3 papers
cs.RO2025
Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator
Wei-Bin Kou, Guangxu Zhu, Rongguang Ye +3
Learning-based street scene semantic understanding in autonomous driving (AD) has advanced significantly recently, but the performance of the AD model is heavily dependent on the q…
cs.LG2024
Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving
Wei-Bin Kou, Qingfeng Lin, Ming Tang +4
Street Scene Semantic Understanding (denoted as TriSU) is a complex task for autonomous driving (AD). However, inference model trained from data in a particular geographical region…
eess.SP2024
Revisiting Trace Norm Minimization for Tensor Tucker Completion: A Direct Multilinear Rank Learning Approach
Xueke Tong, Hancheng Zhu, Lei Cheng +1
To efficiently express tensor data using the Tucker format, a critical task is to minimize the multilinear rank such that the model would not be over-flexible and lead to overfitti…