1 citations · 1 across the 5 of their papers we have counts for
5 papers
Dino-Diffusion Modular Designs Bridge the Cross-Domain Gap in Autonomous Parking
Zixuan Wu, Hengyuan Zhang, Ting-Hsuan Chen +4
Parking is a critical pillar of driving safety. While recent end-to-end (E2E) approaches have achieved promising in-domain results, robustness under domain shifts (e.g., weather an…
SMART: Advancing Scalable Map Priors for Driving Topology Reasoning
Junjie Ye, David Paz, Hengyuan Zhang +5
Topology reasoning is crucial for autonomous driving as it enables comprehensive understanding of connectivity and relationships between lanes and traffic elements. While recent ap…
MapGS: Generalizable Pretraining and Data Augmentation for Online Mapping via Novel View Synthesis
Hengyuan Zhang, David Paz, Yuliang Guo +3
Online mapping reduces the reliance of autonomous vehicles on high-definition (HD) maps, significantly enhancing scalability. However, recent advancements often overlook cross-sens…
Enhancing Online Road Network Perception and Reasoning with Standard Definition Maps
Hengyuan Zhang, David Paz, Yuliang Guo +5
Autonomous driving for urban and highway driving applications often requires High Definition (HD) maps to generate a navigation plan. Nevertheless, various challenges arise when ge…
SemVecNet: Generalizable Vector Map Generation for Arbitrary Sensor Configurations
Narayanan Elavathur Ranganatha, Hengyuan Zhang, Shashank Venkatramani +2
Vector maps are essential in autonomous driving for tasks like localization and planning, yet their creation and maintenance are notably costly. While recent advances in online vec…