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Article has an altmetric score of 2

Grant support

This work has been supported by project "SARAOS" (PID2020-115132RB) funded by MCIN/AEI/10.13039/501100011033 of the Spanish Government and by project "XRECO" (HORIZON-IA-101070250) funded by the European Union.

Analysis of institutional authors

Usón, JavierCorresponding AuthorCabrera, JulianAuthor

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July 21, 2024
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Proceedings Paper
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Analysis and Development of Deep Learning Depth Estimation Techniques for Volumetric Capture and Free Viewpoint Video

Publicated to: 520-523 - 2024-01-01 (), DOI: 10.1145/3625468.3652913

Authors: Usón, J; Cabrera, J

Affiliations

Univ Politecn Madrid, ETSI Telecomunicac, Informat Proc & Telecommun Ctr, Grp Tratamiento Imagenes, Madrid, Spain - Author

Abstract

Volumetric capture is an important topic in eXtended Reality (XR) as it enables the integration of realistic three-dimensional content into virtual scenarios and immersive applications. Certain systems are even capable of delivering these volumetric captures live and in real-time, opening the door to interactive use cases such as immersive videoconferencing. One example of such systems is FVV Live, a Free Viewpoint Video (FVV) application capable of working in real-time with low delay Current breakthroughs in Artificial Intelligence (AI) in general and deep learning in particular report great success when applied to the computer vision tasks involved in volumetric capture, helping to overcome the quality and bandwidth restrictions that these systems often face. Despite their promising results, state-of-the-art approaches still come with the disadvantage of requiring large processing power and time. This project aims to advance the volumetric capture state-of-the-art applying the previously mentioned deep learning techniques, optimizing the models to work in real-time while still delivering high quality. The technology developed will be validated integrating it into immersive video communication systems such as FVV Live in order to overcome their main restrictions and to improve the quality delivered to the end user.

Keywords

Deep learningDepth estimationEstimation techniquesFree-viewpoint videoImmersiveImmersive applicationLearning systemsLow delayReal time systemsReal- timeVideo applicationsVideo conferencingVirtual scenarioVolumetrics

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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-23:

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 1.5.
  • The number of mentions on the social network X (formerly Twitter): 2 (Altmetric).

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (USON PEIRON, JAVIER) and Last Author (CABRERA QUESADA, JULIAN).

the author responsible for correspondence tasks has been USON PEIRON, JAVIER.