Multiple Generative Adversarial Networks Analysis for Predicting Photographers' Retouching

• URL: http://arxiv.org/abs/2006.02921v1
• Date: Wed, 3 Jun 2020 10:10:01 GMT
• Title: Multiple Generative Adversarial Networks Analysis for Predicting Photographers' Retouching
• Authors: Marc Bickel, Samuel Dubuis, S\'ebastien Gachoud
• Abstract summary: This study aims to explore the possibility to use deep learning methods and more specifically, generative adversarial networks (GANs) to mimic artists' retouching.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: 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.

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