AI-based Stereoview to Multiview Generation by Using Deformable Convolution

Wei Lun Hong, Jar Ferr Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Three dimension (3D) movies are the main trend in the film industry. In the current stereoview, the audiences require wearing 3D glasses to perceive 3D visualization. The 3D movies with stereoview with only left and right views, which cannot be directly displayed in the naked-eyes 3D displays. To directly support naked-eyes 3D displays, which require multiple views, we propose a deep learning based stereo to multiview conversion system by using the deformable convolution to synthesize additional virtual views. For immersive 3D multimedia services, we hope we can improve the quality of user 3D experiences without wearing 3D glasses without the needs of depth estimation and depth image based rendering functions.

Original languageEnglish
Title of host publicationISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems
Subtitle of host publication5G Dream to Reality, Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665419512
DOIs
Publication statusPublished - 2021
Event2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021 - Hualien, Taiwan
Duration: 2021 Nov 162021 Nov 19

Publication series

NameISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding

Conference

Conference2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021
Country/TerritoryTaiwan
CityHualien
Period21-11-1621-11-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Safety, Risk, Reliability and Quality

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