1 citations · 2 across the 13 of their papers we have counts for
10 papers · 1 filter
Refine Connections, Close the Gap: A Reliable Enhancement Framework for Driving Scene Topology
Xiaoqi Wang, Dingyi Zhaung, Dingyi Zhuang +7
In autonomous driving, understanding scene topology - the connectivity between lanes and traffic elements - is critical for safe path planning and motion control. While current met…
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…
OSM vs HD Maps: Map Representations for Trajectory Prediction
Jing-Yan Liao, Parth Doshi, Zihan Zhang +2
While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environment…
Occlusion-Aware 2D and 3D Centerline Detection for Urban Driving via Automatic Label Generation
David Paz, Narayanan E. Ranganatha, Srinidhi K. Srinivas +2
This research work seeks to explore and identify strategies that can determine road topology information in 2D and 3D under highly dynamic urban driving scenarios. To facilitate th…
CLiNet: Joint Detection of Road Network Centerlines in 2D and 3D
David Paz, Srinidhi Kalgundi Srinivas, Yunchao Yao +1
This work introduces a new approach for joint detection of centerlines based on image data by localizing the features jointly in 2D and 3D. In contrast to existing work that focuse…
Robust Human Identity Anonymization using Pose Estimation
Hengyuan Zhang, Jing-Yan Liao, David Paz +1
Many outdoor autonomous mobile platforms require more human identity anonymized data to power their data-driven algorithms. The human identity anonymization should be robust so tha…
Auto-calibration Method Using Stop Signs for Urban Autonomous Driving Applications
Yunhai Han, Yuhan Liu, David Paz +1
Calibration of sensors is fundamental to robust performance for intelligent vehicles. In natural environments, disturbances can easily challenge calibration. One possibility is to…
Probabilistic Semantic Mapping for Urban Autonomous Driving Applications
David Paz, Hengyuan Zhang, Qinru Li +2
Recent advancements in statistical learning and computational abilities have enabled autonomous vehicle technology to develop at a much faster rate. While many of the architectures…