1 code implementation • CVPR 2024 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
By enhancing trajectory prediction accuracy and addressing the challenges of out-of-sight objects, our work significantly contributes to improving the safety and reliability of autonomous driving in complex environments.
1 code implementation • 8 Dec 2023 • Deyuan Qu, Qi Chen, Tianyu Bai, HongSheng Lu, Heng Fan, Hao Zhang, Song Fu, Qing Yang
Cooperative perception for connected and automated vehicles is traditionally achieved through the fusion of feature maps from two or more vehicles.
no code implementations • 9 Oct 2023 • Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu
In summary, our approach offers a promising solution to the challenges faced by layout sequence and trajectory prediction models in real-world settings, paving the way for utilizing sensor data from mobile phones to accurately predict pedestrian bounding box trajectories.
no code implementations • 26 Jul 2023 • Mahyar Abbasian, Taha Rajabzadeh, Ahmadreza Moradipari, Seyed Amir Hossein Aqajari, HongSheng Lu, Amir Rahmani
Generative Adversarial Networks (GAN) have emerged as a formidable AI tool to generate realistic outputs based on training datasets.
no code implementations • 30 Jun 2023 • Yun Chen, Nuria González-Prelcic, Takayuki Shimizu, HongSheng Lu
One strategy to obtain user location information in a wireless network operating at millimeter wave (mmWave) is based on the exploitation of the geometric relationships between the channel parameters and the user position.
no code implementations • 22 Nov 2022 • Hansi Liu, Kristin Dana, Marco Gruteser, HongSheng Lu
During inference, it generates refined position estimations based only on pedestrians' phone data that consists of GPS, IMU and FTM.
1 code implementation • ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) 2022 • Hansi Liu, Abrar Alali, Mohamed Ibrahim, Bryan Bo Cao, Nicholas Meegan, Hongyu Li, Marco Gruteser, Shubham Jain, Kristin Dana, Ashwin Ashok, Bin Cheng, HongSheng Lu
In this paper, we present Vi-Fi, a multi-modal system that leverages a user’s smartphone WiFi Fine Timing Measurements (FTM) and inertial measurement unit (IMU) sensor data to associate the user detected on a camera footage with their corresponding smartphone identifier (e. g. WiFi MAC address).
no code implementations • 4 Apr 2022 • Yun Chen, Joan Palacios, Nuria González-Prelcic, Takayuki Shimizu, HongSheng Lu
High resolution compressive channel estimation provides information for vehicle localization when a hybrid mmWave MIMO system is considered.
no code implementations • 5 Nov 2021 • Peng Gao, Brian Reily, Rui Guo, HongSheng Lu, Qingzhao Zhu, Hao Zhang
In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects.
no code implementations • 16 Nov 2020 • Peng Gao, Rui Guo, HongSheng Lu, Hao Zhang
Collaborative object localization aims to collaboratively estimate locations of objects observed from multiple views or perspectives, which is a critical ability for multi-agent systems such as connected vehicles.
no code implementations • 16 Nov 2020 • Ehsan Emad Marvasti, Arash Raftari, Amir Emad Marvasti, Yaser P. Fallah, Rui Guo, HongSheng Lu
In this paper, we examine the requirements, limitations, and performance of different cooperative perception techniques, and present an in-depth analysis of the notion of Deep Feature Sharing (DFS).
no code implementations • 12 Mar 2020 • Monowar Hasan, Sibin Mohan, Takayuki Shimizu, HongSheng Lu
Modern vehicular wireless technology enables vehicles to exchange information at any time, from any place, to any network -- forms the vehicle-to-everything (V2X) communication platforms.
Networking and Internet Architecture Cryptography and Security
no code implementations • 19 Feb 2020 • Ehsan Emad Marvasti, Arash Raftari, Amir Emad Marvasti, Yaser P. Fallah, Rui Guo, HongSheng Lu
The recent advancements in communication and computational systems has led to significant improvement of situational awareness in connected and autonomous vehicles.