2 citations · 5 across the 8 of their papers we have counts for
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cs.RO2023
Challenges of Indoor SLAM: A multi-modal multi-floor dataset for SLAM evaluation
Pushyami Kaveti, Aniket Gupta, Dennis Giaya +5
Robustness in Simultaneous Localization and Mapping (SLAM) remains one of the key challenges for the real-world deployment of autonomous systems. SLAM research has seen significant…
cs.RO2023★ 1 cited
Bridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving
Xiangyu Bai, Yedi Luo, Le Jiang +4
Modern autonomous systems require extensive testing to ensure reliability and build trust in ground vehicles. However, testing these systems in the real-world is challenging due to…
cs.RO2023★ 1 cited
Temporal-controlled Frame Swap for Generating High-Fidelity Stereo Driving Data for Autonomy Analysis
Yedi Luo, Xiangyu Bai, Le Jiang +4
This paper presents a novel approach, TeFS (Temporal-controlled Frame Swap), to generate synthetic stereo driving data for visual simultaneous localization and mapping (vSLAM) task…