most citedBridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving

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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

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…