activity
20192022
most citedMcity Data Collection for Automated Vehicles Study

13 citations · 16 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2022

Temporal and Spatial Online Integrated Calibration for Camera and LiDAR

Shouan Wang, Xinyu Zhang, GuiPeng Zhang +4

While camera and LiDAR are widely used in most of the assisted and autonomous driving systems, only a few works have been proposed to associate the temporal synchronization and ext…

cs.CV2021

Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography

Minghan Zhu, Songan Zhang, Yuanxin Zhong +3

This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera. Most previous monocular 3D vehicle detection algorithms focu…

cs.CV2020★ 2 cited

SUPER: A Novel Lane Detection System

Pingping Lu, Chen Cui, Shaobing Xu +2

AI-based lane detection algorithms were actively studied over the last few years. Many have demonstrated superior performance compared with traditional feature-based methods. The a…

cs.CV2020★ 1 cited

Monocular Depth Prediction through Continuous 3D Loss

Minghan Zhu, Maani Ghaffari, Yuanxin Zhong +4

This paper reports a new continuous 3D loss function for learning depth from monocular images. The dense depth prediction from a monocular image is supervised using sparse LIDAR po…

cs.CV2019★ 13 cited

Mcity Data Collection for Automated Vehicles Study

Yiqun Dong, Yuanxin Zhong, Wenbo Yu +5

The main goal of this paper is to introduce the data collection effort at Mcity targeting automated vehicle development. We captured a comprehensive set of data from a set of perce…