The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …

Abstract Automated Driving Systems (ADS) open up a new domain for the automotive
industry and offer new possibilities for future transportation with higher efficiency and …

We introduce Argoverse 2 (AV2)-a collection of three datasets for perception and forecasting
research in the self-driving domain. The annotated Sensor Dataset contains 1,000 …

Autonomous vehicles require constant environmental perception to obtain the distribution of
obstacles to achieve safe driving. Specifically, 3D object detection is a vital functional …

Light detection and ranging (LiDAR) sensors enable precision sensing of an object in 3D.
LiDAR technology is widely used in metrology, environment monitoring, archaeology, and …

Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

The research community has increasing interest in autonomous driving research, despite
the resource intensity of obtaining representative real world data. Existing self-driving …

Navigation/positioning systems have become critical to many applications, such as
autonomous driving, Internet of Things (IoT), Unmanned Aerial Vehicle (UAV), and smart …

Current perception models in autonomous driving have become notorious for greatly relying
on a mass of annotated data to cover unseen cases and address the long-tail problem. On …

Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …