3 papers
cs.CV2026
IAF-Net: Illumination-Adaptive Fusion for Low-Light Urban Road Segmentation
Bingtao Wang, Daojie Peng, Fulong Ma +2
Semantic road segmentation is important for autonomous driving, but existing methods suffer severe performance degradation under low-light conditions. Many existing multi-modal fus…
cs.CV2026
LiteViLNet: Lightweight Vision-LiDAR Fusion Network for Efficient Road Segmentation
Daojie Peng, Bingtao Wang, Fulong Ma +2
Road segmentation is a fundamental perception task for autonomous driving and intelligent robotic systems, requiring both high accuracy and real-time inference, especially for depl…
cs.RO2026
A Vision-Language-Action Model with Visual Prompt for OFF-Road Autonomous Driving
Liangdong Zhang, Yiming Nie, Haoyang Li +6
Efficient trajectory planning in off-road terrains presents a formidable challenge for autonomous vehicles, often necessitating complex multi-step pipelines. However, traditional a…