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Weakly Supervised GAN for Image-to-Image Translation in the Wild
Joint Authors
Niu, Shaozhang
Cao, Zhiyi
Zhang, Jiwei
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-09
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Generative Adversarial Networks (GANs) have achieved significant success in unsupervised image-to-image translation between given categories (e.g., zebras to horses).
Previous GANs models assume that the shared latent space between different categories will be captured from the given categories.
Unfortunately, besides the well-designed datasets from given categories, many examples come from different wild categories (e.g., cats to dogs) holding special shapes and sizes (short for adversarial examples), so the shared latent space is troublesome to capture, and it will cause the collapse of these models.
For this problem, we assume the shared latent space can be classified as global and local and design a weakly supervised Similar GANs (Sim-GAN) to capture the local shared latent space rather than the global shared latent space.
For the well-designed datasets, the local shared latent space is close to the global shared latent space.
For the wild datasets, we will get the local shared latent space to stop the model from collapse.
Experiments on four public datasets show that our model significantly outperforms state-of-the-art baseline methods.
American Psychological Association (APA)
Cao, Zhiyi& Niu, Shaozhang& Zhang, Jiwei. 2020. Weakly Supervised GAN for Image-to-Image Translation in the Wild. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1196610
Modern Language Association (MLA)
Cao, Zhiyi…[et al.]. Weakly Supervised GAN for Image-to-Image Translation in the Wild. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1196610
American Medical Association (AMA)
Cao, Zhiyi& Niu, Shaozhang& Zhang, Jiwei. Weakly Supervised GAN for Image-to-Image Translation in the Wild. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1196610
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196610