Výsledky vyhledávání - "Tanaka, Kiyoshi"

This paper proposes a series of new approaches to improve Generative Adversarial Network (GAN) for conditional image synthesis and we name the proposed model as ArtGAN. One of the key innovation of ArtGAN is that, the gradient of the loss function w.

Externí odkaz: http://arxiv.org/abs/1708.09533

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ArtGAN: Artwork Synthesis with Conditional Categorical GANs

Autor: Tan, Wei Ren, Chan, Chee Seng, Aguirre, Hernan, Tanaka, Kiyoshi

This paper proposes an extension to the Generative Adversarial Networks (GANs), namely as ARTGAN to synthetically generate more challenging and complex images such as artwork that have abstract characteristics. This is in contrast to most of the curr

Externí odkaz: http://arxiv.org/abs/1702.03410

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