1 citations · 2 across the 6 of their papers we have counts for
6 papers
A Robust and Efficient Multi-Agent Reinforcement Learning Framework for Traffic Signal Control
Sheng-You Huang, Hsiao-Chuan Chang, Yen-Chi Chen +6
Reinforcement Learning (RL) in Traffic Signal Control (TSC) faces significant hurdles in real-world deployment due to limited generalization to dynamic traffic flow variations. Exi…
Boosting Online 3D Multi-Object Tracking through Camera-Radar Cross Check
Sheng-Yao Kuan, Jen-Hao Cheng, Hsiang-Wei Huang +6
In the domain of autonomous driving, the integration of multi-modal perception techniques based on data from diverse sensors has demonstrated substantial progress. Effectively surp…
RT-Pose: A 4D Radar Tensor-based 3D Human Pose Estimation and Localization Benchmark
Yuan-Hao Ho, Jen-Hao Cheng, Sheng Yao Kuan +5
Traditional methods for human localization and pose estimation (HPE), which mainly rely on RGB images as an input modality, confront substantial limitations in real-world applicati…
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024
Benjamin Kiefer, Lojze Žust, Matej Kristan +46
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenge…
Vision meets mmWave Radar: 3D Object Perception Benchmark for Autonomous Driving
Yizhou Wang, Jen-Hao Cheng, Jui-Te Huang +8
Sensor fusion is crucial for an accurate and robust perception system on autonomous vehicles. Most existing datasets and perception solutions focus on fusing cameras and LiDAR. How…
CenterRadarNet: Joint 3D Object Detection and Tracking Framework using 4D FMCW Radar
Jen-Hao Cheng, Sheng-Yao Kuan, Hugo Latapie +2
Robust perception is a vital component for ensuring safe autonomous and assisted driving. Automotive radar (77 to 81 GHz), which offers weather-resilient sensing, provides a comple…