  The Fast Style Transfer methods have been recently proposed to transfer a
photograph to an artistic style in real-time. This task involves controlling
the stroke size in the stylized results, which remains an open challenge. In
this paper, we present a stroke controllable style transfer network that can
achieve continuous and spatial stroke size control. By analyzing the factors
that influence the stroke size, we propose to explicitly account for the
receptive field and the style image scales. We propose a StrokePyramid module
to endow the network with adaptive receptive fields, and two training
strategies to achieve faster convergence and augment new stroke sizes upon a
trained model respectively. By combining the proposed runtime control
strategies, our network can achieve continuous changes in stroke sizes and
produce distinct stroke sizes in different spatial regions within the same
output image.
