2017 LearningtoDiscoverCrossDomainRe

• (Kim et al., 2017) ⇒ Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jung Kwon Lee, and Jiwon Kim. (2017). “Learning to Discover Cross-Domain Relations with Generative Adversarial Networks.” In: Proceedings of the 34th International Conference on Machine Learning.

Subject Headings: Generative Adversarial Network Algorithm.

Cited By

• http://scholar.google.com/scholar?q=%222017%22+Learning+to+Discover+Cross-Domain+Relations+with+Generative+Adversarial+Networks

Quotes

Abstract

While humans easily recognize relations between data from different domains without any supervision, learning to automatically discover them is in general very challenging and needs many ground-truth pairs that illustrate the relations. To avoid costly pairing, we address the task of discovering cross-domain relations given unpaired data. We propose a method based on a generative adversarial network that learns to discover relations between different domains (DiscoGAN). Using the discovered relations, our proposed network successfully transfers style from one domain to another while preserving key attributes such as orientation and face identity.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2017 LearningtoDiscoverCrossDomainRe	Taeksoo Kim Moonsu Cha Hyunsoo Kim Jung Kwon Lee Jiwon Kim			Learning to Discover Cross-Domain Relations with Generative Adversarial Networks