no code implementations • 10 Apr 2024 • Diankun Zhang, Guoan Wang, Runwen Zhu, Jianbo Zhao, Xiwu Chen, Siyu Zhang, Jiahao Gong, Qibin Zhou, Wenyuan Zhang, Ningzi Wang, Feiyang Tan, Hangning Zhou, Ziyao Xu, Haotian Yao, Chi Zhang, Xiaojun Liu, Xiaoguang Di, Bin Li
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system.
no code implementations • 20 Aug 2023 • Chen Feng, Hangning Zhou, Huadong Lin, Zhigang Zhang, Ziyao Xu, Chi Zhang, Boyu Zhou, Shaojie Shen
Predicting the future behavior of agents is a fundamental task in autonomous vehicle domains.
1 code implementation • 18 Apr 2023 • Xiyang Wang, Chunyun Fu, JiaWei He, Mingguang Huang, Ting Meng, Siyu Zhang, Hangning Zhou, Ziyao Xu, Chi Zhang
In the classical tracking-by-detection (TBD) paradigm, detection and tracking are separately and sequentially conducted, and data association must be properly performed to achieve satisfactory tracking performance.
1 code implementation • 1 Aug 2022 • Yilan Zhang, Fengying Xie, Xuedong Song, Hangning Zhou, Yiguang Yang, Haopeng Zhang, Jie Liu
As such they have made great improvements in many tasks of dermoscopy images.
no code implementations • 30 Jun 2022 • Yuting Wang, Hangning Zhou, Zhigang Zhang, Chen Feng, Huadong Lin, Chaofei Gao, Yizhi Tang, Zhenting Zhao, Shiyu Zhang, Jie Guo, Xuefeng Wang, Ziyao Xu, Chi Zhang
This technical report presents an effective method for motion prediction in autonomous driving.
Ranked #12 on Motion Forecasting on Argoverse CVPR 2020
1 code implementation • ECCV 2020 • Jiahao Li, Changhao Zhang, Ziyao Xu, Hangning Zhou, Chi Zhang
In this paper, we propose a novel learning-based pipeline for partially overlapping 3D point cloud registration.