Approaches for Local Artistic Control of Mobile Neural Style Transfer
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
ACM
Abstract
This work presents enhancements to state-of-the-art adaptive neural style transfer techniques, thereby providing a generalized user interface with creativity tool support for lower-level local control to facilitate the demanding interactive editing on mobile devices. The approaches are implemented in a mobile app that is designed for orchestration of three neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors to perform location-based filtering and direct the composition. Based on first user tests, we conclude with insights, showing different levels of satisfaction for the implemented techniques and user interaction design, pointing out directions for future research.
Description
@inproceedings{10.1145:3229147.3229188,
booktitle = {Expressive: Computational Aesthetics, Sketch-Based Interfaces and Modeling, Non-Photorealistic Animation and Rendering},
editor = {Aydın, Tunç and Sýkora, Daniel},
title = {{Approaches for Local Artistic Control of Mobile Neural Style Transfer}},
author = {Reimann, Max and Klingbeil, Mandy and Pasewaldt, Sebastian and Semmo, Amir and Döllner, Jürgen and Trapp, Matthias},
year = {2018},
publisher = {ACM},
ISSN = {2079-8679},
ISBN = {978-1-4503-5892-7},
DOI = {10.1145/3229147.3229188}
}