1.9k citations · 2.1k across the 16 of their papers we have counts for
19 papers
An Uncertainty-Weighted Decision Transformer for Navigation in Dense, Complex Driving Scenarios
Zhihao Zhang, Chengyang Peng, Minghao Zhu +2
Autonomous driving in dense, dynamic environments requires decision-making systems that can exploit both spatial structure and long-horizon temporal dependencies while remaining ro…
Bootstrapping Reinforcement Learning with Sub-optimal Policies for Autonomous Driving
Zhihao Zhang, Chengyang Peng, Ekim Yurtsever +1
Automated vehicle control using reinforcement learning (RL) has attracted significant attention due to its potential to learn driving policies through environment interaction. Howe…
Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learning
Zhihao Zhang, Ekim Yurtsever, Keith A. Redmill
Developing an automated driving system capable of navigating complex traffic environments remains a formidable challenge. Unlike rule-based or supervised learning-based methods, De…
GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs
Mingyu Liu, Ekim Yurtsever, Marc Brede +6
Accurate and effective 3D object detection is critical for ensuring the driving safety of autonomous vehicles. Recently, state-of-the-art two-stage 3D object detectors have exhibit…
A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook
Mingyu Liu, Ekim Yurtsever, Jonathan Fossaert +5
Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for…
3D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmark
Bare Luka Žagar, Tim Hertel, Mingyu Liu +2
Deformable linear objects are vastly represented in our everyday lives. It is often challenging even for humans to visually understand them, as the same object can be entangled so…