Shichao Wu — accepted AI-conference papers

2024

SemanticTopoLoop: Semantic Loop Closure With 3D Topological Graph Based on Quadric-Level Object Map

Zhenzhong Cao, Qianyi Zhang, Jinzheng Guang, Shichao Wu, Zhengxi Hu, Jingtai Liu

RA-L 2024

Loop closure, as one of the crucial components in SLAM, plays an essential role in correcting accumulated errors. Traditional appearance-based methods, such as bag-of-words models, are often limited by local 2D features and the volume of training data, making them less versatile and robust in real-w

Cited by 0 Source ↗Scholar ↗

2022

GA-STT: Human Trajectory Prediction With Group Aware Spatial-Temporal Transformer

Lei Zhou, Dingye Yang, Xiaolin Zhai, Shichao Wu, Zhengxi Hu, Jingtai Liu

RA-L 2022

Human trajectory prediction is a crucial yet challenging problem, which is of fundamental importance to robotics and autonomous driving vehicles. The core challenge lies in effectively modeling the socially aware spatial interaction and complex temporal dependencies among crowds. However, previous m

Cited by 31 Source ↗Scholar ↗