activity
20182021
most citedPoint-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

102 citations · 105 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO20213 cited

MultiCruise: Eco-Lane Selection Strategy with Eco-Cruise Control for Connected and Automated Vehicles

Shunsuke Aoki, Lung En Jan, Junfeng Zhao +4

Connected and Automated Vehicles (CAVs) have real-time information from the surrounding environment by using local on-board sensors, V2X (Vehicle-to-Everything) communications, pre…

cs.CV2020

CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion

Iljoo Baek, Tzu-Chieh Tai, Manoj Bhat +5

Reliable curb detection is critical for safe autonomous driving in urban contexts. Curb detection and tracking are also useful in vehicle localization and path planning. Past work…

eess.SY2020

Co-simulation Platform for Developing InfoRich Energy-Efficient Connected and Automated Vehicles

Shunsuke Aoki, Lung En Jan, Junfeng Zhao +4

With advances in sensing, computing, and communication technologies, Connected and Automated Vehicles (CAVs) are becoming feasible. The advent of CAVs presents new opportunities to…

cs.CV2020102 cited

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

Weijing Shi, Ragunathan, Rajkumar

In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud. Towards this end, we encode the point cloud efficiently in a fixed radius near-neighbor…

cs.CV2018

Real-time Detection, Tracking, and Classification of Moving and Stationary Objects using Multiple Fisheye Images

Iljoo Baek, Albert Davies, Geng Yan +2

The ability to detect pedestrians and other moving objects is crucial for an autonomous vehicle. This must be done in real-time with minimum system overhead. This paper discusses t…