Multiple Generative Adversarial Networks Analysis for Predicting Photographers' Retouching

Anyone can take a photo, but not everybody has the ability to retouch their pictures and obtain result close to professional. Since it is not possible to ask experts to retouch thousands of pictures, we thought about teaching a piece of software how to reproduce the work of those said experts. This...

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Bibliographic Details
Published in:arXiv.org 2020-06
Main Authors: Bickel, Marc, Dubuis, Samuel, Gachoud, Sébastien
Format: Article
Language:English
Subjects:
Artists
Generative adversarial networks
Machine learning
Pictures
Retouching
Online Access:Get full text
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Summary:Anyone can take a photo, but not everybody has the ability to retouch their pictures and obtain result close to professional. Since it is not possible to ask experts to retouch thousands of pictures, we thought about teaching a piece of software how to reproduce the work of those said experts. This study aims to explore the possibility to use deep learning methods and more specifically, generative adversarial networks (GANs), to mimic artists' retouching and find which one of the studied models provides the best results.
ISSN:2331-8422