Search Results for author: David Paz

Found 6 papers, 1 papers with code

OSM vs HD Maps: Map Representations for Trajectory Prediction

no code implementations4 Nov 2023 Jing-Yan Liao, Parth Doshi, Zihan Zhang, David Paz, Henrik Christensen

While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environmental changes impede the widespread deployment of autonomous driving, especially in the motion forecasting task.

Motion Forecasting Trajectory Prediction

Occlusion-Aware 2D and 3D Centerline Detection for Urban Driving via Automatic Label Generation

no code implementations3 Nov 2023 David Paz, Narayanan E. Ranganatha, Srinidhi K. Srinivas, Yunchao Yao, Henrik I. Christensen

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.

Occlusion Handling

CLiNet: Joint Detection of Road Network Centerlines in 2D and 3D

no code implementations4 Feb 2023 David Paz, Srinidhi Kalgundi Srinivas, Yunchao Yao, Henrik I. Christensen

This work introduces a new approach for joint detection of centerlines based on image data by localizing the features jointly in 2D and 3D.

3D Depth Estimation

Robust Human Identity Anonymization using Pose Estimation

1 code implementation10 Jan 2023 Hengyuan Zhang, Jing-Yan Liao, David Paz, Henrik I. Christensen

Many outdoor autonomous mobile platforms require more human identity anonymized data to power their data-driven algorithms.

Face Detection Pose Estimation

Probabilistic Semantic Mapping for Urban Autonomous Driving Applications

no code implementations8 Jun 2020 David Paz, Hengyuan Zhang, Qinru Li, Hao Xiang, Henrik Christensen

Recent advancements in statistical learning and computational abilities have enabled autonomous vehicle technology to develop at a much faster rate.

Autonomous Driving Self-Driving Cars +1

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