7 papers
Regularized Multi-LLMs Collaboration for Enhanced Score-based Causal Discovery
Xiaoxuan Li, Yao Liu, Ruoyu Wang +1
As the significance of understanding the cause-and-effect relationships among variables increases in the development of modern systems and algorithms, learning causality from obser…
Causality-Aware Transformer Networks for Robotic Navigation
Ruoyu Wang, Yao Liu, Yuanjiang Cao +1
Current research in Visual Navigation reveals opportunities for improvement. First, the direct adoption of RNNs and Transformers often overlooks the specific differences between Em…
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…
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…
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…
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…