Single-image reflection removal using conditional GANs

Miran Heo, Yoonsik Choe

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

1 Citation (Scopus)

Abstract

Removing undesired reflections from a single-image is inherently ill-posed problem since defining its exact physical model is almost impossible. Most previous works tackle this problem through the use of multiple images or hand-crafted features. These methods are still quite limited in terms of the generality and photo-realistic result. In this paper, we propose a conditional Generative Adversarial Networks based deep neural network structure to render realistic image and formulate our problem in a simple objective function. Specifically, we use gradient information to elaborate this formulation to preserve both low and high frequency details. Our proposed network does not rely on any physical prior information and performs effectively with a single-image. Experimental results demonstrate that proposed algorithm conducts favorably against existing algorithms from human perceptual aspect.

Original languageEnglish
Title of host publicationICEIC 2019 - International Conference on Electronics, Information, and Communication
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9788995004449
DOIs
Publication statusPublished - 2019 May 3
Event18th International Conference on Electronics, Information, and Communication, ICEIC 2019 - Auckland, New Zealand
Duration: 2019 Jan 222019 Jan 25

Publication series

NameICEIC 2019 - International Conference on Electronics, Information, and Communication

Conference

Conference18th International Conference on Electronics, Information, and Communication, ICEIC 2019
Country/TerritoryNew Zealand
CityAuckland
Period19/1/2219/1/25

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the Technology Innovation Program funded by the Ministry of Trade, Industry and Energy (MOTIE, Korea) (No. 10073229).

Publisher Copyright:
© 2019 Institute of Electronics and Information Engineers (IEIE).

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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