Hailong Qin — accepted AI-conference papers

2025

MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving

Xiyang Wang, Shouzheng Qi, Jieyou Zhao, Hangning Zhou, Siyu Zhang, Guoan Wang +6

IROS 2025

This paper introduces MCTrack, a new 3D multi-object tracking method that achieves performance across KITTI, nuScenes, and Waymo datasets. Addressing the gap in existing tracking paradigms, which often perform well on specific datasets but lack generalizability, MCTrack offers a unified solution. Ad

Cited by 27 Source ↗code ↗Scholar ↗

2017

A Two-Stage Optimized Next-View Planning Framework for 3-D Unknown Environment Exploration, and Structural Reconstruction

Zehui Meng, Hailong Qin, Ziyue Chen, Xudong Chen, Hao Sun, Feng Lin +1

RA-L 2017

In this paper, we present a solution for autonomous exploration and reconstruction in 3-D unknown environments without a priori knowledge of the environments. In our framework, a two-stage heuristic information gain-based next-view planning algorithm is performed to dynamically select and update can

Cited by 120 Source ↗Scholar ↗