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LLNet: A Lightweight Lane Line Detection Network

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Image and Graphics (ICIG 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12888))

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Abstract

The lane line detection methods based on semantic segmentation networks have achieved remarkable results in recent years. However, the semantic segmentation networks are aimed at the pixel level. These methods have a large amount of computation, which can reduce the real-time performance. To reduce the calculation, we propose a Light-weight Lane line detection Network (LLNet). A new sub-layer is established. We also adopt a jumping structure between two sub-layers to enhance the supervisory role of ground truth. Furthermore, we adopt two branches, including instance segmentation and embeddable branch. The combination of two branches can filter out the wrongly detected pixels and further improve the accuracy of detection. Experimental results in the Tusimple dataset show that the detection accuracy of the proposed network is comparable with LaneNet. Meanwhile, it has good real-time performance, and the processing time of a single image is 10.285 ms, which is about one-half of LaneNet.

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Author information

Authors and Affiliations

  1. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, 230031, China

    Lu Zhang, Bin Kong & Can Wang

  2. University of Science and Technology of China, Hefei, 230026, China

    Lu Zhang

  3. The Key Laboratory of Biomimetic Sensing and Advanced Robot Technology, Hefei, 230031, China

    Lu Zhang, Bin Kong & Can Wang

Authors
  1. Lu Zhang
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  2. Bin Kong
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  3. Can Wang
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Corresponding author

Correspondence to Bin Kong .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Yuxin Peng

  2. Tsinghua University, Beijing, China

    Shi-Min Hu

  3. Tampere University, Tampere, Finland

    Moncef Gabbouj

  4. Zhejiang University, Hangzhou, China

    Kun Zhou

  5. Technion – Israel Institute of Technology, Haifa, Israel

    Michael Elad

  6. Tsinghua University, Beijing, China

    Kun Xu

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Zhang, L., Kong, B., Wang, C. (2021). LLNet: A Lightweight Lane Line Detection Network. In: Peng, Y., Hu, SM., Gabbouj, M., Zhou, K., Elad, M., Xu, K. (eds) Image and Graphics. ICIG 2021. Lecture Notes in Computer Science(), vol 12888. Springer, Cham. https://doi.org/10.1007/978-3-030-87355-4_30

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  • DOI: https://doi.org/10.1007/978-3-030-87355-4_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87354-7

  • Online ISBN: 978-3-030-87355-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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