近三年车道线检测paper with code

今天和大家分享2019-2021年车道线检测领域含有开源代码的论文。

ArXiv2021

LaneAF: Robust Multi-Lane Detection with Affinity Fields

论文下载地址：https://arxiv.org/pdf/2103.12040.pdf
开源代码地址：https://github.com/sel118/LaneAF

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

论文下载地址：https://arxiv.org/pdf/2105.05003.pdf
开源代码地址：https://github.com/aliyun/conditional-lane-detection

CVPR2021

Keep your Eyes on the Lane: Real-time Attention-guided Lane Detection

论文下载地址：https://arxiv.org/pdf/2010.12035.pdf
开源代码地址：https://github.com/lucastabelini/LaneATT

AAAI2021

RESA: Recurrent Feature-Shift Aggregator for Lane Detection

论文下载地址：https://arxiv.org/pdf/2008.13719.pdf
开源代码地址：https://github.com/ZJULearning/resa

IEEE Transactions on Intelligent Transportation Systems 2021

Key Points Estimation and Point Instance Segmentation Approach for Lane Detection

论文下载地址：https://arxiv.org/pdf/2002.06604.pdf
开源代码地址：https://github.com/koyeongmin/PINet_new

CVPR2020

Inter-Region Affinity Distillation for Road Marking Segmentation

论文下载地址：https://arxiv.org/pdf/2004.05304v1.pdf
开源代码地址：https://github.com/cardwing/Codes-for-IntRA-KD

ECCV2020

Ultra Fast Structure-aware Deep Lane Detection

论文下载地址：https://arxiv.org/pdf/2004.11757.pdf
开源代码地址：https://github.com/cfzd/Ultra-Fast-Lane-Detection

Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection

论文下载地址：https://arxiv.org/pdf/2003.10656.pdf
开源代码地址：https://github.com/yuliangguo/Pytorch_Generalized_3D_Lane_Detection

WACV2020

End-to-end Lane Shape Prediction with Transformers

论文下载地址：https://arxiv.org/pdf/2011.04233.pdf
开源代码地址：https://github.com/liuruijin17/LSTR

IV2020

Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer

论文下载地址：https://arxiv.org/pdf/2002.01177.pdf
开源代码地址：https://github.com/Chenzhaowei13/Light-Condition-Style-Transfer

ICPR2020

PolyLaneNet: Lane Estimation via Deep Polynomial Regression

论文下载地址：https://arxiv.org/pdf/2004.10924.pdf
开源代码地址：https://github.com/lucastabelini/PolyLaneNet

ICCV2019

Learning Lightweight Lane Detection CNNs by Self Attention Distillation

论文下载地址：https://openaccess.thecvf.com/content_ICCV_2019/papers/Hou_Learning_Lightweight_Lane_Detection_CNNs_by_Self_Attention_Distillation_ICCV_2019_paper.pdf
开源代码地址：https://github.com/cardwing/Codes-for-Lane-Detection

End-to-end Lane Detection through Differentiable Least-Squares Fitting

论文下载地址：https://arxiv.org/pdf/1902.00293
开源代码地址：https://github.com/wvangansbeke/LaneDetection_End2End

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