1 citations · 1 across the 12 of their papers we have counts for
4 papers · 1 filter
MTA: Multimodal Task Alignment for BEV Perception and Captioning
Yunsheng Ma, Burhaneddin Yaman, Xin Ye +5
Bird's eye view (BEV)-based 3D perception plays a crucial role in autonomous driving applications. The rise of large language models has spurred interest in BEV-based captioning to…
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…
CLIP-BEVFormer: Enhancing Multi-View Image-Based BEV Detector with Ground Truth Flow
Chenbin Pan, Burhaneddin Yaman, Senem Velipasalar +1
Autonomous driving stands as a pivotal domain in computer vision, shaping the future of transportation. Within this paradigm, the backbone of the system plays a crucial role in int…
VLP: Vision Language Planning for Autonomous Driving
Chenbin Pan, Burhaneddin Yaman, Tommaso Nesti +4
Autonomous driving is a complex and challenging task that aims at safe motion planning through scene understanding and reasoning. While vision-only autonomous driving methods have…