Rastin Pries — accepted AI-conference papers

2026

HPGS-SLAM: Hybrid Point-Guided Dense Visual SLAM With Online Mapping via Gaussian Splatting

Xin Su, Xiaoang Zhang, Rastin Pries, Eckehard G. Steinbach

RA-L 2026

In this letter, we introduce HPGS-SLAM, a real-time RGB-D SLAM system guided by hybrid point features (combining traditional and learned point features), enabling high-precision tracking and online dense mapping with photorealistic reconstruction. HPGS-SLAM consists of two main components: (1) a lig

Cited by 1 Source ↗Scholar ↗

2024

HPF-SLAM: An Efficient Visual SLAM System Leveraging Hybrid Point Features

Xin Su, Sebastian Eger, Adam Misik, Dong Yang, Rastin Pries, Eckehard Steinbach

ICRA 2024poster

Visual SLAM is an essential tool in diverse applications such as robot perception and extended reality, where feature-based methods are prevalent due to their accuracy and robustness. However, existing methods employ either hand-crafted or solely learnable point features and are thus limited by the…

Cited by 1 Source ↗Scholar ↗