Longhua Ma — accepted AI-conference papers

2026

GS-Loc: A Vision Foundation Model-Driven 3D Gaussian Splatting Framework for Robust Visual Relocalization

Yupei Zeng, Yuhang Dong, Xuanhua Chen, Guangyuan Lu, Runjian Li, Jiajun Lv +2

RA-L 2026

Robust and accurate localization technologies are crucial for autonomous vehicles and mobile robots. Precisely perceiving the 3D environment and its semantic attributes in the real world greatly enhances the ability of these systems to perform localization tasks effectively. This paper proposes GS-L

Cited by 0 Source ↗Scholar ↗

2025

ImitDiff: Transferring Foundation-Model Priors for Distraction-Robust Visuomotor Policy

Yuhang Dong, Haizhou Ge, Yupei Zeng, Jiangning Zhang, Beiwen Tian, Hongrui Zhu +6

RA-L 2025

Visuomotor imitation learning policies enable robots to efficiently acquire manipulation skills from visual demonstrations. However, as scene complexity and visual distractions increase, policies that perform well in simple settings often experience substantial performance degradation. To address th

Cited by 1 Source ↗Scholar ↗