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+@article{houghtransform,
+  title={A survey of the Hough transform},
+  author={Illingworth, John and Kittler, Josef},
+  journal={Computer vision, graphics, and image processing},
+  volume={44},
+  number={1},
+  pages={87--116},
+  year={1988},
+  publisher={Elsevier}
+}
+
+@article{cannyedge,
+  title={A computational approach to edge detection},
+  author={Canny, John},
+  journal={IEEE Transactions on pattern analysis and machine intelligence},
+  number={6},
+  pages={679--698},
+  year={1986},
+  publisher={IEEE}
+}
+
+@inproceedings{kluge1995deformable,
+  title={A deformable-template approach to lane detection},
+  author={Kluge, Karl and Lakshmanan, Sridhar},
+  booktitle={Proceedings of the Intelligent Vehicles' 95. Symposium},
+  pages={54--59},
+  year={1995},
+  organization={IEEE}
+}
+
+
+@article{yolov10,
+  title={Yolov10: Real-time end-to-end object detection},
+  author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang},
+  journal={arXiv preprint arXiv:2405.14458},
+  year={2024}
+}
+
+@article{fasterrcnn,
+  title={Faster R-CNN: Towards real-time object detection with region proposal networks},
+  author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
+  journal={IEEE transactions on pattern analysis and machine intelligence},
+  volume={39},
+  number={6},
+  pages={1137--1149},
+  year={2016},
+  publisher={IEEE}
+}
+
+@inproceedings{clrnet,
+  title={Clrnet: Cross layer refinement network for lane detection},
+  author={Zheng, Tu and Huang, Yifei and Liu, Yang and Tang, Wenjian and Yang, Zheng and Cai, Deng and He, Xiaofei},
+  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
+  pages={898--907},
+  year={2022}
+}
+
+@inproceedings{clrernet,
+  title={CLRerNet: improving confidence of lane detection with LaneIoU},
+  author={Honda, Hiroto and Uchida, Yusuke},
+  booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
+  pages={1176--1185},
+  year={2024}
+}
+
+
+@inproceedings{laneatt,
+  title={Keep your eyes on the lane: Real-time attention-guided lane detection},
+  author={Tabelini, Lucas and Berriel, Rodrigo and Paixao, Thiago M and Badue, Claudine and De Souza, Alberto F and Oliveira-Santos, Thiago},
+  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
+  pages={294--302},
+  year={2021}
+}
+
+@inproceedings{adnet,
+  title={Adnet: Lane shape prediction via anchor decomposition},
+  author={Xiao, Lingyu and Li, Xiang and Yang, Sen and Yang, Wankou},
+  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
+  pages={6404--6413},
+  year={2023}
+}
+
+@inproceedings{srlane,
+  title={Sketch and Refine: Towards Fast and Accurate Lane Detection},
+  author={Chen, Chao and Liu, Jie and Zhou, Chang and Tang, Jie and Wu, Gangshan},
+  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
+  volume={38},
+  number={2},
+  pages={1001--1009},
+  year={2024}
+}
+
+
+@misc{tusimple,
+  author = {{TuSimple}},
+  title = {TuSimple Benchmark},
+  year = {2020},
+  url = {https://github.com/TuSimple/tusimple-benchmark/},
+  note = {Accessed: September 2020}
+}
+
+@inproceedings{scnn,
+  title={Spatial as deep: Spatial cnn for traffic scene understanding},
+  author={Pan, Xingang and Shi, Jianping and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
+  booktitle={Proceedings of the AAAI conference on artificial intelligence},
+  volume={32},
+  number={1},
+  year={2018}
+}
+
+@inproceedings{curvelanes,
