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<p>Road scene parsing is a crucial capability for self-driving vehicles and intelligent road inspection systems. Recent research has increasingly focused on enhancing driving safety and comfort by improving the detection of both drivable areas and road defects. This article reviews state-of-the-art networks developed over the past decade for both general-purpose semantic segmentation and specialized road scene parsing tasks. It also includes extensive experimental comparisons of these networks across five public datasets. Additionally, we explore the key challenges and emerging trends in the field, aiming to guide researchers toward developing next-generation models for more effective and reliable road scene parsing.</p>

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A glance over the past decade: road scene parsing towards safe and comfortable autonomous driving

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年3月13日

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  • Rui Fan,
  • Jiahang Li,
  • Jiaqi Li,
  • Jiale Wang,
  • Ziwei Long,
  • Ning Jia,
  • Yanan Liu,
  • Wenshuo Wang,
  • Mohammud J. Bocus,
  • Sergey Vityazev,
  • Xieyuanli Chen,
  • Junhao Xiao,
  • Stepan Andreev,
  • Huimin Lu,
  • Alexander Dvorkovich

摘要

Road scene parsing is a crucial capability for self-driving vehicles and intelligent road inspection systems. Recent research has increasingly focused on enhancing driving safety and comfort by improving the detection of both drivable areas and road defects. This article reviews state-of-the-art networks developed over the past decade for both general-purpose semantic segmentation and specialized road scene parsing tasks. It also includes extensive experimental comparisons of these networks across five public datasets. Additionally, we explore the key challenges and emerging trends in the field, aiming to guide researchers toward developing next-generation models for more effective and reliable road scene parsing.