most citedFedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.RO2025

Adverse Weather-Independent Framework Towards Autonomous Driving Perception through Temporal Correlation and Unfolded Regularization

Wei-Bin Kou, Guangxu Zhu, Rongguang Ye +5

Various adverse weather conditions such as fog and rain pose a significant challenge to autonomous driving (AD) perception tasks like semantic segmentation, object detection, etc.…

cs.RO2025

iMacHSR: Intermediate Multi-Access Heterogeneous Supervision and Regularization Scheme Toward Architecture-Agnostic Training

Wei-Bin Kou, Guangxu Zhu, Yichen Jin +4

While deep supervision is a powerful training strategy by supervising intermediate layers with auxiliary losses, it faces three underexplored problems: (I) Existing deep supervisio…

cs.RO20251 cited

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving

Wei-Bin Kou, Guangxu Zhu, Bingyang Cheng +3

Street Scene Semantic Understanding (denoted as S3U) is a crucial but complex task for autonomous driving (AD) vehicles. Their inference models typically face poor generalization d…

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.CV2025

Enhancing Large Vision Model in Street Scene Semantic Understanding through Leveraging Posterior Optimization Trajectory

Wei-Bin Kou, Qingfeng Lin, Ming Tang +5

To improve the generalization of the autonomous driving (AD) perception model, vehicles need to update the model over time based on the continuously collected data. As time progres…

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…