The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …

Recently, the development and application of lane line departure warning systems have
been in the market. For any of the systems, the key part of lane line tracking, lane line …

Training deep models for lane detection is challenging due to the very subtle and sparse
supervisory signals inherent in lane annotations. Without learning from much richer context …

Modern cars are incorporating an increasing number of driver assist features, among which
automatic lane keeping. The latter allows the car to properly position itself within the road …

Perception techniques for autonomous driving should be adaptive to various environments.
In essential perception modules for traffic line detection, many conditions should be …

In this paper, we propose a unified end-to-end trainable multi-task network that jointly
handles lane and road marking detection and recognition that is guided by a vanishing point …

Perception is an essential task for self-driving cars, but most perception tasks are usually
handled independently. We propose a unified neural network named DLT-Net to detect …

Over the past few decades, the need has arisen for multi-lane detection algorithms for use in
vehicle safety-related applications. In this paper we propose a new multi-lane detection …

Aiming at vehicle and lane detections on road scene, this paper proposes a vehicle and
lane line joint detection method suitable for car following scenes. This method uses the …

Abstract Vectorized High-Definition (HD) map construction requires predictions of the
category and point coordinates of map elements (eg road boundary lane divider pedestrian …