Abstract 3D lane detection from monocular images is a fundamental yet challenging task in
autonomous driving. Recent advances primarily rely on structural 3D surrogates (eg, bird's …

Deep learning-based lane detection (LD) plays a critical role in autonomous driving
systems, such as adaptive cruise control. However, it is vulnerable to backdoor attacks …

In this paper, we revisit the limitations of anchor-based lane detection methods, which have
predominantly focused on fixed anchors that stem from the edges of the image, disregarding …

Lane detection (LD) is an essential component of autonomous driving systems, providing
fundamental functionalities like adaptive cruise control and automated lane centering …

Lane marker detection is a crucial component of the autonomous driving and driver
assistance systems. Modern deep lane detection methods with anchor-based lane …

The gradual proliferation of high-definition (HD) maps has played a pivotal role in the
advancement of intelligent vehicles. However, a considerable number of vehicles still face …

Lane detection is fundamental to autonomous driving, yet remains challenging in complex
environments with occlusions, ambiguous markings, and varied lighting. We introduce the …

In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane
detection. Most existing methods perform sparse supervision on a subset of high-scoring …

In this study, we introduce an online monocular lane mapping approach that solely relies on
a single camera and odometry for generating spline-based maps. Our proposed technique …

Lane detection is critical for intelligent vehicles to sense drivable areas. Compared to
general objects, lane lines are slender-shaped, easily occluded, or defaced. Therefore, the …