5 citations · 5 across the 4 of their papers we have counts for
4 papers
LTDA-Drive: LLMs-guided Generative Models based Long-tail Data Augmentation for Autonomous Driving
Mahmut Yurt, Xin Ye, Yunsheng Ma +5
3D perception plays an essential role for improving the safety and performance of autonomous driving. Yet, existing models trained on real-world datasets, which naturally exhibit l…
ALN-P3: Unified Language Alignment for Perception, Prediction, and Planning in Autonomous Driving
Yunsheng Ma, Burhaneddin Yaman, Xin Ye +5
Recent advances have explored integrating large language models (LLMs) into end-to-end autonomous driving systems to enhance generalization and interpretability. However, most exis…
Modeling Dual-Exposure Quad-Bayer Patterns for Joint Denoising and Deblurring
Yuzhi Zhao, Lai-Man Po, Xin Ye +2
Image degradation caused by noise and blur remains a persistent challenge in imaging systems, stemming from limitations in both hardware and methodology. Single-image solutions fac…
LORD: Large Models based Opposite Reward Design for Autonomous Driving
Xin Ye, Feng Tao, Abhirup Mallik +2
Reinforcement learning (RL) based autonomous driving has emerged as a promising alternative to data-driven imitation learning approaches. However, crafting effective reward functio…