Regional Weighted Generative Adversarial Network for LDR to HDR Image Conversion

Sung Woon Jung, Dong Min Son, Hyuk Ju Kwon, Sung Hak Lee

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

5 Scopus citations

Abstract

For the image conversion from low dynamic range images to high dynamic range images, we considered the possibility of using the Generative Adversarial Network (GAN) as one of the deep neural network methods. Deep learning requires a lot of data before building a module, but once creation is done, it is convenient to use it. In this paper, we proposed a weighting map for a local luminance based learning to reconstruct locally tone-mapped images.

Original languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages697-700
Number of pages4
ISBN (Electronic)9781728149851
DOIs
StatePublished - Feb 2020
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: 19 Feb 202021 Feb 2020

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Country/TerritoryJapan
CityFukuoka
Period19/02/2021/02/20

Keywords

  • Cycle GAN
  • HDR
  • Image Conversion
  • Weighted loss function

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