Autonomous vehicles were experiencing rapid development in the past few years. However,
achieving full autonomy is not a trivial task, due to the nature of the complex and dynamic …

Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …

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.) …

Constructing HD semantic maps is a central component of autonomous driving. However,
traditional pipelines require a vast amount of human efforts and resources in annotating and …

We present Argoverse, a dataset designed to support autonomous vehicle perception tasks
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …

High-definition maps (HD maps) are a key component of most modern self-driving systems
due to their valuable semantic and geometric information. Unfortunately, building HD maps …

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 …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Monocular 3D lane detection is a challenging task due to its lack of depth information. A
popular solution is to first transform the front-viewed (FV) images or features into the bird-eye …

Multi-sensor perception is crucial to ensure the reliability and accuracy in autonomous
driving system, while multi-object tracking (MOT) improves that by tracing sequential …