[1] Gooch A A, Olsen S C, Tumblin J et al. Color2Gray[J]. ACM Transactions on Graphics, 24, 634-639(2005).

[2] Ge P S, Guo L, Qi G D et al. Lane marker line identification method in variable light environment[J]. Laser & Optoelectronics Progress, 57, 161502(2020).

[3] Cheng C Y, Huang Y B, Lu X et al. Lane detection based on active infrared filter and around-view imaging[J]. Laser & Optoelectronics Progress, 55, 121014(2018).

[4] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition[EB/OL]. [2020-08-03]. https://arxiv.org/abs/1409.1556

[5] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition[C]. //2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA., 770-778(2016).

[6] Lee S, Kim J, Yoon J S et al. VPGNet: vanishing point guided network for lane and road marking detection and recognition[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy, 1965-1973(2017).

[7] Pan X G, Shi J P, Luo P et al. Spatial as deep: spatial CNN for traffic scene understanding[EB/OL]. [2020-08-01]. https://arxiv.org/abs/1712.06080

[8] Neven D, Brabandere B D, Georgoulis S et al. Towards end-to-end lane detection: an instance segmentation approach[C]. //2018 IEEE Intelligent Vehicles Symposium (IV), June 26-30, 2018, Changshu, China, 286-291(2018).

[9] Paszke A, Chaurasia A, Kim S et al. ENet: a deep neural network architecture for real-time semantic segmentation[EB/OL]. [2020-08-03]. https://arxiv.org/abs/1606.02147

[10] Chen L C, Zhu Y K, Papandreou G et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[EB/OL]. [2020-08-05]. https://arxiv.org/abs/1802.02611

[11] Ronneberger O, Fischer P, Brox T. U-net:convolutional networks for biomedical image segmentation[M]. // Navab N, Hornegger J, Wells W, et al. Medical Image Computing and Computer-Assisted Intervention-MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science. Cham: Springer, 9351, 234-241(2015).

[12] Yang M K, Yu K, Zhang C et al. DenseASPP for semantic segmentation in street scenes[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA., 3684-3692(2018).

[13] Huang G, Liu Z, van der Maaten L et al. Densely connected convolutional networks[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 2261-2269(2017).

[14] Salehi S S M, Erdogmus D, Gholipour V. Tversky loss function for image segmentation using 3D fully convolutional deep networks[EB/OL]. [2020-08-01]. https://arxiv.org/abs/1706.05721

[15] Brabandere B D, Neven D, Gool L V. Semantic instance segmentation with a discriminative loss function[EB/OL]. [2020-08-01]. https://arxiv.org/abs/1708.02551

[16] Hsu Y C, Xu Z, Kira Z et al. Learning to cluster for proposal-free instance segmentation[C]. //2018 International Joint Conference on Neural Networks (IJCNN), July 8-13, 2018, Rio de Janeiro, Brazil., 1-8(2018).

[17] Pizzati F, Allodi M, Barrera A et al. Lane detection and classification using cascaded CNNs[EB/OL]. [2020-08-01]. https://arxiv.org/abs/1907.01294