Jianfei Ge — accepted AI-conference papers

2026

Toward Degradation-Robust High-Precision Mapping: A Large-Scale LiDAR-Inertial Dataset

Xiaofeng Jin, Ningbo Bu, Jianfei Ge, Shijie Wang, Jiangjian Xiao, Matteo Matteucci

RA-L 2026

LiDAR-Inertial Odometry (LIO) has demonstrated robust real-time capability and efficient mapping performance compared to traditional terrestrial laser scanners. Although recent advances driven by public datasets have improved LIO stability under certain degraded conditions, existing studies still la

Cited by 0 Source ↗code ↗Scholar ↗

2025

Rendering Anywhere You See: Renderability Field-guided Gaussian Splatting

Xiaofeng Jin, Yan Fang, Matteo Frosi, Jianfei Ge, Jiangjian Xiao, Matteo Matteucci

IROS 2025

Scene view synthesis, which generates novel views from limited perspectives, is increasingly vital for applications like virtual reality, augmented reality, and robotics. Unlike object-based tasks, such as generating 360° views of a car, scene view synthesis handles entire environments where non-uni

Cited by 2 Source ↗Scholar ↗