A Review of Deep Learning Solutions in 360° Video Streaming

Moatasim Mahmoud, Stamatia Rizou, Andreas S. Panayides, Pavlos I. Lazaridis, Nikolaos V. Kantartzis, George K. Karagiannidis, Zaharias D. Zaharis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


The spread of virtual reality and 360° video applications has raised research interest in developing new streaming techniques. On one hand, 360° videos rely on strict network requirements compared to conventional 2D videos. Realizing an adequate user experience is subject to ultra-low latency and huge bitrate requirements. On the other hand, 360° videos have distinct characteristics that allow for innovative streaming solutions. These solutions have benefited from the advancements in deep learning for optimizing the transmission under restricted network resources. In this paper, we review existing works employing deep learning in 360° video transmission and we highlight the challenges associated with 360° video streaming.

Original languageEnglish
Title of host publication2023 12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9798350321074
ISBN (Print)9798350321081
Publication statusPublished - 17 Jul 2023
Event12th International Conference on Modern Circuits and Systems Technologies - Athens, Greece
Duration: 28 Jun 202330 Jun 2023
Conference number: 12


Conference12th International Conference on Modern Circuits and Systems Technologies
Abbreviated titleMOCAST 2023

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