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

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
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引用次数: 0

Abstract

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.

回顾过去十年:路况解析走向安全舒适的自动驾驶
道路场景分析是自动驾驶车辆和智能道路检测系统的关键能力。最近的研究越来越关注通过改进可行驶区域和道路缺陷的检测来提高驾驶安全性和舒适性。本文回顾了过去十年中为通用语义分割和专门道路场景解析任务开发的最先进的网络。它还包括在五个公共数据集上对这些网络进行广泛的实验比较。此外,我们还探讨了该领域的关键挑战和新兴趋势,旨在指导研究人员开发下一代模型,以实现更有效、更可靠的道路场景解析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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