TY  - GEN
A1  - Reimann, Max
A1  - Klingbeil, Mandy
A1  - Pasewaldt, Sebastian
A1  - Semmo, Amir
A1  - Trapp, Matthias
A1  - Döllner, Jürgen Roland Friedrich
ED  - Sourin, A Sourina
T1  - MaeSTrO: A Mobile App for Style Transfer Orchestration using Neural Networks
T2  - International Conference on Cyberworlds (CW)
N2  - Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expression, the technology still faces inherent limitations in providing low-level controls for localized image stylization. This work enhances state-of-the-art neural style transfer techniques by a generalized user interface with interactive tools to facilitate a creative and localized editing process. Thereby, we first propose a problem characterization representing trade-offs between visual quality, run-time performance, and user control. We then present MaeSTrO, a mobile app for orchestration of neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors. At this, first user tests indicate different levels of satisfaction for the implemented techniques and interaction design.
KW  - non-photorealistic rendering
KW  - style transfer
Y1  - 2018
SN  - 978-1-5386-7315-7
U6  - https://doi.org/10.1109/CW.2018.00016
SP  - 9
EP  - 16
PB  - IEEE
CY  - New York
ER  -