//2020 25th International Conference on Pattern Recognition (ICPR), 2021: 6150-6156.
[15] LIU R, YUAN Z, LIU T, et al. End-to-end lane shape prediction with transformers[C]//Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2021: 3694-3702. |