7 citations · 15 across the 5 of their papers we have counts for
5 papers
WARM-3D: A Weakly-Supervised Sim2Real Domain Adaptation Framework for Roadside Monocular 3D Object Detection
Xingcheng Zhou, Deyu Fu, Walter Zimmer +4
Existing roadside perception systems are limited by the absence of publicly available, large-scale, high-quality 3D datasets. Exploring the use of cost-effective, extensive synthet…
TUMTraf V2X Cooperative Perception Dataset
Walter Zimmer, Gerhard Arya Wardana, Suren Sritharan +3
Cooperative perception offers several benefits for enhancing the capabilities of autonomous vehicles and improving road safety. Using roadside sensors in addition to onboard sensor…
GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events
Xingcheng Zhou, Alois C. Knoll
The recognition and understanding of traffic incidents, particularly traffic accidents, is a topic of paramount importance in the realm of intelligent transportation systems and in…
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook
Mingyu Liu, Ekim Yurtsever, Jonathan Fossaert +5
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for…
Real-Time And Robust 3D Object Detection with Roadside LiDARs
Walter Zimmer, Jialong Wu, Xingcheng Zhou +1
This work aims to address the challenges in autonomous driving by focusing on the 3D perception of the environment using roadside LiDARs. We design a 3D object detection model that…