Creative and diverse artwork generation using adversarial networks

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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Bibliographic Details
Main Authors: Haibo Chen, Lei Zhao, Lihong Qiu, Zhizhong Wang, Huiming Zhang, Wei Xing, Dongming Lu
Format: Article
Language:English
Published: Wiley 2020-12-01
Series:IET Computer Vision
Subjects:
creative artwork generation
diverse artwork generation
style transfer methods
artistic style
photographs
convolutional generative adversarial networks
Online Access:https://doi.org/10.1049/iet-cvi.2020.0014

Internet

https://doi.org/10.1049/iet-cvi.2020.0014

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