1 citations · 1 across the 2 of their papers we have counts for
4 papers · 1 filter
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…
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…
Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition
Yao Liu, Gangfeng Cui, Jiahui Luo +2
As a fundamental aspect of human life, two-person interactions contain meaningful information about people's activities, relationships, and social settings. Human action recognitio…
Uncertainty-Aware Pedestrian Trajectory Prediction via Distributional Diffusion
Yao Liu, Zesheng Ye, Rui Wang +3
Tremendous efforts have been put forth on predicting pedestrian trajectory with generative models to accommodate uncertainty and multi-modality in human behaviors. An individual's…