2 citations · 3 across the 5 of their papers we have counts for
5 papers
Lightweight LiDAR-Based Cone Detection Framework Using Random Forest for Formula Student Driverless
Márk Mező-Kerekes, Péter Praksz, Chang Liu
Reliable, low-latency perception is crucial for Formula Student Driverless vehicles, yet many existing pipelines rely on deep learning and multi-sensor fusion, often requiring GPU…
Risk-Aware World Model Predictive Control for Generalizable End-to-End Autonomous Driving
Jiangxin Sun, Feng Xue, Teng Long +4
With advances in imitation learning (IL) and large-scale driving datasets, end-to-end autonomous driving (E2E-AD) has made great progress recently. Currently, IL-based methods have…
Path Planning based on 2D Object Bounding-box
Yanliang Huang, Liguo Zhou, Chang Liu +1
The implementation of Autonomous Driving (AD) technologies within urban environments presents significant challenges. These challenges necessitate the development of advanced perce…
YOLO-BEV: Generating Bird's-Eye View in the Same Way as 2D Object Detection
Chang Liu, Liguo Zhou, Yanliang Huang +1
Vehicle perception systems strive to achieve comprehensive and rapid visual interpretation of their surroundings for improved safety and navigation. We introduce YOLO-BEV, an effic…
THMA: Tencent HD Map AI System for Creating HD Map Annotations
Kun Tang, Xu Cao, Zhipeng Cao +8
Nowadays, autonomous vehicle technology is becoming more and more mature. Critical to progress and safety, high-definition (HD) maps, a type of centimeter-level map collected using…