GANs with Multiple Constraints for Image Translation

Bibliographic Details
Title: GANs with Multiple Constraints for Image Translation
Authors: Yan Gan, Junxin Gong, Mao Ye, Yang Qian, Kedi Liu, Su Zhang
Source: Complexity, Vol 2018 (2018)
Publisher Information: Hindawi-Wiley, 2018.
Publication Year: 2018
Collection: LCC:Electronic computers. Computer science
Subject Terms: Electronic computers. Computer science, QA75.5-76.95
More Details: Unpaired image translation is a challenging problem in computer vision, while existing generative adversarial networks (GANs) models mainly use the adversarial loss and other constraints to model. But the degree of constraint imposed on the generator and the discriminator is not enough, which results in bad image quality. In addition, we find that the current GANs-based models have not yet been implemented by adding an auxiliary domain, which is used to constrain the generator. To solve the problem mentioned above, we propose a multiscale and multilevel GANs (MMGANs) model for image translation. In this model, we add an auxiliary domain to constrain generator, which combines this auxiliary domain with the original domains for modelling and helps generator learn the detailed content of the image. Then we use multiscale and multilevel feature matching to constrain the discriminator. The purpose is to make the training process as stable as possible. Finally, we conduct experiments on six image translation tasks. The results verify the validity of the proposed model.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1076-2787
1099-0526
Relation: https://doaj.org/toc/1076-2787; https://doaj.org/toc/1099-0526
DOI: 10.1155/2018/4613935
Access URL: https://doaj.org/article/678e034d1acb4ac3ad938283626876ab
Accession Number: edsdoj.678e034d1acb4ac3ad938283626876ab
Database: Directory of Open Access Journals
More Details
ISSN:10762787
10990526
DOI:10.1155/2018/4613935
Published in:Complexity
Language:English