  We present StyleTune, a mobile app for interactive multi-level control of
neural style transfers that facilitates creative adjustments of style elements
and enables high output fidelity. In contrast to current mobile neural style
transfer apps, StyleTune supports users to adjust both the size and orientation
of style elements, such as brushstrokes and texture patches, on a global as
well as local level. To this end, we propose a novel stroke-adaptive
feed-forward style transfer network, that enables control over stroke size and
intensity and allows a larger range of edits than current approaches. For
additional level-of-control, we propose a network agnostic method for
stroke-orientation adjustment by utilizing the rotation-variance of CNNs. To
achieve high output fidelity, we further add a patch-based style transfer
method that enables users to obtain output resolutions of more than 20
Megapixel. Our approach empowers users to create many novel results that are
not possible with current mobile neural style transfer apps.
