Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation

Mohamad Mofeed Chaar, Jamal Raiyn, Galia Weidl

2025

Abstract

Depth imaging is a crucial area in Autonomous Driving Systems (ADS), as it plays a key role in detecting and measuring objects in the vehicle’s surroundings. However, a significant challenge in this domain arises from missing information in Depth images, where certain points are not measurable due to gaps or inconsistencies in pixel data. Our research addresses two key tasks to overcome this challenge. First, we developed an algorithm using a multi-layered training approach to generate Depth images from a single RGB image. Second, we addressed the issue of missing information in Depth images by applying our algorithm to rectify these gaps, resulting in Depth images with complete and accurate data. We further tested our algorithm on the Cityscapes dataset and successfully resolved the missing information in its Depth images, demonstrating the effectiveness of our approach in real-world urban environments.

Paper Citation

in Harvard Style

Chaar M., Raiyn J. and Weidl G. (2025). Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation. In Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS; ISBN 978-989-758-745-0, SciTePress, pages 549-556. DOI: 10.5220/0013365900003941

in Bibtex Style

@conference{vehits25,
author={Mohamad Mofeed Chaar and Jamal Raiyn and Galia Weidl},
title={Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation},
booktitle={Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS},
year={2025},
pages={549-556},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013365900003941},
isbn={978-989-758-745-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS
TI - Predicting Depth Maps from Single RGB Images and Addressing Missing Information in Depth Estimation
SN - 978-989-758-745-0
AU - Chaar M.
AU - Raiyn J.
AU - Weidl G.
PY - 2025
SP - 549
EP - 556
DO - 10.5220/0013365900003941
PB - SciTePress