+  title={Curvelane-nas: Unifying lane-sensitive architecture search and adaptive point blending},
+  author={Xu, Hang and Wang, Shaoju and Cai, Xinyue and Zhang, Wei and Liang, Xiaodan and Li, Zhenguo},
+  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XV 16},
+  pages={689--704},
+  year={2020},
+  organization={Springer}
+}
+
+@inproceedings{llamas,
+  title={Unsupervised labeled lane markers using maps},
+  author={Behrendt, Karsten and Soussan, Ryan},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision workshops},
+  pages={0--0},
+  year={2019}
+}
+
+@article{dalnet,
+  title={DALNet: A rail detection network based on dynamic anchor line},
+  author={Yu, Zichen and Liu, Quanli and Wang, Wei and Zhang, Liyong and Zhao, Xiaoguang},
+  journal={IEEE Transactions on Instrumentation and Measurement},
+  year={2024},
+  publisher={IEEE}
+}
+
+@article{lanenet,
+  title={Lanenet: Real-time lane detection networks for autonomous driving},
+  author={Wang, Ze and Ren, Weiqiang and Qiu, Qiang},
+  journal={arXiv preprint arXiv:1807.01726},
+  year={2018}
+}
+
+@inproceedings{condlanenet,
+  title={Condlanenet: a top-to-down lane detection framework based on conditional convolution},
+  author={Liu, Lizhe and Chen, Xiaohao and Zhu, Siyu and Tan, Ping},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
+  pages={3773--3782},
+  year={2021}
+}
+
+@inproceedings{ufld,
+  title={Ultra fast structure-aware deep lane detection},
+  author={Qin, Zequn and Wang, Huanyu and Li, Xi},
+  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part XXIV 16},
+  pages={276--291},
+  year={2020},
+  organization={Springer}
+}
+
+@article{ufldv2,
+  title={Ultra fast deep lane detection with hybrid anchor driven ordinal classification},
+  author={Qin, Zequn and Zhang, Pengyi and Li, Xi},
+  journal={IEEE transactions on pattern analysis and machine intelligence},
+  volume={46},
+  number={5},
+  pages={2555--2568},
+  year={2022},
+  publisher={IEEE}
+}
+
+@article{fololane,
+  title={Ultra fast deep lane detection with hybrid anchor driven ordinal classification},
+  author={Qin, Zequn and Zhang, Pengyi and Li, Xi},
+  journal={IEEE transactions on pattern analysis and machine intelligence},
+  volume={46},
+  number={5},
+  pages={2555--2568},
+  year={2022},
+  publisher={IEEE}
+}
+
+@article{ganet,
+  title={GAnet: genetic algorithm platform for pipe network optimisation},
+  author={Morley, MS and Atkinson, RM and Savi{\'c}, DA and Walters, GA},
+  journal={Advances in engineering software},
+  volume={32},
+  number={6},
+  pages={467--475},
+  year={2001},
+  publisher={Elsevier}
+}
+
+@inproceedings{polylanenet,
+  title={Polylanenet: Lane estimation via deep polynomial regression},
+  author={Tabelini, Lucas and Berriel, Rodrigo and Paixao, Thiago M and Badue, Claudine and De Souza, Alberto F and Oliveira-Santos, Thiago},
+  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},
+  pages={6150--6156},
+  year={2021},
+  organization={IEEE}
+}
+
+@inproceedings{bezierlanenet,
+  title={Rethinking efficient lane detection via curve modeling},
+  author={Feng, Zhengyang and Guo, Shaohua and Tan, Xin and Xu, Ke and Wang, Min and Ma, Lizhuang},
+  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+  pages={17062--17070},
+  year={2022}
+}
+
+
+@article{yolox,
+  title={YOLOX: Exceeding YOLO series in 2021},
+  author={Zheng, Ge and Songtao, Liu and Feng, Wang and Zeming, Li and Jian, Sun and others},
+  journal={arXiv preprint arXiv:2107.08430},
+  year={2021},
+  publisher={arXiv}
