45 citations · 54 across the 5 of their papers we have counts for
8 papers · 1 filter
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving
Chen Min, Dawei Zhao, Liang Xiao +10
Vision-centric autonomous driving has recently raised wide attention due to its lower cost. Pre-training is essential for extracting a universal representation. However, current vi…
Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
Zheng Zhu, Xiaofeng Wang, Wangbo Zhao +15
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual en…
UniWorld: Autonomous Driving Pre-training via World Models
Chen Min, Dawei Zhao, Liang Xiao +2
In this paper, we draw inspiration from Alberto Elfes' pioneering work in 1989, where he introduced the concept of the occupancy grid as World Models for robots. We imbue the robot…
UniScene: Multi-Camera Unified Pre-training via 3D Scene Reconstruction for Autonomous Driving
Chen Min, Liang Xiao, Dawei Zhao +2
Multi-camera 3D perception has emerged as a prominent research field in autonomous driving, offering a viable and cost-effective alternative to LiDAR-based solutions. The existing…
Adversarial and Random Transformations for Robust Domain Adaptation and Generalization
Liang Xiao, Jiaolong Xu, Dawei Zhao +3
Data augmentation has been widely used to improve generalization in training deep neural networks. Recent works show that using worst-case transformations or adversarial augmentati…
Trajectory Prediction for Autonomous Driving with Topometric Map
Jiaolong Xu, Liang Xiao, Dawei Zhao +2
State-of-the-art autonomous driving systems rely on high definition (HD) maps for localization and navigation. However, building and maintaining HD maps is time-consuming and expen…