Stereoscopic image super-resolution with stereo consistent feature

Wonil Song, Sungil Choi, Somi Jeong, Kwanghoon Sohn

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

11 Citations (Scopus)

Abstract

We present a first attempt for stereoscopic image superresolution (SR) for recovering high-resolution details while preserving stereo-consistency between stereoscopic image pair. The most challenging issue in the stereoscopic SR is that the texture details should be consistent for corresponding pixels in stereoscopic SR image pair. However, existing stereo SR methods cannot maintain the stereo-consistency, thus causing 3D fatigue to the viewers. To address this issue, in this paper, we propose a self and parallax attention mechanism (SPAM) to aggregate the information from its own image and the counterpart stereo image simultaneously, thus reconstructing high-quality stereoscopic SR image pairs. Moreover, we design an efficient network architecture and effective loss functions to enforce stereo-consistency constraint. Finally, experimental results demonstrate the superiority of our method over state-of-the-art SR methods in terms of both quantitative metrics and qualitative visual quality while maintaining stereo-consistency between stereoscopic image pair.

Original languageEnglish
Title of host publicationAAAI 2020 - 34th AAAI Conference on Artificial Intelligence
PublisherAAAI press
Pages12031-12038
Number of pages8
ISBN (Electronic)9781577358350
Publication statusPublished - 2020
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 2020 Feb 72020 Feb 12

Publication series

NameAAAI 2020 - 34th AAAI Conference on Artificial Intelligence

Conference

Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York
Period20/2/720/2/12

Bibliographical note

Funding Information:
This research was supported by R&D program for Advanced Integrated-intelligence for Identification (AIID) through the National Research Foundation of KOREA(NRF) funded by Ministry of Science and ICT (NRF-2018M3E3A1057289).

Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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