MFANet: Mixed Feature Attention Network for Port Lane Detection-Reference-Cited by-同舟云学术

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MFANet: Mixed Feature Attention Network for Port Lane Detection

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 42nd Chinese Control Conference (CCC)
language:
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Author:

Zhang Jinwei¹,Su Jinya¹,Yi Dewei²,Yang Jun¹

Affiliation:

1. Ministry of Education, and the School of Automation, Southeast University,Key Laboratory of Measurement and Control of Complex Systems of Engineering,Nanjing,China,210096

2. University of Aberdeen,Department of Computing Science,Aberdeen,U.K.,AB24 3UE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10239690/10239711/10240831.pdf?arnumber=10240831

Reference19 articles.

1. Fastdraw: Addressing the Long Tail of Lane Detection by Adapting a Sequential Prediction Network;philion;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2020

2. End-to-End Lane Marker Detection via Row-wise Classification

3. PolyLaneNet: Lane Estimation via Deep Polynomial Regression;tabelini;Proceedings of International Conference on Pattern Recognition,2020

4. Fastdraw: Inter-Region Affinity Distillation for Road Marking Segmentation;hou;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2020

5. Learning Lightweight Lane Detection CNNs by Self Attention Distillation

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