Reliable detection and tracking of surrounding objects are indispensable for comprehensive
motion prediction and planning of autonomous vehicles. Due to the limitations of individual …

In the domain of autonomous driving, the integration of multi-modal perception techniques
based on data from diverse sensors has demonstrated substantial progress. Effectively …

In this work, we address the problem of multi-vehicle detection and tracking for traffic
monitoring applications. We preset a novel intelligent visual sensor for tracking-by-detection …

View Video Presentation: https://doi. org/10.2514/6.2022-0362. vid Autonomous operations
are a crucial aspect in the context of Urban Air Mobility and other emerging aviation markets …

Multi-object tracking (MOT) with camera-LiDAR fusion demands accurate results of object
detection, affinity computation and data association in real time. This paper presents an …

The tracking accuracy of nearby vehicles determines the safety and feasibility of driver
assistance systems or autonomous vehicles. Recent research has been active to employ …

3D multi-object tracking is a crucial component in the perception system of autonomous
driving vehicles. Tracking all dynamic objects around the vehicle is essential for tasks such …

Autonomous mobile systems such as vehicles or robots are equipped with multiple sensor
modalities including Lidar, RGB, and Radar. The fusion of multi-modal information can …

We formulate camera and LiDAR fusion tracking as a sequential decision-making process.
With our deep reinforcement learning framework, we try to optimize the tracking trajectory to …

Abstract Multi-Target Multi-Camera tracking is a fundamental task for intelligent traffic
systems. The track 1 of AI City Challenge 2022 aims at the city-scale multi-camera vehicle …