Methods for 3D lane detection have been recently proposed to address the issue of
inaccurate lane layouts in many autonomous driving scenarios (uphill/downhill, bump, etc.) …

Abstract 3D lane detection which plays a crucial role in vehicle routing, has recently been a
rapidly developing topic in autonomous driving. Previous works struggle with practicality due …

We present ONCE-3DLanes, a real-world autonomous driving dataset with lane layout
annotation in 3D space. Conventional 2D lane detection from a monocular image yields …

Detecting 3D lanes from the camera is a rising problem for autonomous vehicles. In this task,
the correct camera pose is the key to generating accurate lanes, which can transform an …

Abstract 3D lane detection usually builds a dense correspondence between the front-view
space and the BEV space to estimate lane points in the 3D space. 3D lanes only occupy a …

In this paper, we propose an advanced approach in targeting the problem of monocular 3D
lane detection by leveraging geometry structure underneath the process of 2D to 3D lane …

Lane detection is crucial for autonomous driving systems (ADS), utilizing sensors like
cameras and LiDAR to identify lanes and understand vehicle position, direction, and lane …

Monocular 3D lane detection has become a fundamental problem in the context of
autonomous driving which comprises the tasks of finding the road surface and locating lane …

Introduction Semantic segmentation is a crucial visual representation learning task for
autonomous driving systems, as it enables the perception of surrounding objects and road …

The inability of semantic segmentation methods to detect anomaly road obstacles not pre-
defined in the datasets significantly hinders the safety-critical application in autonomous …