151 citations · 331 across the 24 of their papers we have counts for
24 papers
Cooperverse: A Mobile-Edge-Cloud Framework for Universal Cooperative Perception with Mixed Connectivity and Automation
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
Cooperative perception (CP) is attracting increasing attention and is regarded as the core foundation to support cooperative driving automation, a potential key solution to address…
VINet: Lightweight, Scalable, and Heterogeneous Cooperative Perception for 3D Object Detection
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
Utilizing the latest advances in Artificial Intelligence (AI), the computer vision community is now witnessing an unprecedented evolution in all kinds of perception tasks, particul…
Driver Digital Twin for Online Prediction of Personalized Lane Change Behavior
Xishun Liao, Xuanpeng Zhao, Ziran Wang +5
Connected and automated vehicles (CAVs) are supposed to share the road with human-driven vehicles (HDVs) in a foreseeable future. Therefore, considering the mixed traffic environme…
A Survey and Framework of Cooperative Perception: From Heterogeneous Singleton to Hierarchical Cooperation
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +4
Perceiving the environment is one of the most fundamental keys to enabling Cooperative Driving Automation (CDA), which is regarded as the revolutionary solution to addressing the s…
PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDAR
Zhengwei Bai, Guoyuan Wu, Matthew J. Barth +3
3D object detection plays a fundamental role in enabling autonomous driving, which is regarded as the significant key to unlocking the bottleneck of contemporary transportation sys…
Spatiotemporal Transformer Attention Network for 3D Voxel Level Joint Segmentation and Motion Prediction in Point Cloud
Zhensong Wei, Xuewei Qi, Zhengwei Bai +6
Environment perception including detection, classification, tracking, and motion prediction are key enablers for automated driving systems and intelligent transportation applicatio…