Lane detection is essential for many aspects of autonomous driving,such as lane-based navigation and high-definition(HD)map modeling.Although lane detection is challenging especially with complex road conditions,consi...Lane detection is essential for many aspects of autonomous driving,such as lane-based navigation and high-definition(HD)map modeling.Although lane detection is challenging especially with complex road conditions,considerable progress has been witnessed in this area in the past several years.In this survey,we review recent visual-based lane detection datasets and methods.For datasets,we categorize them by annotations,provide detailed descriptions for each category,and show comparisons among them.For methods,we focus on methods based on deep learning and organize them in terms of their detection targets.Moreover,we introduce a new dataset with more detailed annotations for HD map modeling,a new direction for lane detection that is applicable to autonomous driving in complex road conditions,a deep neural network LineNet for lane detection,and show its application to HD map modeling.展开更多
In the first week of May 2021,researchers from four different institutions:Google,Tsinghua University,Oxford University,and Facebook shared their latest work[1–4]on ar Xiv.org at almost the same time,each proposing n...In the first week of May 2021,researchers from four different institutions:Google,Tsinghua University,Oxford University,and Facebook shared their latest work[1–4]on ar Xiv.org at almost the same time,each proposing new learning architectures,consisting mainly of linear layers,claiming them to be comparable or superior to convolutional-based models.展开更多
基金This work was supported by the National Natural Science Foundation of China under Grant Nos.61902210 and 61521002a research grant from the Beijing Higher Institution Engineering Research Center,and the Tsinghua-Tencent Joint Laboratory for Internet Innovation Technology.
文摘Lane detection is essential for many aspects of autonomous driving,such as lane-based navigation and high-definition(HD)map modeling.Although lane detection is challenging especially with complex road conditions,considerable progress has been witnessed in this area in the past several years.In this survey,we review recent visual-based lane detection datasets and methods.For datasets,we categorize them by annotations,provide detailed descriptions for each category,and show comparisons among them.For methods,we focus on methods based on deep learning and organize them in terms of their detection targets.Moreover,we introduce a new dataset with more detailed annotations for HD map modeling,a new direction for lane detection that is applicable to autonomous driving in complex road conditions,a deep neural network LineNet for lane detection,and show its application to HD map modeling.
基金supported by the National Natural Science Foundation of China(Project No.61521002)。
文摘In the first week of May 2021,researchers from four different institutions:Google,Tsinghua University,Oxford University,and Facebook shared their latest work[1–4]on ar Xiv.org at almost the same time,each proposing new learning architectures,consisting mainly of linear layers,claiming them to be comparable or superior to convolutional-based models.
