no code implementations • 7 Jul 2021 • Yuanxin Zhong, Minghan Zhu, Huei Peng
A unified neural network structure is presented for joint 3D object detection and point cloud segmentation in this paper.
1 code implementation • 29 Mar 2021 • Minghan Zhu, Songan Zhang, Yuanxin Zhong, Pingping Lu, Huei Peng, John Lenneman
This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera.
1 code implementation • 22 Nov 2020 • Yuanxin Zhong
With the growth of machine learning algorithms with geometry primitives, a high-efficiency library with differentiable geometric operators are desired.
1 code implementation • 4 Nov 2020 • Yuanxin Zhong, Minghan Zhu, Huei Peng
Object detection and tracking is a key task in autonomy.
2 code implementations • 21 Mar 2020 • Minghan Zhu, Maani Ghaffari, Yuanxin Zhong, Pingping Lu, Zhong Cao, Ryan M. Eustice, Huei Peng
In contrast to the current point-to-point loss evaluation approach, the proposed 3D loss treats point clouds as continuous objects; therefore, it compensates for the lack of dense ground truth depth due to LIDAR's sparsity measurements.
no code implementations • 12 Dec 2019 • Yiqun Dong, Yuanxin Zhong, Wenbo Yu, Minghan Zhu, Pingping Lu, Yeyang Fang, Jiajun Hong, Huei Peng
The main goal of this paper is to introduce the data collection effort at Mcity targeting automated vehicle development.