+}
+
+@inproceedings{lstr,
+  title={End-to-end lane shape prediction with transformers},
+  author={Liu, Ruijin and Yuan, Zejian and Liu, Tie and Xiong, Zhiliang},
+  booktitle={Proceedings of the IEEE/CVF winter conference on applications of computer vision},
+  pages={3694--3702},
+  year={2021}
+}
+
+@inproceedings{detr,
+  title={End-to-end object detection with transformers},
+  author={Carion, Nicolas and Massa, Francisco and Synnaeve, Gabriel and Usunier, Nicolas and Kirillov, Alexander and Zagoruyko, Sergey},
+  booktitle={European conference on computer vision},
+  pages={213--229},
+  year={2020},
+  organization={Springer}
+}
+
+@inproceedings{o2o,
+  title={What makes for end-to-end object detection?},
+  author={Sun, Peize and Jiang, Yi and Xie, Enze and Shao, Wenqi and Yuan, Zehuan and Wang, Changhu and Luo, Ping},
+  booktitle={International Conference on Machine Learning},
+  pages={9934--9944},
+  year={2021},
+  organization={PMLR}
+}
+
+@inproceedings{relationnet,
+  title={Relation networks for object detection},
+  author={Hu, Han and Gu, Jiayuan and Zhang, Zheng and Dai, Jifeng and Wei, Yichen},
+  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+  pages={3588--3597},
+  year={2018}
+}
+
+@article{date,
+  title={Date: Dual assignment for end-to-end fully convolutional object detection},
+  author={Chen, Yiqun and Chen, Qiang and Hu, Qinghao and Cheng, Jian},
+  journal={arXiv preprint arXiv:2211.13859},
+  year={2022}
+}
+
+@inproceedings{o3d,
+  title={End-to-end object detection with fully convolutional network},
+  author={Wang, Jianfeng and Song, Lin and Li, Zeming and Sun, Hongbin and Sun, Jian and Zheng, Nanning},
+  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
+  pages={15849--15858},
+  year={2021}
+}
+
+@inproceedings{learnnms,
+  title={Learning non-maximum suppression},
+  author={Hosang, Jan and Benenson, Rodrigo and Schiele, Bernt},
+  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+  pages={4507--4515},
+  year={2017}
+}
+
+
+@article{linecnn,
+  title={Line-cnn: End-to-end traffic line detection with line proposal unit},
+  author={Li, Xiang and Li, Jun and Hu, Xiaolin and Yang, Jian},
+  journal={IEEE Transactions on Intelligent Transportation Systems},
+  volume={21},
+  number={1},
+  pages={248--258},
+  year={2019},
+  publisher={IEEE}
+}
+
+@article{sparse,
+  title={Sparse Laneformer},
+  author={Liu, Ji and Zhang, Zifeng and Lu, Mingjie and Wei, Hongyang and Li, Dong and Xie, Yile and Peng, Jinzhang and Tian, Lu and Sirasao, Ashish and Barsoum, Emad},
+  journal={arXiv preprint arXiv:2404.07821},
+  year={2024}
+}
+
+@inproceedings{vil100,
+  title={Vil-100: A new dataset and a baseline model for video instance lane detection},
+  author={Zhang, Yujun and Zhu, Lei and Feng, Wei and Fu, Huazhu and Wang, Mingqian and Li, Qingxia and Li, Cheng and Wang, Song},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
+  pages={15681--15690},
+  year={2021}
+}
+
+@article{xu2022overview,
+  title={Overview frequency principle/spectral bias in deep learning},
+  author={Xu, Zhi-Qin John and Zhang, Yaoyu and Luo, Tao},
+  journal={arXiv preprint arXiv:2201.07395},
+  year={2022}
+}
+
+@inproceedings{stewart2016end,
+  title={End-to-end people detection in crowded scenes},
+  author={Stewart, Russell and Andriluka, Mykhaylo and Ng, Andrew Y},
+  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+  pages={2325--2333},
+  year={2016}
+}
+
+
+@inproceedings{yolact,
