WHITE-BOX CARTOONIZATION USING AN EXTENDED GAN FRAMEWORK

نویسندگان

چکیده

In the present study, we propose to implement a new framework for estimating generative models via an adversarial process extend existing GAN and develop white-box controllable image cartoonization, which can generate high-quality cartooned images/videos from real-world photos videos. The learning purposes of our system are based on three distinct representations: surface representation, structure texture representation. representation refers smooth images. relates sparse colour blocks compresses generic content. shows texture, curves, features in cartoon Generative Adversarial Network (GAN) decomposes images into different representations learns them This decomposition makes more flexible allows users make changes required output. approach overcomes any previous terms maintaining clarity, colours, textures, shapes yet showing characteristics

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ژورنال

عنوان ژورنال: International journal of engineering applied science and technology

سال: 2021

ISSN: ['2455-2143']

DOI: https://doi.org/10.33564/ijeast.2021.v05i12.049