Zhanlin Liu — accepted AI-conference papers

2025

BEV-PolyNet: BEV-Based Polygonal End to End Parking Slot Detection Framework

Zhenjie Duan, Yaoming Zhuang, Yifan Chao, Pengcheng Zhu, Li Li, Chengdong Wu +1

RA-L 2025

Accurate parking slot detection is crucial for autonomous parking and intelligent driving, directly impacting safety and efficiency. However, most existing methods rely on AVM images, making them susceptible to image distortion and vehicle occlusion. Additionally, many approaches independently regre

Cited by 0 Source ↗Scholar ↗

2024

MGS-SLAM: Monocular Sparse Tracking and Gaussian Mapping With Depth Smooth Regularization

Pengcheng Zhu, Yaoming Zhuang, Baoquan Chen, Li Li, Chengdong Wu, Zhanlin Liu

RA-L 2024

This letter introduces a novel framework for dense Visual Simultaneous Localization and Mapping (VSLAM) based on Gaussian Splatting. Recently, SLAM based on Gaussian Splatting has shown promising results. However, in monocular scenarios, the Gaussian maps reconstructed lack geometric accuracy and ex

Cited by 22 Source ↗Scholar ↗