+  title={Yolact: Real-time instance segmentation},
+  author={Bolya, Daniel and Zhou, Chong and Xiao, Fanyi and Lee, Yong Jae},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
+  pages={9157--9166},
+  year={2019}
+}
+
+@article{alemi2016deep,
+  title={Deep variational information bottleneck},
+  author={Alemi, Alexander A and Fischer, Ian and Dillon, Joshua V and Murphy, Kevin},
+  journal={arXiv preprint arXiv:1612.00410},
+  year={2016}
+}
+
+@inproceedings{focal,
+  title={Focal loss for dense object detection},
+  author={Lin, Tsung-Yi and Goyal, Priya and Girshick, Ross and He, Kaiming and Doll{\'a}r, Piotr},
+  booktitle={Proceedings of the IEEE international conference on computer vision},
+  pages={2980--2988},
+  year={2017}
+}
+
+@inproceedings{resnet,
+  title={Deep residual learning for image recognition},
+  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
+  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+  pages={770--778},
+  year={2016}
+}
+
+@article{adam,
+  title={Adam: A method for stochastic optimization},
+  author={Kingma, Diederik P},
+  journal={arXiv preprint arXiv:1412.6980},
+  year={2014}
+}
+
+@inproceedings{dla,
+  title={Deep layer aggregation},
+  author={Yu, Fisher and Wang, Dequan and Shelhamer, Evan and Darrell, Trevor},
+  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+  pages={2403--2412},
+  year={2018}
+}
+
+@inproceedings{resa,
+  title={Resa: Recurrent feature-shift aggregator for lane detection},
+  author={Zheng, Tu and Fang, Hao and Zhang, Yi and Tang, Wenjian and Yang, Zheng and Liu, Haifeng and Cai, Deng},
+  booktitle={Proceedings of the AAAI conference on artificial intelligence},
+  volume={35},
+  number={4},
+  pages={3547--3554},
+  year={2021}
+}
+
+@article{bsnet,
+  title={Bsnet: Lane detection via draw b-spline curves nearby},
+  author={Chen, Haoxin and Wang, Mengmeng and Liu, Yong},
+  journal={arXiv preprint arXiv:2301.06910},
+  year={2023}
+}
+
+@inproceedings{eigenlanes,
+  title={Eigenlanes: Data-driven lane descriptors for structurally diverse lanes},
+  author={Jin, Dongkwon and Park, Wonhui and Jeong, Seong-Gyun and Kwon, Heeyeon and Kim, Chang-Su},
+  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
+  pages={17163--17171},
+  year={2022}
+}
+
+@article{laneaf,
+  title={Laneaf: Robust multi-lane detection with affinity fields},
+  author={Abualsaud, Hala and Liu, Sean and Lu, David B and Situ, Kenny and Rangesh, Akshay and Trivedi, Mohan M},
+  journal={IEEE Robotics and Automation Letters},
+  volume={6},
+  number={4},
+  pages={7477--7484},
+  year={2021},
+  publisher={IEEE}
+}
+
+@inproceedings{enetsad,
+  title={Learning lightweight lane detection cnns by self attention distillation},
+  author={Hou, Yuenan and Ma, Zheng and Liu, Chunxiao and Loy, Chen Change},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
+  pages={1013--1021},
+  year={2019}
+}
+
+@inproceedings{pointlanenet,
+  title={Pointlanenet: Efficient end-to-end cnns for accurate real-time lane detection},
+  author={Chen, Zhenpeng and Liu, Qianfei and Lian, Chenfan},
+  booktitle={2019 IEEE intelligent vehicles symposium (IV)},
+  pages={2563--2568},
+  year={2019},
+  organization={IEEE}
+}
+
+
+@article{pss,
+  title={Object detection made simpler by eliminating heuristic NMS},
+  author={Zhou, Qiang and Yu, Chaohui},
+  journal={IEEE Transactions on Multimedia},
+  volume={25},
+  pages={9254--9262},
+  year={2023},
+  publisher={IEEE}
+}
\ No newline at end of file