67 citations · 73 across the 5 of their papers we have counts for
5 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…
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…
Cyber Mobility Mirror: A Deep Learning-based Real-World Object Perception Platform Using Roadside LiDAR
Zhengwei Bai, Saswat Priyadarshi Nayak, Xuanpeng Zhao +6
Object perception plays a fundamental role in Cooperative Driving Automation (CDA) which is regarded as a revolutionary promoter for the next-generation transportation systems. How…
Where is My Stuff? An Interactive System for Spatial Relations
E. Akin Sisbot, Jonathan H. Connell
In this paper we present a system that detects and tracks objects and agents, computes spatial relations, and communicates those relations to the user using speech. Our system is a…