Dogan Kircali — accepted AI-conference papers

2025

Tele-GS: 3D Gaussian Scene Representation for Low-Bandwidth Teleoperation

Chunyang Zhao, Zeyu Zhou, Haoran Liu, Dogan Kircali, Huan Yang, Chang Boon Low +2

IROS 2025

Video streaming based teleoperation often faces a trade-off between bandwidth consumption and the need for high-fidelity telepresence. Higher image resolution or a wider field of view (FOV) substantially increases bandwidth requirements. In this paper, we propose a novel telepresence model for teleo

Cited by 0 Source ↗Scholar ↗

2024

Towards Kbps-level Vehicle Teleoperation via Persistent-Transient Environment Modelling

Chunyang Zhao, Zeyu Zhou, Haoran Liu, Dogan Kircali, Guoyi Chi, Hongming Shen +2

IROS 2024

Traditional teleoperation technologies based on video streaming are facing several challenges in practical applications, including limited bandwidth, constrained spatial awareness, and sensitivity to illumination. Existing studies have not adequately addressed these issues. This paper presents a nov

Cited by 1 Source ↗Scholar ↗