Labels are the cornerstone of supervised machine learning algorithms. Most visual
recognition methods are fully supervised using bounding boxes or pixel-wise segmentations …

This article presents a lane detection system in unstructured, complex environments in real
time. We formulated lane detection as a binary segmentation problem and proposed a novel …

Robust understanding of the lane position and type is essential for changing lanes in
autonomous vehicles. However, accomplishing this task in real time with high level of …

Lane detection is a basic but challenging task in autonomous driving systems. With a
combination of high-level and low-level information, early studies of lane detection have …

With the rapid development of urban ground transportation, lane line detection is gradually
becoming a major technological direction to help to realize safe vehicle navigation …

Lane detection plays a pivotal role in the successful implementation of Advanced Driver
Assistance Systems (ADASs), which are essential for detecting the road's lane markings and …

Lane detection is a fundamental task for autonomous driving. Most existed deep learning-
based methods use a combination of semantic segmentation and post-processing for lane …

Lane detection is a vital component of intelligent driving systems, offering indispensable
functionality to keep the vehicle within its designated lane, thereby reducing the risk of lane …

Lane detection is one of the fundamental modules in self-driving. In this paper we employ a
transformer-only method for lane detection, thus it could benefit from the blooming …

Abstract 3D lane detection based on LiDAR point clouds is a challenging task that requires
precise locations, accurate topologies, and distinguishable instances. In this paper, we …