no code implementations • 4 Nov 2023 • Jing-Yan Liao, Parth Doshi, Zihan Zhang, David Paz, Henrik Christensen
While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environmental changes impede the widespread deployment of autonomous driving, especially in the motion forecasting task.
no code implementations • 3 Nov 2023 • David Paz, Narayanan E. Ranganatha, Srinidhi K. Srinivas, Yunchao Yao, Henrik I. Christensen
This research work seeks to explore and identify strategies that can determine road topology information in 2D and 3D under highly dynamic urban driving scenarios.
no code implementations • 4 Feb 2023 • David Paz, Srinidhi Kalgundi Srinivas, Yunchao Yao, Henrik I. Christensen
This work introduces a new approach for joint detection of centerlines based on image data by localizing the features jointly in 2D and 3D.
1 code implementation • 10 Jan 2023 • Hengyuan Zhang, Jing-Yan Liao, David Paz, Henrik I. Christensen
Many outdoor autonomous mobile platforms require more human identity anonymized data to power their data-driven algorithms.
no code implementations • 14 Oct 2020 • Yunhai Han, YuHan Liu, David Paz, Henrik Christensen
Calibration of sensors is fundamental to robust performance for intelligent vehicles.
no code implementations • 8 Jun 2020 • David Paz, Hengyuan Zhang, Qinru Li, Hao Xiang, Henrik Christensen
Recent advancements in statistical learning and computational abilities have enabled autonomous vehicle technology to develop at a much faster rate.