2 citations · 3 across the 4 of their papers we have counts for
4 papers
Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
Juanwu Lu, Can Cui, Yunsheng Ma +2
Safety and robustness are crucial factors in developing trustworthy autonomous vehicles. One essential aspect of addressing these factors is to equip vehicles with the capability t…
Towards Generalizable and Interpretable Motion Prediction: A Deep Variational Bayes Approach
Juanwu Lu, Wei Zhan, Masayoshi Tomizuka +1
Estimating the potential behavior of the surrounding human-driven vehicles is crucial for the safety of autonomous vehicles in a mixed traffic flow. Recent state-of-the-art achieve…
MACP: Efficient Model Adaptation for Cooperative Perception
Yunsheng Ma, Juanwu Lu, Can Cui +4
Vehicle-to-vehicle (V2V) communications have greatly enhanced the perception capabilities of connected and automated vehicles (CAVs) by enabling information sharing to "see through…
Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion
Can Cui, Yunsheng Ma, Juanwu Lu +1
Sensor fusion is a crucial augmentation technique for improving the accuracy and reliability of perception systems for automated vehicles under diverse driving conditions. However,…