From Depth Sensing to Deep Depth Estimation for 3D Reconstruction: Open Challenges

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	English
Title of host publication	Proceedings of the 3rd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE
Publisher	SciTePress
Pages	164-171
ISBN (Electronic)	978-989-758-642-2
Publication status	Published - 2023

Urban Operations Expert Talks 2024
Hamesse, C. (Participant)
25 Jun 2024
Activity: Participating in or organising an event (conference, measurement campaign, ...) › Participating in a conference, workshop, ...

Cite this

@inproceedings{c51d0c07137549f2a38bcd859d74c0f1,

title = "From Depth Sensing to Deep Depth Estimation for 3D Reconstruction: Open Challenges",

author = "Charles Hamesse and Hiep Luong and Robby Haelterman",

year = "2023",

language = "English",

pages = "164--171",

booktitle = "Proceedings of the 3rd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE",

publisher = "SciTePress",

}

From Depth Sensing to Deep Depth Estimation for 3D Reconstruction: Open Challenges. / Hamesse, Charles; Luong, Hiep; Haelterman, Robby.
Proceedings of the 3rd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE. SciTePress, 2023. p. 164-171.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review