BACK TO INDEX
Publications about 'Depth estimation'
|
Articles in journal or book chapters
|
-
Michaël Fonder,
Damien Ernst,
and Marc Van Droogenbroeck.
Parallax Inference for Robust Temporal Monocular Depth Estimation in Unstructured Environments.
Sensors,
22(23):1-22,
December 2022.
Keyword(s): Depth,
Depth estimation,
Deep learning,
Drone,
UAV,
Parallax.
[bibtex-entry]
-
Michaël Fonder and Marc Ernst, DamienVan Droogenbroeck.
M4Depth: Monocular depth estimation for autonomous vehicles in unseen environments.
ArXiv,
abs/2105.09847,
May 2021.
Keyword(s): Depth estimation,
Drone,
UAV,
Artificial Intelligence,
Deep learning.
[bibtex-entry]
-
Arnaud Leduc,
Anthony Cioppa,
Silvio Giancola,
Bernard Ghanem,
and Marc Van Droogenbroeck.
SoccerNet-Depth: a Scalable Dataset for Monocular Depth Estimation in Sports Videos.
In IEEE International Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), CVsports,
Seattle, Washington, USA,
June 2024.
Keyword(s): Soccer,
SoccerNet,
Football,
Depth estimation,
Volley-ball,
Synthetic data,
Dataset.
[bibtex-entry]
-
Michaël Fonder and Marc Van Droogenbroeck.
A technique to jointly estimate depth and depth uncertainty for unmanned aerial vehicles.
In IEEE International Conference on Systems, Signals and Image Processing (IWSSIP),
Ohrid, North Macedonia,
pages 1-5,
June 2023.
Keyword(s): Depth,
Depth estimation,
Depth uncertainty,
Deep learning,
Drone,
UAV,
Parallax.
[bibtex-entry]
BACK TO INDEX
Disclaimer:
This material is presented to ensure timely dissemination of
scholarly and technical work. Copyright and all rights therein
are retained by authors or by other copyright holders.
All person copying this information are expected to adhere to
the terms and constraints invoked by each author's copyright.
In most cases, these works may not be reposted
without the explicit permission of the copyright holder.
Last modified: Wed Sep 4 11:50:53 2024