457 citations · 845 across the 36 of their papers we have counts for
7 papers · 1 filter
Improved Robustness and Safety for Pre-Adaptation of Meta Reinforcement Learning with Prior Regularization
Lu Wen, Songan Zhang, H. Eric Tseng +3
Meta Reinforcement Learning (Meta-RL) has seen substantial advancements recently. In particular, off-policy methods were developed to improve the data efficiency of Meta-RL techniq…
Real-time Semantic 3D Dense Occupancy Mapping with Efficient Free Space Representations
Yuanxin Zhong, Huei Peng
A real-time semantic 3D occupancy mapping framework is proposed in this paper. The mapping framework is based on the Bayesian kernel inference strategy from the literature. Two nov…
Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations
Minghan Zhu, Maani Ghaffari, Huei Peng
This paper proposes a correspondence-free method for point cloud rotational registration. We learn an embedding for each point cloud in a feature space that preserves the SO(3)-equ…
VIN: Voxel-based Implicit Network for Joint 3D Object Detection and Segmentation for Lidars
Yuanxin Zhong, Minghan Zhu, Huei Peng
A unified neural network structure is presented for joint 3D object detection and point cloud segmentation in this paper. We leverage rich supervision from both detection and segme…
Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning
Songan Zhang, Lu Wen, Huei Peng +1
It is essential for an automated vehicle in the field to perform discretionary lane changes with appropriate roadmanship - driving safely and efficiently without annoying or endang…
Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
Minghan Zhu, Songan Zhang, Yuanxin Zhong +3
This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera. Most previous monocular 3D vehicle detection algorithms focu…
An Interaction-aware Evaluation Method for Highly Automated Vehicles
Xinpeng Wang, Songan Zhang, Kuan-Hui Lee +1
It is important to build a rigorous verification and validation (V&V) process to evaluate the safety of highly automated vehicles (HAVs) before their wide deployment on public road…