5 papers
FoSS: Modeling Long Range Dependencies and Multimodal Uncertainty in Trajectory Prediction via Fourier State Space Integration
Yizhou Huang, Gengze Jiang, Yihua Cheng +1
Accurate trajectory prediction is vital for safe autonomous driving, yet existing approaches struggle to balance modeling power and computational efficiency. Attention-based archit…
Excavate the potential of Single-Scale Features: A Decomposition Network for Water-Related Optical Image Enhancement
Zheng Cheng, Wenri Wang, Guangyong Chen +5
Underwater image enhancement (UIE) techniques aim to improve visual quality of images captured in aquatic environments by addressing degradation issues caused by light absorption a…
Learning Velocity and Acceleration: Self-Supervised Motion Consistency for Pedestrian Trajectory Prediction
Yizhou Huang, Yihua Cheng, Kezhi Wang
Understanding human motion is crucial for accurate pedestrian trajectory prediction. Conventional methods typically rely on supervised learning, where ground-truth labels are direc…
Trajectory Mamba: Efficient Attention-Mamba Forecasting Model Based on Selective SSM
Yizhou Huang, Yihua Cheng, Kezhi Wang
Motion prediction is crucial for autonomous driving, as it enables accurate forecasting of future vehicle trajectories based on historical inputs. This paper introduces Trajectory…
Efficient Driving Behavior Narration and Reasoning on Edge Device Using Large Language Models
Yizhou Huang, Yihua Cheng, Kezhi Wang
Deep learning architectures with powerful reasoning capabilities have driven significant advancements in autonomous driving technology. Large language models (LLMs) applied in this…