Wasserstein divergence for GANs

In many domains of computer vision, generative adversarial networks (GANs) have achieved great success, among which the family of Wasserstein GANs (WGANs) is considered to be state-of-the-art due to the theoretical contributions and competitive qualitative performance. However, it is very challengin...

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Bibliographic Details
Main Authors: WU, J., HUANG, Zhiwu, THOMA, J., ACHARYA, D., VAN, Gool L.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sis_research/6402
https://ink.library.smu.edu.sg/context/sis_research/article/7405/viewcontent/Wasserstein_Divergence_for_GANs.pdf
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Institution: Singapore Management University
Language: English

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