3 papers
cs.CV2024
Modeling Pedestrian Intrinsic Uncertainty for Multimodal Stochastic Trajectory Prediction via Energy Plan Denoising
Yao Liu, Quan Z. Sheng, Lina Yao
Pedestrian trajectory prediction plays a pivotal role in the realms of autonomous driving and smart cities. Despite extensive prior research employing sequence and generative model…
cs.RO2024
Multi-agent Traffic Prediction via Denoised Endpoint Distribution
Yao Liu, Ruoyu Wang, Yuanjiang Cao +2
The exploration of high-speed movement by robots or road traffic agents is crucial for autonomous driving and navigation. Trajectory prediction at high speeds requires considering…
cs.CV2024
Attention-aware Social Graph Transformer Networks for Stochastic Trajectory Prediction
Yao Liu, Binghao Li, Xianzhi Wang +2
Trajectory prediction is fundamental to various intelligent technologies, such as autonomous driving and robotics. The motion prediction of pedestrians and vehicles helps emergency…