Creative and diverse artwork generation using adversarial networks

Existing style transfer methods have achieved great success in artwork generation by transferring artistic styles onto everyday photographs while keeping their contents unchanged. Despite this success, these methods have one inherent limitation: they cannot produce newly created image contents, lack...

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Auteurs principaux:	Haibo Chen, Lei Zhao, Lihong Qiu, Zhizhong Wang, Huiming Zhang, Wei Xing, Dongming Lu
Format:	Artigo
Langue:	Inglês
Publié:	Wiley 2020-12-01
Collection:	IET Computer Vision
Sujets:	creative artwork generation diverse artwork generation style transfer methods artistic style photographs convolutional generative adversarial networks
Accès en ligne:	https://doi.org/10.1049/iet-cvi.2020.0014
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