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In a paper submitted to the NeurIPS 2020 Machine Learning for Creativity and Design workshop, Pinkney and Adler present their research, which enables image generation in novel domains and with a degree of creative control on the output. The team’s resolution dependant GAN interpolation method combines high resolution layers of an FFHQ model with low resolution layers from a model transferred to animated character faces to enable the combination of realistic facial textures with the structural characteristics of a cartoon.

Here is a quick read: NeurIPS 2020 Workshop | Indie GAN Interpolation Method Turns Selfies Into Cartoon Characters

The paper Resolution Dependant GAN Interpolation for Controllable Image Synthesis Between Domains is on arXiv.

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Categories: MACHINE LEARNING

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