no code implementations • 17 Nov 2023 • Yizhou Wang, Jen-Hao Cheng, Jui-Te Huang, Sheng-Yao Kuan, Qiqian Fu, Chiming Ni, Shengyu Hao, Gaoang Wang, Guanbin Xing, Hui Liu, Jenq-Neng Hwang
This kind of radar format can enable machine learning models to generate more reliable object perception results after interacting and fusing the information or features between the camera and radar.
no code implementations • 31 Oct 2021 • Xiangyu Gao, Hui Liu, Sumit Roy, Guanbin Xing, Ali Alansari, Youchen Luo
Detecting harmful carried objects plays a key role in intelligent surveillance systems and has widespread applications, for example, in airport security.
no code implementations • 4 Apr 2021 • Xiangyu Gao, Sumit Roy, Guanbin Xing, Sian Jin
Millimeter-wave (mmWave) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) features that require accurate location and Doppler velocity estimates of objects, independent of environmental conditions.
1 code implementation • 9 Feb 2021 • Yizhou Wang, Zhongyu Jiang, Yudong Li, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
Finally, we propose a method to evaluate the object detection performance of the RODNet.
no code implementations • 22 Jan 2021 • Xiangyu Gao, Sumit Roy, Guanbin Xing
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support advanced driver-assistance system features.
3 code implementations • 13 Nov 2020 • Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
Millimeter-wave radars are being increasingly integrated into commercial vehicles to support new advanced driver-assistance systems by enabling robust and high-performance object detection, localization, as well as recognition - a key component of new environmental perception.
1 code implementation • 3 Mar 2020 • Yizhou Wang, Zhongyu Jiang, Xiangyu Gao, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
Radar is usually more robust than the camera in severe driving scenarios, e. g., weak/strong lighting and bad weather.
1 code implementation • 29 Dec 2019 • Xiangyu Gao, Guanbin Xing, Sumit Roy, Hui Liu
Millimeter-wave (mmW) radars are being increasingly integrated in commercial vehicles to support new Adaptive Driver Assisted Systems (ADAS) for its ability to provide high accuracy location, velocity, and angle estimates of objects, largely independent of environmental conditions.