Jianqi Liu — accepted AI-conference papers

2025

BEV-LIO(LC): BEV Image Assisted LiDAR-Inertial Odometry with Loop Closure

Haoxin Cai, Shenghai Yuan, Xinyi Li, Junfeng Guo, Jianqi Liu

IROS 2025

This work introduces BEV-LIO(LC), a novel LiDAR-Inertial Odometry (LIO) framework that combines Bird’s Eye View (BEV) image representations of LiDAR data with geometry-based point cloud registration and incorporates loop closure (LC) through BEV image features. By normalizing point density, we proje

Cited by 11 Source ↗code ↗Scholar ↗

2024

LiteTrack: Layer Pruning with Asynchronous Feature Extraction for Lightweight and Efficient Visual Tracking

Qingmao Wei, Bi Zeng, Jianqi Liu, Li He, Guotian Zeng

ICRA 2024poster

The recent advancements in transformer-based visual trackers have led to significant progress, attributed to their strong modeling capabilities. However, as performance improves, running latency correspondingly increases, presenting a challenge for real-time robotics applications, especially on edge…

Cited by 20 Source ↗code ↗Scholar ↗